Imaging evaluation of traumatic thoracolumbar spine injuries: Radiological review

PubMed Central

Gamanagatti, Shivanand; Rathinam, Deepak; Rangarajan, Krithika; Kumar, Atin; Farooque, Kamran; Sharma, Vijay

2015-01-01

Spine fractures account for a large portion of musculoskeletal injuries worldwide. A classification of spine fractures is necessary in order to develop a common language for treatment indications and outcomes. Several classification systems have been developed based on injury anatomy or mechanisms of action, but they have demonstrated poor reliability, have yielded little prognostic information, and have not been widely used. For this reason, the Arbeitsgemeinschaftfür Osteosynthesefragen (AO) committee has classified thorocolumbar spine injuries based on the pathomorphological criteria into3 types (A: Compression; B: Distraction; C: Axial torque and rotational deformity). Each of these types is further divided into 3 groups and 3 subgroups reflecting progressive scale of morphological damage and the degree of instability. Because of its highly detailed sub classifications, the AO system has shown limited interobserver variability. It is similar to its predecessors in that it does not incorporate the patient’s neurologic status.The need for a reliable, reproducible, clinically relevant, prognostic classification system with an optimal balance of ease of use and detail of injury description contributed to the development of a new classification system, the thoracolumbar injury classification and severity score (TLICS). The TLICS defines injury based on three clinical characteristics: injury morphology, integrity of the posterior ligamentous complex, and neurologic status of the patient. The severity score offers prognostic information and is helpful in decision making about surgical vs nonsurgical management. PMID:26435776

Methods in hair research: how to objectively distinguish between anagen and catagen in human hair follicle organ culture.

PubMed

Kloepper, Jennifer Elisabeth; Sugawara, Koji; Al-Nuaimi, Yusur; Gáspár, Erzsébet; van Beek, Nina; Paus, Ralf

2010-03-01

The organ culture of human scalp hair follicles (HFs) is the best currently available assay for hair research in the human system. In order to determine the hair growth-modulatory effects of agents in this assay, one critical read-out parameter is the assessment of whether the test agent has prolonged anagen duration or induced catagen in vitro. However, objective criteria to distinguish between anagen VI HFs and early catagen in human HF organ culture, two hair cycle stages with a deceptively similar morphology, remain to be established. Here, we develop, document and test an objective classification system that allows to distinguish between anagen VI and early catagen in organ-cultured human HFs, using both qualitative and quantitative parameters that can be generated by light microscopy or immunofluorescence. Seven qualitative classification criteria are defined that are based on assessing the morphology of the hair matrix, the dermal papilla and the distribution of pigmentary markers (melanin, gp100). These are complemented by ten quantitative parameters. We have tested this classification system by employing the clinically used topical hair growth inhibitor, eflornithine, and show that eflornithine indeed produces the expected premature catagen induction, as identified by the novel classification criteria reported here. Therefore, this classification system offers a standardized, objective and reproducible new experimental method to reliably distinguish between human anagen VI and early catagen HFs in organ culture.

Pathohistological classification systems in gastric cancer: Diagnostic relevance and prognostic value

PubMed Central

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-01-01

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer. PMID:24914328

Correlation-based pattern recognition for implantable defibrillators.

PubMed Central

Wilkins, J.

1996-01-01

An estimated 300,000 Americans die each year from cardiac arrhythmias. Historically, drug therapy or surgery were the only treatment options available for patients suffering from arrhythmias. Recently, implantable arrhythmia management devices have been developed. These devices allow abnormal cardiac rhythms to be sensed and corrected in vivo. Proper arrhythmia classification is critical to selecting the appropriate therapeutic intervention. The classification problem is made more challenging by the power/computation constraints imposed by the short battery life of implantable devices. Current devices utilize heart rate-based classification algorithms. Although easy to implement, rate-based approaches have unacceptably high error rates in distinguishing supraventricular tachycardia (SVT) from ventricular tachycardia (VT). Conventional morphology assessment techniques used in ECG analysis often require too much computation to be practical for implantable devices. In this paper, a computationally-efficient, arrhythmia classification architecture using correlation-based morphology assessment is presented. The architecture classifies individuals heart beats by assessing similarity between an incoming cardiac signal vector and a series of prestored class templates. A series of these beat classifications are used to make an overall rhythm assessment. The system makes use of several new results in the field of pattern recognition. The resulting system achieved excellent accuracy in discriminating SVT and VT. PMID:8947674

What nephrolopathologists need to know about antiphospholipid syndrome-associated nephropathy: Is it time for formulating a classification for renal morphologic lesions?

PubMed

Mubarak, Muhammed; Nasri, Hamid

2014-01-01

Antiphospholipid syndrome (APS) is a systemic autoimmune disorder which commonly affects kidneys. Directory of Open Access Journals (DOAJ), Google Scholar, PubMed (NLM), LISTA (EBSCO) and Web of Science have been searched. There is sufficient epidemiological, clinical and histopathological evidence to show that antiphospholipid syndrome is a distinctive lesion caused by antiphospholipid antibodies in patients with different forms of antiphospholipid syndrome. It is now time to devise a classification for an accurate diagnosis and prognostication of the disease. Now that the morphological lesions of APSN are sufficiently well characterized, it is prime time to devise a classification which is of diagnostic and prognostic utility in this disease.

What nephrolopathologists need to know about antiphospholipid syndrome-associated nephropathy: Is it time for formulating a classification for renal morphologic lesions?

PubMed Central

Mubarak, Muhammed; Nasri, Hamid

2014-01-01

Context: Antiphospholipid syndrome (APS) is a systemic autoimmune disorder which commonly affects kidneys. Evidence Acquisitions: Directory of Open Access Journals (DOAJ), Google Scholar, PubMed (NLM), LISTA (EBSCO) and Web of Science have been searched. Results: There is sufficient epidemiological, clinical and histopathological evidence to show that antiphospholipid syndrome is a distinctive lesion caused by antiphospholipid antibodies in patients with different forms of antiphospholipid syndrome. It is now time to devise a classification for an accurate diagnosis and prognostication of the disease. Conclusions: Now that the morphological lesions of APSN are sufficiently well characterized, it is prime time to devise a classification which is of diagnostic and prognostic utility in this disease. PMID:24644536

Gaia eclipsing binary and multiple systems. Supervised classification and self-organizing maps

NASA Astrophysics Data System (ADS)

Süveges, M.; Barblan, F.; Lecoeur-Taïbi, I.; Prša, A.; Holl, B.; Eyer, L.; Kochoska, A.; Mowlavi, N.; Rimoldini, L.

2017-07-01

Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys. Aims: We aim to aid the extraction of samples of eclipsing binaries from such databases and to provide basic information about the objects. We intend to estimate class labels according to two different, well-known classification systems, one based on the light curve morphology (EA/EB/EW classes) and the other based on the physical characteristics of the binary system (system morphology classes; detached through overcontact systems). Furthermore, we explore low-dimensional surfaces along which the light curves of eclipsing binaries are concentrated, and consider their use in the characterization of the binary systems and in the exploration of biases of the full unknown Gaia data with respect to the training sets. Methods: We have explored the performance of principal component analysis (PCA), linear discriminant analysis (LDA), Random Forest classification and self-organizing maps (SOM) for the above aims. We pre-processed the photometric time series by combining a double Gaussian profile fit and a constrained smoothing spline, in order to de-noise and interpolate the observed light curves. We achieved further denoising, and selected the most important variability elements from the light curves using PCA. Supervised classification was performed using Random Forest and LDA based on the PC decomposition, while SOM gives a continuous 2-dimensional manifold of the light curves arranged by a few important features. We estimated the uncertainty of the supervised methods due to the specific finite training set using ensembles of models constructed on randomized training sets. Results: We obtain excellent results (about 5% global error rate) with classification into light curve morphology classes on the Hipparcos data. The classification into system morphology classes using the Catalog and Atlas of Eclipsing binaries (CALEB) has a higher error rate (about 10.5%), most importantly due to the (sometimes strong) similarity of the photometric light curves originating from physically different systems. When trained on CALEB and then applied to Kepler-detected eclipsing binaries subsampled according to Gaia observing times, LDA and SOM provide tractable, easy-to-visualize subspaces of the full (functional) space of light curves that summarize the most important phenomenological elements of the individual light curves. The sequence of light curves ordered by their first linear discriminant coefficient is compared to results obtained using local linear embedding. The SOM method proves able to find a 2-dimensional embedded surface in the space of the light curves which separates the system morphology classes in its different regions, and also identifies a few other phenomena, such as the asymmetry of the light curves due to spots, eccentric systems, and systems with a single eclipse. Furthermore, when data from other surveys are projected to the same SOM surface, the resulting map yields a good overview of the general biases and distortions due to differences in time sampling or population.

Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical tree model of hematopoesis

NASA Astrophysics Data System (ADS)

Krappe, Sebastian; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

2016-03-01

The morphological differentiation of bone marrow is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually under the use of bright field microscopy. This is a time-consuming, subjective, tedious and error-prone process. Furthermore, repeated examinations of a slide may yield intra- and inter-observer variances. For that reason a computer assisted diagnosis system for bone marrow differentiation is pursued. In this work we focus (a) on a new method for the separation of nucleus and plasma parts and (b) on a knowledge-based hierarchical tree classifier for the differentiation of bone marrow cells in 16 different classes. Classification trees are easily interpretable and understandable and provide a classification together with an explanation. Using classification trees, expert knowledge (i.e. knowledge about similar classes and cell lines in the tree model of hematopoiesis) is integrated in the structure of the tree. The proposed segmentation method is evaluated with more than 10,000 manually segmented cells. For the evaluation of the proposed hierarchical classifier more than 140,000 automatically segmented bone marrow cells are used. Future automated solutions for the morphological analysis of bone marrow smears could potentially apply such an approach for the pre-classification of bone marrow cells and thereby shortening the examination time.

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Congenital Differences of the Upper Extremity: Classification and Treatment Principles

PubMed Central

2011-01-01

For hand surgeons, the treatment of children with congenital differences of the upper extremity is challenging because of the diverse spectrum of conditions encountered, but the task is also rewarding because it provides surgeons with the opportunity to impact a child's growth and development. An ideal classification of congenital differences of the upper extremity would reflect the full spectrum of morphologic abnormalities and encompass etiology, a guide to treatment, and provide prognoses. In this report, I review current classification systems and discuss their contradictions and limitations. In addition, I present a modified classification system and provide treatment principles. As our understanding of the etiology of congenital differences of the upper extremity increases and as experience of treating difficult cases accumulates, even an ideal classification system and optimal treatment strategies will undoubtedly continue to evolve. PMID:21909463

Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linott, C.; Slosar, A.; Lintott, C.

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly availablemore » and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.« less

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS

NASA Astrophysics Data System (ADS)

Simmons, B. D.; Lintott, Chris; Willett, Kyle W.; Masters, Karen L.; Kartaltepe, Jeyhan S.; Häußler, Boris; Kaviraj, Sugata; Krawczyk, Coleman; Kruk, S. J.; McIntosh, Daniel H.; Smethurst, R. J.; Nichol, Robert C.; Scarlata, Claudia; Schawinski, Kevin; Conselice, Christopher J.; Almaini, Omar; Ferguson, Henry C.; Fortson, Lucy; Hartley, William; Kocevski, Dale; Koekemoer, Anton M.; Mortlock, Alice; Newman, Jeffrey A.; Bamford, Steven P.; Grogin, N. A.; Lucas, Ray A.; Hathi, Nimish P.; McGrath, Elizabeth; Peth, Michael; Pforr, Janine; Rizer, Zachary; Wuyts, Stijn; Barro, Guillermo; Bell, Eric F.; Castellano, Marco; Dahlen, Tomas; Dekel, Avishai; Ownsworth, Jamie; Faber, Sandra M.; Finkelstein, Steven L.; Fontana, Adriano; Galametz, Audrey; Grützbauch, Ruth; Koo, David; Lotz, Jennifer; Mobasher, Bahram; Mozena, Mark; Salvato, Mara; Wiklind, Tommy

2017-02-01

We present quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications, the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of `smooth' galaxies with parametric morphologies to select a sample of featureless discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

PubMed Central

Di Ruberto, Cecilia; Kocher, Michel

2018-01-01

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images. PMID:29419781

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology.

PubMed

Loddo, Andrea; Di Ruberto, Cecilia; Kocher, Michel

2018-02-08

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

Bayesian classification for the selection of in vitro human embryos using morphological and clinical data.

PubMed

Morales, Dinora Araceli; Bengoetxea, Endika; Larrañaga, Pedro; García, Miguel; Franco, Yosu; Fresnada, Mónica; Merino, Marisa

2008-05-01

In vitro fertilization (IVF) is a medically assisted reproduction technique that enables infertile couples to achieve successful pregnancy. Given the uncertainty of the treatment, we propose an intelligent decision support system based on supervised classification by Bayesian classifiers to aid to the selection of the most promising embryos that will form the batch to be transferred to the woman's uterus. The aim of the supervised classification system is to improve overall success rate of each IVF treatment in which a batch of embryos is transferred each time, where the success is achieved when implantation (i.e. pregnancy) is obtained. Due to ethical reasons, different legislative restrictions apply in every country on this technique. In Spain, legislation allows a maximum of three embryos to form each transfer batch. As a result, clinicians prefer to select the embryos by non-invasive embryo examination based on simple methods and observation focused on morphology and dynamics of embryo development after fertilization. This paper proposes the application of Bayesian classifiers to this embryo selection problem in order to provide a decision support system that allows a more accurate selection than with the actual procedures which fully rely on the expertise and experience of embryologists. For this, we propose to take into consideration a reduced subset of feature variables related to embryo morphology and clinical data of patients, and from this data to induce Bayesian classification models. Results obtained applying a filter technique to choose the subset of variables, and the performance of Bayesian classifiers using them, are presented.

Cell dynamic morphology classification using deep convolutional neural networks.

PubMed

Li, Heng; Pang, Fengqian; Shi, Yonggang; Liu, Zhiwen

2018-05-15

Cell morphology is often used as a proxy measurement of cell status to understand cell physiology. Hence, interpretation of cell dynamic morphology is a meaningful task in biomedical research. Inspired by the recent success of deep learning, we here explore the application of convolutional neural networks (CNNs) to cell dynamic morphology classification. An innovative strategy for the implementation of CNNs is introduced in this study. Mouse lymphocytes were collected to observe the dynamic morphology, and two datasets were thus set up to investigate the performances of CNNs. Considering the installation of deep learning, the classification problem was simplified from video data to image data, and was then solved by CNNs in a self-taught manner with the generated image data. CNNs were separately performed in three installation scenarios and compared with existing methods. Experimental results demonstrated the potential of CNNs in cell dynamic morphology classification, and validated the effectiveness of the proposed strategy. CNNs were successfully applied to the classification problem, and outperformed the existing methods in the classification accuracy. For the installation of CNNs, transfer learning was proved to be a promising scheme. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Molecular phylogenetics and character evolution of morphologically diverse groups, Dendrobium section Dendrobium and allies

PubMed Central

Takamiya, Tomoko; Wongsawad, Pheravut; Sathapattayanon, Apirada; Tajima, Natsuko; Suzuki, Shunichiro; Kitamura, Saki; Shioda, Nao; Handa, Takashi; Kitanaka, Susumu; Iijima, Hiroshi; Yukawa, Tomohisa

2014-01-01

It is always difficult to construct coherent classification systems for plant lineages having diverse morphological characters. The genus Dendrobium, one of the largest genera in the Orchidaceae, includes ∼1100 species, and enormous morphological diversification has hindered the establishment of consistent classification systems covering all major groups of this genus. Given the particular importance of species in Dendrobium section Dendrobium and allied groups as floriculture and crude drug genetic resources, there is an urgent need to establish a stable classification system. To clarify phylogenetic relationships in Dendrobium section Dendrobium and allied groups, we analysed the macromolecular characters of the group. Phylogenetic analyses of 210 taxa of Dendrobium were conducted on DNA sequences of internal transcribed spacer (ITS) regions of 18S–26S nuclear ribosomal DNA and the maturase-coding gene (matK) located in an intron of the plastid gene trnK using maximum parsimony and Bayesian methods. The parsimony and Bayesian analyses revealed 13 distinct clades in the group comprising section Dendrobium and its allied groups. Results also showed paraphyly or polyphyly of sections Amblyanthus, Aporum, Breviflores, Calcarifera, Crumenata, Dendrobium, Densiflora, Distichophyllae, Dolichocentrum, Holochrysa, Oxyglossum and Pedilonum. On the other hand, the monophyly of section Stachyobium was well supported. It was found that many of the morphological characters that have been believed to reflect phylogenetic relationships are, in fact, the result of convergence. As such, many of the sections that have been recognized up to this point were found to not be monophyletic, so recircumscription of sections is required. PMID:25107672

The Evolution of the Observed Hubble Sequence over the past 6Gyr

NASA Astrophysics Data System (ADS)

Delgado-Serrano, R.; Hammer, F.; Yang, Y. B.; Puech, M.; Flores, H.; Rodrigues, M.

2011-10-01

During the past years we have confronted serious problems of methodology concerning the morphological and kinematic classification of distant galaxies. This has forced us to create a new simple and effective morphological classification methodology, in order to guarantee a morpho-kinematic correlation, make the reproducibility easier and restrict the classification subjectivity. Giving the characteristic of our morphological classification, we have thus been able to apply the same methodology, using equivalent observations, to representative samples of local and distant galaxies. It has allowed us to derive, for the first time, the distant Hubble sequence (~6 Gyr ago), and determine a morphological evolution of galaxies over the past 6 Gyr. Our results strongly suggest that more than half of the present-day spirals had peculiar morphologies, 6 Gyr ago.

[Outstanding problems of normal and pathological morphology of the diffuse endocrine system].

PubMed

Iaglov, V V; Iaglova, N V

2011-01-01

The diffuse endocrine system (DES)--a mosaic-cellular endoepithelial gland--is the biggest part of the human endocrine system. Scientists used to consider cells of DES as neuroectodermal. According to modem data cells of DES are different cytogenetic types because they develop from the different embryonic blastophyllum. So that any hormone-active tumors originated from DES of the digestive, respiratory and urogenital system shouldn't be considered as neuroendocrinal tumors. The basic problems of DES morphology and pathology are the creation of scientifically substantiated histogenetic classification of DES tumors.

The Reliability of Galaxy Classifications by Citizen Scientists

NASA Astrophysics Data System (ADS)

Francis, Lennox; Kautsch, Stefan J.; Bizyaev, Dmitry

2017-01-01

Citizen scientists are becoming more and more important in helping professionals working through big data. An example in astronomy is crowdsourced galaxy classification. But how reliable are these classifications for studies of galaxy evolution? We present a tool in order to investigate those morphological classifications and test it on a diverse population on our campus. We observe a slight offset towards earlier Hubble types in the crowdsourced morphologies, when compared to professional classifications.

Barrier island morphodynamic classification based on lidar metrics for north Assateague Island, Maryland

USGS Publications Warehouse

Brock, John C.; Krabill, William; Sallenger, Asbury H.

2004-01-01

In order to reap the potential of airborne lidar surveys to provide geological information useful in understanding coastal sedimentary processes acting on various time scales, a new set of analysis methods are needed. This paper presents a multi-temporal lidar analysis of north Assateague Island, Maryland, and demonstrates the calculation of lidar metrics that condense barrier island morphology and morphological change into attributed linear features that may be used to analyze trends in coastal evolution. The new methods proposed in this paper are also of significant practical value, because lidar metric analysis reduces large volumes of point elevations into linear features attributed with essential morphological variables that are ideally suited for inclusion in Geographic Information Systems. A morphodynamic classification of north Assategue Island for a recent 10 month time period that is based on the recognition of simple patterns described by lidar change metrics is presented. Such morphodynamic classification reveals the relative magnitude and the fine scale alongshore variation in the importance of coastal changes over the study area during a defined time period. More generally, through the presentation of this morphodynamic classification of north Assateague Island, the value of lidar metrics in both examining large lidar data sets for coherent trends and in building hypotheses regarding processes driving barrier evolution is demonstrated

[Evaluation of traditional pathological classification at molecular classification era for gastric cancer].

PubMed

Yu, Yingyan

2014-01-01

Histopathological classification is in a pivotal position in both basic research and clinical diagnosis and treatment of gastric cancer. Currently, there are different classification systems in basic science and clinical application. In medical literatures, different classifications are used including Lauren and WHO systems, which have confused many researchers. Lauren classification has been proposed for half a century, but is still used worldwide. It shows many advantages of simple, easy handling with prognostic significance. The WHO classification scheme is better than Lauren classification in that it is continuously being revised according to the progress of gastric cancer, and is always used in the clinical and pathological diagnosis of common scenarios. Along with the progression of genomics, transcriptomics, proteomics, metabolomics researches, molecular classification of gastric cancer becomes the current hot topics. The traditional therapeutic approach based on phenotypic characteristics of gastric cancer will most likely be replaced with a gene variation mode. The gene-targeted therapy against the same molecular variation seems more reasonable than traditional chemical treatment based on the same morphological change.

The new WHO 2016 classification of brain tumors-what neurosurgeons need to know.

PubMed

Banan, Rouzbeh; Hartmann, Christian

2017-03-01

The understanding of molecular alterations of tumors has severely changed the concept of classification in all fields of pathology. The availability of high-throughput technologies such as next-generation sequencing allows for a much more precise definition of tumor entities. Also in the field of brain tumors a dramatic increase of knowledge has occurred over the last years partially calling into question the purely morphologically based concepts that were used as exclusive defining criteria in the WHO 2007 classification. Review of the WHO 2016 classification of brain tumors as well as a search and review of publications in the literature relevant for brain tumor classification from 2007 up to now. The idea of incorporating the molecular features in classifying tumors of the central nervous system led the authors of the new WHO 2016 classification to encounter inevitable conceptual problems, particularly with respect to linking morphology to molecular alterations. As a solution they introduced the concept of a "layered diagnosis" to the classification of brain tumors that still allows at a lower level a purely morphologically based diagnosis while partially forcing the incorporation of molecular characteristics for an "integrated diagnosis" at the highest diagnostic level. In this context the broad availability of molecular assays was debated. On the one hand molecular antibodies specifically targeting mutated proteins should be available in nearly all neuropathological laboratories. On the other hand, different high-throughput assays are accessible only in few first-world neuropathological institutions. As examples oligodendrogliomas are now primarily defined by molecular characteristics since the required assays are generally established, whereas molecular grouping of ependymomas, found to clearly outperform morphologically based tumor interpretation, was rejected from inclusion in the WHO 2016 classification because the required assays are currently only established in a small number of institutions. In summary, while neuropathologists have now encountered various challenges in the transitional phase from the previous WHO 2007 version to the new WHO 2016 classification of brain tumors, clinical neurooncologists now face many new diagnoses allowing a clearly improved understanding that could offer them more effective therapeutic opportunities in neurooncological treatment. The new WHO 2016 classification presumably presents the highest number of modifications since the initial WHO classification of 1979 and thereby forces all professionals in the field of neurooncology to intensively understand the new concepts. This review article aims to present the basic concepts of the new WHO 2016 brain tumor classification for neurosurgeons with a focus on neurooncology.

Differentiation of arterioles from venules in mouse histology images using machine learning

NASA Astrophysics Data System (ADS)

Elkerton, J. S.; Xu, Yiwen; Pickering, J. G.; Ward, Aaron D.

2016-03-01

Analysis and morphological comparison of arteriolar and venular networks are essential to our understanding of multiple diseases affecting every organ system. We have developed and evaluated the first fully automatic software system for differentiation of arterioles from venules on high-resolution digital histology images of the mouse hind limb immunostained for smooth muscle α-actin. Classifiers trained on texture and morphologic features by supervised machine learning provided excellent classification accuracy for differentiation of arterioles and venules, achieving an area under the receiver operating characteristic curve of 0.90 and balanced false-positive and false-negative rates. Feature selection was consistent across cross-validation iterations, and a small set of three features was required to achieve the reported performance, suggesting potential generalizability of the system. This system eliminates the need for laborious manual classification of the hundreds of microvessels occurring in a typical sample, and paves the way for high-throughput analysis the arteriolar and venular networks in the mouse.

Combining convolutional neural networks and Hough Transform for classification of images containing lines

NASA Astrophysics Data System (ADS)

Sheshkus, Alexander; Limonova, Elena; Nikolaev, Dmitry; Krivtsov, Valeriy

2017-03-01

In this paper, we propose an expansion of convolutional neural network (CNN) input features based on Hough Transform. We perform morphological contrasting of source image followed by Hough Transform, and then use it as input for some convolutional filters. Thus, CNNs computational complexity and the number of units are not affected. Morphological contrasting and Hough Transform are the only additional computational expenses of introduced CNN input features expansion. Proposed approach was demonstrated on the example of CNN with very simple structure. We considered two image recognition problems, that were object classification on CIFAR-10 and printed character recognition on private dataset with symbols taken from Russian passports. Our approach allowed to reach noticeable accuracy improvement without taking much computational effort, which can be extremely important in industrial recognition systems or difficult problems utilising CNNs, like pressure ridge analysis and classification.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed

Rocha, José C; Passalia, Felipe; Matos, Felipe D; Maserati, Marc P; Alves, Mayra F; Almeida, Tamie G de; Cardoso, Bruna L; Basso, Andrea C; Nogueira, Marcelo F G

2016-08-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed Central

Rocha, José C.; Passalia, Felipe; Matos, Felipe D.; Maserati Jr, Marc P.; Alves, Mayra F.; de Almeida, Tamie G.; Cardoso, Bruna L.; Basso, Andrea C.; Nogueira, Marcelo F. G.

2016-01-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment. PMID:27584609

A Global Classification System for Catchment Hydrology

NASA Astrophysics Data System (ADS)

Woods, R. A.

2004-05-01

It is a shocking state of affairs - there is no underpinning scientific taxonomy of catchments. There are widely used global classification systems for climate, river morphology, lakes and wetlands, but for river catchments there exists only a plethora of inconsistent, incomplete regional schemes. By proceeding without a common taxonomy for catchments, freshwater science has missed one of its key developmental stages, and has leapt from definition of phenomena to experiments, theories and models, without the theoretical framework of a classification. I propose the development of a global hierarchical classification system for physical aspects of river catchments, to help underpin physical science in the freshwater environment and provide a solid foundation for classification of river ecosystems. Such a classification scheme can open completely new vistas in hydrology: for example it will be possible to (i) rationally transfer experimental knowledge of hydrological processes between basins anywhere in the world, provided they belong to the same class; (ii) perform meaningful meta-analyses in order to reconcile studies that show inconsistent results (iii) generate new testable hypotheses which involve locations worldwide.

A Stream Morphology Classification for Eco-hydraulic Purposes Based on Geospatial Data: a Solute Transport Application Case

NASA Astrophysics Data System (ADS)

Jiménez Jaramillo, M. A.; Camacho Botero, L. A.; Vélez Upegui, J. I.

2010-12-01

Variation in stream morphology along a basin drainage network leads to different hydraulic patterns and sediment transport processes. Moreover, solute transport processes along streams, and stream habitats for fisheries and microorganisms, rely on stream corridor structure, including elements such as bed forms, channel patterns, riparian vegetation, and the floodplain. In this work solute transport processes simulation and stream habitat identification are carried out at the basin scale. A reach-scale morphological classification system based on channel slope and specific stream power was implemented by using digital elevation models and hydraulic geometry relationships. Although the morphological framework allows identification of cascade, step-pool, plane bed and pool-riffle morphologies along the drainage network, it still does not account for floodplain configuration and bed-forms identification of those channel types. Hence, as a first application case in order to obtain parsimonious three-dimensional characterizations of drainage channels, the morphological framework has been updated by including topographical floodplain delimitation through a Multi-resolution Valley Bottom Flatness Index assessing, and a stochastic bed form representation of the step-pool morphology. Model outcomes were tested in relation to in-stream water storage for different flow conditions and representative travel times according to the Aggregated Dead Zone -ADZ- model conceptualization of solute transport processes.

In-depth morphological study of mesiobuccal root canal systems in maxillary first molars: review

PubMed Central

Chang, Seok-Woo; Lee, Jong-Ki; Lee, Yoon

2013-01-01

A common failure in endodontic treatment of the permanent maxillary first molars is likely to be caused by an inability to locate, clean, and obturate the second mesiobuccal (MB) canals. Because of the importance of knowledge on these additional canals, there have been numerous studies which investigated the maxillary first molar MB root canal morphology using in vivo and laboratory methods. In this article, the protocols, advantages and disadvantages of various methodologies for in-depth study of maxillary first molar MB root canal morphology were discussed. Furthermore, newly identified configuration types for the establishment of new classification system were suggested based on two image reformatting techniques of micro-computed tomography, which can be useful as a further 'Gold Standard' method for in-depth morphological study of complex root canal systems. PMID:23493453

Automated classification of articular cartilage surfaces based on surface texture.

PubMed

Stachowiak, G P; Stachowiak, G W; Podsiadlo, P

2006-11-01

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

Hyperspectral feature mapping classification based on mathematical morphology

NASA Astrophysics Data System (ADS)

Liu, Chang; Li, Junwei; Wang, Guangping; Wu, Jingli

2016-03-01

This paper proposed a hyperspectral feature mapping classification algorithm based on mathematical morphology. Without the priori information such as spectral library etc., the spectral and spatial information can be used to realize the hyperspectral feature mapping classification. The mathematical morphological erosion and dilation operations are performed respectively to extract endmembers. The spectral feature mapping algorithm is used to carry on hyperspectral image classification. The hyperspectral image collected by AVIRIS is applied to evaluate the proposed algorithm. The proposed algorithm is compared with minimum Euclidean distance mapping algorithm, minimum Mahalanobis distance mapping algorithm, SAM algorithm and binary encoding mapping algorithm. From the results of the experiments, it is illuminated that the proposed algorithm's performance is better than that of the other algorithms under the same condition and has higher classification accuracy.

Stroke Risk Stratification and its Validation using Ultrasonic Echolucent Carotid Wall Plaque Morphology: A Machine Learning Paradigm.

PubMed

Araki, Tadashi; Jain, Pankaj K; Suri, Harman S; Londhe, Narendra D; Ikeda, Nobutaka; El-Baz, Ayman; Shrivastava, Vimal K; Saba, Luca; Nicolaides, Andrew; Shafique, Shoaib; Laird, John R; Gupta, Ajay; Suri, Jasjit S

2017-01-01

Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque. Further, this paper presents a scientific validation system for stroke risk assessment. Both these innovations have never been presented before. The methodology consists of an automated segmentation system of the near wall and far wall regions in grayscale carotid B-mode ultrasound scans. Sixteen grayscale texture features are computed, and fed into the machine learning system. The training system utilizes the lumen diameter to create ground truth labels for the stratification of stroke risk. The cross-validation procedure is adapted in order to obtain the machine learning testing classification accuracy through the use of three sets of partition protocols: (5, 10, and Jack Knife). The mean classification accuracy over all the sets of partition protocols for the automated system in the far and near walls is 95.08% and 93.47%, respectively. The corresponding accuracies for the manual system are 94.06% and 92.02%, respectively. The precision of merit of the automated machine learning system when compared against manual risk assessment system are 98.05% and 97.53% for the far and near walls, respectively. The ROC of the risk assessment system for the far and near walls is close to 1.0 demonstrating high accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

Preplanetary Nebulae: A Hubble Space Telescope Imaging Survey and a New Morphological Classification System

NASA Technical Reports Server (NTRS)

Sahai, Raghvendra; Morris, Mark; Sanchez Contreras, Carmen; Claussen, Mark

2007-01-01

Using the Hubble Space Telescope (HST ), we have carried out a survey of candidate preplanetary nebulae (PPNs). We report here our discoveries of objects having well-resolved geometric structures, and we use the large sample of PPNs now imaged with HST (including previously studied objects in this class) to devise a comprehensive morphological classification system for this category of objects. The wide variety of aspherical morphologies which we have found for PPNs are qualitatively similar to those found for young planetary nebulae (PNs) in previous surveys. We also find prominent halos surrounding the central aspherical shapes in many of our objects; these are direct signatures of the undisturbed circumstellar envelopes of the progenitor AGB stars. Although the majority of these have surface brightness distributions consistent with a constant mass-loss rate with a constant expansion velocity, there are also examples of objects with varying mass-loss rates. As in our surveys of young PNs, we find no round PPNs. The similarities in morphologies between our survey objects and young PNs supports the view that the former are the progenitors of aspherical PNs. This suggests that the primary shaping of a PN does not occur during the PN phase via the fast radiative wind of the hot central star, but significantly earlier in its evolution.

A Visual Galaxy Classification Interface and its Classroom Application

NASA Astrophysics Data System (ADS)

Kautsch, Stefan J.; Phung, Chau; VanHilst, Michael; Castro, Victor H

2014-06-01

Galaxy morphology is an important topic in modern astronomy to understand questions concerning the evolution and formation of galaxies and their dark matter content. In order to engage students in exploring galaxy morphology, we developed a web-based, graphical interface that allows students to visually classify galaxy images according to various morphological types. The website is designed with HTML5, JavaScript, PHP, and a MySQL database. The classification interface provides hands-on research experience and training for students and interested clients, and allows them to contribute to studies of galaxy morphology. We present the first results of a pilot study and compare the visually classified types using our interface with that from automated classification routines.

A subgeneric classification of Selaginella (Selaginellaceae).

PubMed

Weststrand, Stina; Korall, Petra

2016-12-01

The lycophyte family Selaginellaceae includes approximately 750 herbaceous species worldwide, with the main species richness in the tropics and subtropics. We recently presented a phylogenetic analysis of Selaginellaceae based on DNA sequence data and, with the phylogeny as a framework, the study discussed the character evolution of the group focusing on gross morphology. Here we translate these findings into a new classification. To present a robust and useful classification, we identified well-supported monophyletic groups from our previous phylogenetic analysis of 223 species, which together represent the diversity of the family with respect to morphology, taxonomy, and geographical distribution. Care was taken to choose groups with supporting morphology. In this classification, we recognize a single genus Selaginella and seven subgenera: Selaginella, Rupestrae, Lepidophyllae, Gymnogynum, Exaltatae, Ericetorum, and Stachygynandrum. The subgenera are all well supported based on analysis of DNA sequence data and morphology. A key to the subgenera is presented. Our new classification is based on a well-founded hypothesis of the evolutionary relationships of Selaginella, and each subgenus can be identified by a suite of morphological features, most of them possible to study in the field. Our intention is that the classification will be useful not only to experts in the field, but also to a broader audience. © 2016 Weststrand and Korall. Published by the Botanical Society of America. This work is licensed under a Creative Commons Attribution License (CC-BY 4.0).

Morphological phylogeny of Tradescantia L. (Commelinaceae) sheds light on a new infrageneric classification for the genus and novelties on the systematics of subtribe Tradescantiinae

PubMed Central

Pellegrini, Marco O. O.

2017-01-01

Abstract Throughout the years, three infrageneric classifications were proposed for Tradescantia along with several informal groups and species complexes. The current infrageneric classification accepts 12 sections – with T. sect. Tradescantia being further divided into four series – and assimilates many concepts adopted by previous authors. Recent molecular-based phylogenetic studies indicate that the currently accepted sections might not represent monophyletic groups within Tradescantia. Based on newly gathered morphological data on the group, complemented with available micromorphological, cytological and phytochemical data, I present the first morphology-based evolutionary hypothesis for Tradescantia. Furthermore, I reduce subtribe Thyrsantheminae to a synonym of subtribe Tradescantiinae, and propose a new infrageneric classification for Tradescantia, based on the total evidence of the present morphological phylogeny, in accordance to the previously published molecular data. PMID:29118649

[A research on real-time ventricular QRS classification methods for single-chip-microcomputers].

PubMed

Peng, L; Yang, Z; Li, L; Chen, H; Chen, E; Lin, J

1997-05-01

Ventricular QRS classification is key technique of ventricular arrhythmias detection in single-chip-microcomputer based dynamic electrocardiogram real-time analyser. This paper adopts morphological feature vector including QRS amplitude, interval information to reveal QRS morphology. After studying the distribution of QRS morphology feature vector of MIT/BIH DB ventricular arrhythmia files, we use morphological feature vector cluster to classify multi-morphology QRS. Based on the method, morphological feature parameters changing method which is suitable to catch occasional ventricular arrhythmias is presented. Clinical experiments verify missed ventricular arrhythmia is less than 1% by this method.

Making Mosquito Taxonomy Useful: A Stable Classification of Tribe Aedini that Balances Utility with Current Knowledge of Evolutionary Relationships.

PubMed

Wilkerson, Richard C; Linton, Yvonne-Marie; Fonseca, Dina M; Schultz, Ted R; Price, Dana C; Strickman, Daniel A

2015-01-01

The tribe Aedini (Family Culicidae) contains approximately one-quarter of the known species of mosquitoes, including vectors of deadly or debilitating disease agents. This tribe contains the genus Aedes, which is one of the three most familiar genera of mosquitoes. During the past decade, Aedini has been the focus of a series of extensive morphology-based phylogenetic studies published by Reinert, Harbach, and Kitching (RH&K). Those authors created 74 new, elevated or resurrected genera from what had been the single genus Aedes, almost tripling the number of genera in the entire family Culicidae. The proposed classification is based on subjective assessments of the "number and nature of the characters that support the branches" subtending particular monophyletic groups in the results of cladistic analyses of a large set of morphological characters of representative species. To gauge the stability of RH&K's generic groupings we reanalyzed their data with unweighted parsimony jackknife and maximum-parsimony analyses, with and without ordering 14 of the characters as in RH&K. We found that their phylogeny was largely weakly supported and their taxonomic rankings failed priority and other useful taxon-naming criteria. Consequently, we propose simplified aedine generic designations that 1) restore a classification system that is useful for the operational community; 2) enhance the ability of taxonomists to accurately place new species into genera; 3) maintain the progress toward a natural classification based on monophyletic groups of species; and 4) correct the current classification system that is subject to instability as new species are described and existing species more thoroughly defined. We do not challenge the phylogenetic hypotheses generated by the above-mentioned series of morphological studies. However, we reduce the ranks of the genera and subgenera of RH&K to subgenera or informal species groups, respectively, to preserve stability as new data become available.

Making Mosquito Taxonomy Useful: A Stable Classification of Tribe Aedini that Balances Utility with Current Knowledge of Evolutionary Relationships

PubMed Central

Wilkerson, Richard C.; Linton, Yvonne-Marie; Fonseca, Dina M.; Schultz, Ted R.; Price, Dana C.; Strickman, Daniel A.

2015-01-01

The tribe Aedini (Family Culicidae) contains approximately one-quarter of the known species of mosquitoes, including vectors of deadly or debilitating disease agents. This tribe contains the genus Aedes, which is one of the three most familiar genera of mosquitoes. During the past decade, Aedini has been the focus of a series of extensive morphology-based phylogenetic studies published by Reinert, Harbach, and Kitching (RH&K). Those authors created 74 new, elevated or resurrected genera from what had been the single genus Aedes, almost tripling the number of genera in the entire family Culicidae. The proposed classification is based on subjective assessments of the “number and nature of the characters that support the branches” subtending particular monophyletic groups in the results of cladistic analyses of a large set of morphological characters of representative species. To gauge the stability of RH&K’s generic groupings we reanalyzed their data with unweighted parsimony jackknife and maximum-parsimony analyses, with and without ordering 14 of the characters as in RH&K. We found that their phylogeny was largely weakly supported and their taxonomic rankings failed priority and other useful taxon-naming criteria. Consequently, we propose simplified aedine generic designations that 1) restore a classification system that is useful for the operational community; 2) enhance the ability of taxonomists to accurately place new species into genera; 3) maintain the progress toward a natural classification based on monophyletic groups of species; and 4) correct the current classification system that is subject to instability as new species are described and existing species more thoroughly defined. We do not challenge the phylogenetic hypotheses generated by the above-mentioned series of morphological studies. However, we reduce the ranks of the genera and subgenera of RH&K to subgenera or informal species groups, respectively, to preserve stability as new data become available. PMID:26226613

Classification and phylogenetic analysis of Chinese hawthorn assessed by plant and pollen morphology.

PubMed

Ma, S L Y; Lu, Y M

2016-09-19

The Chinese hawthorn (Crataegus pinnatifida Bge. var. major N.E.Br.) is uniquely originated in northern China. The ecological and horticultural importance of Chinese hawthorn is considerable and some varieties are valued for their fruit or medicine extracts. Its taxonomy and phylogeny remain poorly understood. Apart from general plant morphological traits, pollen is an important trait for the classification of plants and their evolutionary origin. However, few studies have investigated the pollen of Chinese hawthorn. Here, an analysis of plant and pollen morphological characteristics was conducted in 57 cultivars from the Shenyang region. Thirty plant morphological characters and nine pollen grain characters were investigated. The plant morphological analysis revealed that the coefficient of variation for 13 traits was >20%, which indicates a high degree of variability. We also found that the pollen grains varied greatly in size, shape (from prolate to perprolate), and exine pattern (striate-perforate predominantly). The number of apertures was typically three. Based on these findings, we suggest that pollen morphology associated with plant morphological traits can be used for classification and phylogenetic analysis of Chinese hawthorn cultivars. In sum, our results provide new insights and constitute a scientific basis for future studies on the classification and evolution of Chinese hawthorn.

J-Plus: Morphological Classification Of Compact And Extended Sources By Pdf Analysis

NASA Astrophysics Data System (ADS)

López-Sanjuan, C.; Vázquez-Ramió, H.; Varela, J.; Spinoso, D.; Cristóbal-Hornillos, D.; Viironen, K.; Muniesa, D.; J-PLUS Collaboration

2017-10-01

We present a morphological classification of J-PLUS EDR sources into compact (i.e. stars) and extended (i.e. galaxies). Such classification is based on the Bayesian modelling of the concentration distribution, including observational errors and magnitude + sky position priors. We provide the star / galaxy probability of each source computed from the gri images. The comparison with the SDSS number counts support our classification up to r 21. The 31.7 deg² analised comprises 150k stars and 101k galaxies.

Rotation-invariant convolutional neural networks for galaxy morphology prediction

NASA Astrophysics Data System (ADS)

Dieleman, Sander; Willett, Kyle W.; Dambre, Joni

2015-06-01

Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey have resulted in the availability of very large collections of images, which have permitted population-wide analyses of galaxy morphology. Morphological analysis has traditionally been carried out mostly via visual inspection by trained experts, which is time consuming and does not scale to large (≳104) numbers of images. Although attempts have been made to build automated classification systems, these have not been able to achieve the desired level of accuracy. The Galaxy Zoo project successfully applied a crowdsourcing strategy, inviting online users to classify images by answering a series of questions. Unfortunately, even this approach does not scale well enough to keep up with the increasing availability of galaxy images. We present a deep neural network model for galaxy morphology classification which exploits translational and rotational symmetry. It was developed in the context of the Galaxy Challenge, an international competition to build the best model for morphology classification based on annotated images from the Galaxy Zoo project. For images with high agreement among the Galaxy Zoo participants, our model is able to reproduce their consensus with near-perfect accuracy (>99 per cent) for most questions. Confident model predictions are highly accurate, which makes the model suitable for filtering large collections of images and forwarding challenging images to experts for manual annotation. This approach greatly reduces the experts' workload without affecting accuracy. The application of these algorithms to larger sets of training data will be critical for analysing results from future surveys such as the Large Synoptic Survey Telescope.

Use of mutation profiles to refine the classification of endometrial carcinomas

PubMed Central

Cheang, Maggie CU; Wiegand, Kimberly; Senz, Janine; Tone, Alicia; Yang, Winnie; Prentice, Leah; Tse, Kane; Zeng, Thomas; McDonald, Helen; Schmidt, Amy P.; Mutch, David G.; McAlpine, Jessica N; Hirst, Martin; Shah, Sohrab P; Lee, Cheng-Han; Goodfellow, Paul J; Gilks, C. Blake; Huntsman, David G

2014-01-01

The classification of endometrial carcinomas is based on pathological assessment of tumour cell type; the different cell types (endometrioid, serous, carcinosarcoma, mixed, and clear cell) are associated with distinct molecular alterations. This current classification system for high-grade subtypes, in particular the distinction between high-grade endometrioid (EEC-3) and serous carcinomas (ESC), is limited in its reproducibility and prognostic abilities. Therefore, a search for specific molecular classifiers to improve endometrial carcinoma subclassification is warranted. We performed target enrichment sequencing on 393 endometrial carcinomas from two large cohorts, sequencing exons from the following 9 genes; ARID1A, PPP2R1A, PTEN, PIK3CA, KRAS, CTNNB1, TP53, BRAF and PPP2R5C. Based on this gene panel each endometrial carcinoma subtype shows a distinct mutation profile. EEC-3s have significantly different frequencies of PTEN and TP53 mutations when compared to low-grade endometrioid carcinomas. ESCs and EEC-3s are distinct subtypes with significantly different frequencies of mutations in PTEN, ARID1A, PPP2R1A, TP53, and CTNNB1. From the mutation profiles we were able to identify subtype outliers, i.e. cases diagnosed morphologically as one subtype but with a mutation profile suggestive of a different subtype. Careful review of these diagnostically challenging cases suggested that the original morphological classification was incorrect in most instances. The molecular profile of carcinosarcomas suggests two distinct mutation profiles for these tumours; endometrioid-type (PTEN, PIK3CA, ARID1A, KRAS mutations), and serous-type (TP53 and PPP2R1A mutations). While this nine gene panel does not allow for a purely molecularly based classification of endometrial carcinoma, it may prove useful as an adjunct to morphological classification and serve as an aid in the classification of problematic cases. If used in practice, it may lead to improved diagnostic reproducibility and may also serve to stratify patients for targeted therapeutics. PMID:22653804

Comprehensive Materials and Morphologies Study of Ion Traps (COMMIT) for Scalable Quantum Computation

DTIC Science & Technology

2012-04-21

the photoelectric effect. The typical shortest wavelengths needed for ion traps range from 194 nm for Hg+ to 493 nm for Ba +, corresponding to 6.4-2.5...REPORT Comprehensive Materials and Morphologies Study of Ion Traps (COMMIT) for scalable Quantum Computation - Final Report 14. ABSTRACT 16. SECURITY...CLASSIFICATION OF: Trapped ion systems, are extremely promising for large-scale quantum computation, but face a vexing problem, with motional quantum

Galaxy Zoo: Infrared and Optical Morphology

NASA Astrophysics Data System (ADS)

Carla Shanahan, Jesse; Lintott, Chris; Zoo, Galaxy

2018-01-01

We present the detailed, visual morphologies of approximately 60,000 galaxies observed by the UKIRT Infrared Deep Sky Survey and then classified by participants in the Galaxy Zoo project. Our sample is composed entirely of nearby objects with redshifts of z ≤ 0.3, which enables us to robustly analyze their morphological characteristics including smoothness, bulge properties, spiral structure, and evidence of bars or rings. The determination of these features is made via a consensus-based analysis of the Galaxy Zoo project data in which inconsistent and outlying classifications are statistically down-weighted. We then compare these classifications of infrared morphology to the objects’ optical classifications in the Galaxy Zoo 2 release (Willett et al. 2013). It is already known that morphology is an effective tool for uncovering a galaxy’s dynamical past, and previous studies have shown significant correlations with physical characteristics such as stellar mass distribution and star formation history. We show that majority of the sample has agreement or expected differences between the optical and infrared classifications, but also present a preliminary analysis of a subsample of objects with striking discrepancies.

Galaxy Zoo: Morphological Classification of Galaxy Images from the Illustris  Simulation

NASA Astrophysics Data System (ADS)

Dickinson, Hugh; Fortson, Lucy; Lintott, Chris; Scarlata, Claudia; Willett, Kyle; Bamford, Steven; Beck, Melanie; Cardamone, Carolin; Galloway, Melanie; Simmons, Brooke; Keel, William; Kruk, Sandor; Masters, Karen; Vogelsberger, Mark; Torrey, Paul; Snyder, Gregory F.

2018-02-01

Modern large-scale cosmological simulations model the universe with increasing sophistication and at higher spatial and temporal resolutions. These ongoing enhancements permit increasingly detailed comparisons between the simulation outputs and real observational data. Recent projects such as Illustris are capable of producing simulated images that are designed to be comparable to those obtained from local surveys. This paper tests the degree to which Illustris achieves this goal across a diverse population of galaxies using visual morphologies derived from Galaxy Zoo citizen scientists. Morphological classifications provided by these volunteers for simulated galaxies are compared with similar data for a compatible sample of images drawn from the Sloan Digital Sky Survey (SDSS) Legacy Survey. This paper investigates how simple morphological characterization by human volunteers asked to distinguish smooth from featured systems differs between simulated and real galaxy images. Significant differences are identified, which are most likely due to the limited resolution of the simulation, but which could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Specifically, for stellar masses {M}\\star ≲ {10}11 {M}ȯ , a substantially larger proportion of Illustris galaxies that exhibit disk-like morphology or visible substructure, relative to their SDSS counterparts. Toward higher masses, the visual morphologies for simulated and observed galaxies converge and exhibit similar distributions. The stellar mass threshold indicated by this divergent behavior confirms recent works using parametric measures of morphology from Illustris simulated images. When {M}\\star ≳ {10}11 {M}ȯ , the Illustris data set contains substantially fewer galaxies that classifiers regard as unambiguously featured. In combination, these results suggest that comparison between the detailed properties of observed and simulated galaxies, even when limited to reasonably massive systems, may be misleading.

New Features for Neuron Classification.

PubMed

Hernández-Pérez, Leonardo A; Delgado-Castillo, Duniel; Martín-Pérez, Rainer; Orozco-Morales, Rubén; Lorenzo-Ginori, Juan V

2018-04-28

This paper addresses the problem of obtaining new neuron features capable of improving results of neuron classification. Most studies on neuron classification using morphological features have been based on Euclidean geometry. Here three one-dimensional (1D) time series are derived from the three-dimensional (3D) structure of neuron instead, and afterwards a spatial time series is finally constructed from which the features are calculated. Digitally reconstructed neurons were separated into control and pathological sets, which are related to three categories of alterations caused by epilepsy, Alzheimer's disease (long and local projections), and ischemia. These neuron sets were then subjected to supervised classification and the results were compared considering three sets of features: morphological, features obtained from the time series and a combination of both. The best results were obtained using features from the time series, which outperformed the classification using only morphological features, showing higher correct classification rates with differences of 5.15, 3.75, 5.33% for epilepsy and Alzheimer's disease (long and local projections) respectively. The morphological features were better for the ischemia set with a difference of 3.05%. Features like variance, Spearman auto-correlation, partial auto-correlation, mutual information, local minima and maxima, all related to the time series, exhibited the best performance. Also we compared different evaluators, among which ReliefF was the best ranked.

Molecular phylogeny of tribe Rhipsalideae (Cactaceae) and taxonomic implications for Schlumbergera and Hatiora.

PubMed

Calvente, Alice; Zappi, Daniela C; Forest, Félix; Lohmann, Lúcia G

2011-03-01

Tribe Rhipsalideae is composed of unusual epiphytic or lithophytic cacti that inhabit humid tropical and subtropical forests. Members of this tribe present a reduced vegetative body, a specialized adventitious root system, usually spineless areoles and flowers and fruits reduced in size. Despite the debate surrounding the classification of Rhipsalideae, no studies have ever attempted to reconstruct phylogenetic relationships among its members or to test the monophyly of its genera using DNA sequence data; all classifications formerly proposed for this tribe have only employed morphological data. In this study, we reconstruct the phylogeny of Rhipsalideae using plastid (trnQ-rps16, rpl32-trnL, psbA-trnH) and nuclear (ITS) markers to evaluate the classifications previously proposed for the group. We also examine morphological features traditionally used to delimit genera within Rhipsalideae in light of the resulting phylogenetic trees. In total new sequences for 35 species of Rhipsalideae were produced (out of 55; 63%). The molecular phylogeny obtained comprises four main clades supporting the recognition of genera Lepismium, Rhipsalis, Hatiora and Schlumbergera. The evidence gathered indicate that a broader genus Schlumbergera, including Hatiora subg. Rhipsalidopsis, should be recognized. Consistent morphological characters rather than homoplastic features are used in order to establish a more coherent and practical classification for the group. Nomenclatural changes and a key for the identification of the genera currently included in Rhipsalideae are provided. Copyright © 2011 Elsevier Inc. All rights reserved.

[Neuroendocrine tumors of digestive system: morphologic spectrum and cell proliferation (Ki67 index)].

PubMed

Delektorskaia, V V; Kushliskiĭ, N E

2013-01-01

This review deals with the analysis of up-to-date concepts ofdiferent types of human neuroendocrine tumors of the digestive system. It summarizes the information on the specifics of recent histological classifications and criteria of morphological diagnosis accounting histological, ultrastructural and immunohistochemical parameters. Current issues of the nomenclature as well as various systems of grading and staging are discussed. In the light of these criteria the results of the own research clinical value of the determination of cell proliferation in primary and metastatic gastroenteropancreatic neuroendocrine neoplasms on the basis of evaluation of the Ki67 antigen expression are also presented.

Segmentation of white blood cells and comparison of cell morphology by linear and naïve Bayes classifiers.

PubMed

Prinyakupt, Jaroonrut; Pluempitiwiriyawej, Charnchai

2015-06-30

Blood smear microscopic images are routinely investigated by haematologists to diagnose most blood diseases. However, the task is quite tedious and time consuming. An automatic detection and classification of white blood cells within such images can accelerate the process tremendously. In this paper we propose a system to locate white blood cells within microscopic blood smear images, segment them into nucleus and cytoplasm regions, extract suitable features and finally, classify them into five types: basophil, eosinophil, neutrophil, lymphocyte and monocyte. Two sets of blood smear images were used in this study's experiments. Dataset 1, collected from Rangsit University, were normal peripheral blood slides under light microscope with 100× magnification; 555 images with 601 white blood cells were captured by a Nikon DS-Fi2 high-definition color camera and saved in JPG format of size 960 × 1,280 pixels at 15 pixels per 1 μm resolution. In dataset 2, 477 cropped white blood cell images were downloaded from CellaVision.com. They are in JPG format of size 360 × 363 pixels. The resolution is estimated to be 10 pixels per 1 μm. The proposed system comprises a pre-processing step, nucleus segmentation, cell segmentation, feature extraction, feature selection and classification. The main concept of the segmentation algorithm employed uses white blood cell's morphological properties and the calibrated size of a real cell relative to image resolution. The segmentation process combined thresholding, morphological operation and ellipse curve fitting. Consequently, several features were extracted from the segmented nucleus and cytoplasm regions. Prominent features were then chosen by a greedy search algorithm called sequential forward selection. Finally, with a set of selected prominent features, both linear and naïve Bayes classifiers were applied for performance comparison. This system was tested on normal peripheral blood smear slide images from two datasets. Two sets of comparison were performed: segmentation and classification. The automatically segmented results were compared to the ones obtained manually by a haematologist. It was found that the proposed method is consistent and coherent in both datasets, with dice similarity of 98.9 and 91.6% for average segmented nucleus and cell regions, respectively. Furthermore, the overall correction rate in the classification phase is about 98 and 94% for linear and naïve Bayes models, respectively. The proposed system, based on normal white blood cell morphology and its characteristics, was applied to two different datasets. The results of the calibrated segmentation process on both datasets are fast, robust, efficient and coherent. Meanwhile, the classification of normal white blood cells into five types shows high sensitivity in both linear and naïve Bayes models, with slightly better results in the linear classifier.

[CT morphometry for calcaneal fractures and comparison of the Zwipp and Sanders classifications].

PubMed

Andermahr, J; Jesch, A B; Helling, H J; Jubel, A; Fischbach, R; Rehm, K E

2002-01-01

The aim of the study is to correlate the CT-morphological changes of fractured calcaneus and the classifications of Zwipp and Sanders with the clinical outcome. In a retrospective clinical study, the preoperative CT scans of 75 calcaneal fractures were analysed. The morphometry of the fractures was determined by measuring height, length diameter and calcaneo-cuboidal angle in comparison to the intact contralateral side. At a mean of 38 months after trauma 44 patients were clinically followed-up. The data of CT image morphometry were correlated with the severity of fracture classified by Zwipp or Sanders as well as with the functional outcome. There was a good correlation between the fracture classifications and the morphometric data. Both fracture classifying systems have a predictive impact for functional outcome. The more exacting and accurate Zwipp classification considers the most important cofactors like involvement of the calcaneo-cuboidal joint, soft tissue damage, additional fractures etc. The Sanders classification is easier to use during clinical routine. The Zwipp classification includes more relevant cofactors (fracture of the calcaneo-cuboidal-joint, soft tissue swelling, etc.) and presents a higher correlation to the choice of therapy. Both classification systems present a prognostic impact concerning the clinical outcome.

Reliability analysis of the AOSpine thoracolumbar spine injury classification system by a worldwide group of naïve spinal surgeons.

PubMed

Kepler, Christopher K; Vaccaro, Alexander R; Koerner, John D; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, Shanmuganathan; Aarabi, Bizhan; Vialle, Luiz R; Fehlings, Michael G; Schroeder, Gregory D; Reinhold, Maximilian; Schnake, Klaus John; Bellabarba, Carlo; Cumhur Öner, F

2016-04-01

The aims of this study were (1) to demonstrate the AOSpine thoracolumbar spine injury classification system can be reliably applied by an international group of surgeons and (2) to delineate those injury types which are difficult for spine surgeons to classify reliably. A previously described classification system of thoracolumbar injuries which consists of a morphologic classification of the fracture, a grading system for the neurologic status and relevant patient-specific modifiers was applied to 25 cases by 100 spinal surgeons from across the world twice independently, in grading sessions 1 month apart. The results were analyzed for classification reliability using the Kappa coefficient (κ). The overall Kappa coefficient for all cases was 0.56, which represents moderate reliability. Kappa values describing interobserver agreement were 0.80 for type A injuries, 0.68 for type B injuries and 0.72 for type C injuries, all representing substantial reliability. The lowest level of agreement for specific subtypes was for fracture subtype A4 (Kappa = 0.19). Intraobserver analysis demonstrated overall average Kappa statistic for subtype grading of 0.68 also representing substantial reproducibility. In a worldwide sample of spinal surgeons without previous exposure to the recently described AOSpine Thoracolumbar Spine Injury Classification System, we demonstrated moderate interobserver and substantial intraobserver reliability. These results suggest that most spine surgeons can reliably apply this system to spine trauma patients as or more reliably than previously described systems.

Morphology classification of galaxies in CL 0939+4713 using a ground-based telescope image

NASA Technical Reports Server (NTRS)

Fukugita, M.; Doi, M.; Dressler, A.; Gunn, J. E.

1995-01-01

Morphological classification is studied for galaxies in cluster CL 0939+4712 at z = 0.407 using simple photometric parameters obtained from a ground-based telescope image with seeing of 1-2 arcseconds full width at half maximim (FWHM). By ploting the galaxies in a plane of the concentration parameter versus mean surface brightness, we find a good correlation between the location on the plane and galaxy colors, which are known to correlate with morphological types from a recent Hubble Space Telescope (HST) study. Using the present method, we expect a success rate of classification into early and late types of about 70% or possibly more.

Increasing CAD system efficacy for lung texture analysis using a convolutional network

NASA Astrophysics Data System (ADS)

Tarando, Sebastian Roberto; Fetita, Catalin; Faccinetto, Alex; Brillet, Pierre-Yves

2016-03-01

The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. For the large majority of CAD systems, such classification relies on a two-dimensional analysis of axial CT images. In a previously developed CAD system, we proposed a fully-3D approach exploiting a multi-scale morphological analysis which showed good performance in detecting diseased areas, but with a major drawback consisting of sometimes overestimating the pathological areas and mixing different type of lung patterns. This paper proposes a combination of the existing CAD system with the classification outcome provided by a convolutional network, specifically tuned-up, in order to increase the specificity of the classification and the confidence to diagnosis. The advantage of using a deep learning approach is a better regularization of the classification output (because of a deeper insight into a given pathological class over a large series of samples) where the previous system is extra-sensitive due to the multi-scale response on patient-specific, localized patterns. In a preliminary evaluation, the combined approach was tested on a 10 patient database of various lung pathologies, showing a sharp increase of true detections.

Developing and Integrating Advanced Movement Features Improves Automated Classification of Ciliate Species

PubMed Central

Soleymani, Ali; Pennekamp, Frank; Petchey, Owen L.; Weibel, Robert

2015-01-01

Recent advances in tracking technologies such as GPS or video tracking systems describe the movement paths of individuals in unprecedented details and are increasingly used in different fields, including ecology. However, extracting information from raw movement data requires advanced analysis techniques, for instance to infer behaviors expressed during a certain period of the recorded trajectory, or gender or species identity in case data is obtained from remote tracking. In this paper, we address how different movement features affect the ability to automatically classify the species identity, using a dataset of unicellular microbes (i.e., ciliates). Previously, morphological attributes and simple movement metrics, such as speed, were used for classifying ciliate species. Here, we demonstrate that adding advanced movement features, in particular such based on discrete wavelet transform, to morphological features can improve classification. These results may have practical applications in automated monitoring of waste water facilities as well as environmental monitoring of aquatic systems. PMID:26680591

Hip health at skeletal maturity: a population-based study of young adults with cerebral palsy.

PubMed

Wawrzuta, Joanna; Willoughby, Kate L; Molesworth, Charlotte; Ang, Soon Ghee; Shore, Benjamin J; Thomason, Pam; Graham, H Kerr

2016-12-01

We studied 'hip health' in a population-based cohort of adolescents and young adults with cerebral palsy to investigate associations between hip morphology, pain, and gross motor function. Ninety-eight young adults (65 males, 33 females) from the birth cohort were identified as having developed hip displacement (migration percentage >30) and were reviewed at a mean age of 18 years 10 months (range 15-24y). Hip morphology was classified using the Melbourne Cerebral Palsy Hip Classification Scale (MCPHCS). Severity and frequency of pain were recorded using Likert scales. Gross motor function was classified by the Gross Motor Function Classification System (GMFCS). Hip pain was reported in 72% of participants. Associations were found between pain scores and both hip morphology and GMFCS. Median pain severity score for MCPHCS grades 1 to 4 was 2 (interquartile range [IQR] 1.0-3.0) compared to 7 (IQR 6.0-8.0) for grades 5 and 6 (severe subluxation or dislocation). Hip surveillance and access to surgery were associated with improved hip morphology and less pain. Poor hip morphology at skeletal maturity was associated with high levels of pain. Limited hip surveillance and access to surgery, rather than GMFCS, was associated with poor hip morphology. The majority of young adults who had access to hip surveillance, and preventive and reconstructive surgery, had satisfactory hip morphology at skeletal maturity and less pain. © 2016 Mac Keith Press.

The First AO Classification System for Fractures of the Craniomaxillofacial Skeleton: Rationale, Methodological Background, Developmental Process, and Objectives

PubMed Central

Audigé, Laurent; Cornelius, Carl-Peter; Ieva, Antonio Di; Prein, Joachim

2014-01-01

Validated trauma classification systems are the sole means to provide the basis for reliable documentation and evaluation of patient care, which will open the gateway to evidence-based procedures and healthcare in the coming years. With the support of AO Investigation and Documentation, a classification group was established to develop and evaluate a comprehensive classification system for craniomaxillofacial (CMF) fractures. Blueprints for fracture classification in the major constituents of the human skull were drafted and then evaluated by a multispecialty group of experienced CMF surgeons and a radiologist in a structured process during iterative agreement sessions. At each session, surgeons independently classified the radiological imaging of up to 150 consecutive cases with CMF fractures. During subsequent review meetings, all discrepancies in the classification outcome were critically appraised for clarification and improvement until consensus was reached. The resulting CMF classification system is structured in a hierarchical fashion with three levels of increasing complexity. The most elementary level 1 simply distinguishes four fracture locations within the skull: mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). Levels 2 and 3 focus on further defining the fracture locations and for fracture morphology, achieving an almost individual mapping of the fracture pattern. This introductory article describes the rationale for the comprehensive AO CMF classification system, discusses the methodological framework, and provides insight into the experiences and interactions during the evaluation process within the core groups. The details of this system in terms of anatomy and levels are presented in a series of focused tutorials illustrated with case examples in this special issue of the Journal. PMID:25489387

The First AO Classification System for Fractures of the Craniomaxillofacial Skeleton: Rationale, Methodological Background, Developmental Process, and Objectives.

PubMed

Audigé, Laurent; Cornelius, Carl-Peter; Di Ieva, Antonio; Prein, Joachim

2014-12-01

Validated trauma classification systems are the sole means to provide the basis for reliable documentation and evaluation of patient care, which will open the gateway to evidence-based procedures and healthcare in the coming years. With the support of AO Investigation and Documentation, a classification group was established to develop and evaluate a comprehensive classification system for craniomaxillofacial (CMF) fractures. Blueprints for fracture classification in the major constituents of the human skull were drafted and then evaluated by a multispecialty group of experienced CMF surgeons and a radiologist in a structured process during iterative agreement sessions. At each session, surgeons independently classified the radiological imaging of up to 150 consecutive cases with CMF fractures. During subsequent review meetings, all discrepancies in the classification outcome were critically appraised for clarification and improvement until consensus was reached. The resulting CMF classification system is structured in a hierarchical fashion with three levels of increasing complexity. The most elementary level 1 simply distinguishes four fracture locations within the skull: mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). Levels 2 and 3 focus on further defining the fracture locations and for fracture morphology, achieving an almost individual mapping of the fracture pattern. This introductory article describes the rationale for the comprehensive AO CMF classification system, discusses the methodological framework, and provides insight into the experiences and interactions during the evaluation process within the core groups. The details of this system in terms of anatomy and levels are presented in a series of focused tutorials illustrated with case examples in this special issue of the Journal.

Morphology Is a Link to the Past: Examining Formative and Secular Galactic Evolution through Morphology

NASA Astrophysics Data System (ADS)

Galloway, Melanie A.

Galaxy morphology is one of the primary keys to understanding a galaxy's evolutionary history. External mechanisms (environment/clustering, mergers) have a strong impact on the formative evolution of the major galactic components (disk, bulge, Hubble type), while internal instabilities created by bars, spiral arms, or other substructures drive secular evolution via the rearrangement of material within the disk. This thesis will explore several ways in which morphology impacts the dynamics and evolution of a galaxy using visual classifications from several Galaxy Zoo projects. The first half of this work will detail the motivations of using morphology to study galaxy evolution, and describe how morphology is measured, debiased, and interpreted using crowdsourced classification data via Galaxy Zoo. The second half will present scientific studies which make use of these classifications; first by focusing on the morphology of galaxies in the local Universe (z < 0.2) using data from Galaxy Zoo 2 and Galaxy Zoo UKIDSS. Last, the high-redshift Universe will be explored by examining populations of morphologies at various lookback times, from z = 0 out to z = 1 using data from Galaxy Zoo Hubble. The investigation of the physical implications of morphology in the local Universe will first be presented in Chapter 4, in a study of the impact of bars on the fueling of an active galactic nucleus (AGN). Using a sample of 19,756 disk galaxies at 0.01 < z < 0.05 imaged by the Sloan Digital Sky Survey and morphologically classified by Galaxy Zoo 2 (GZ2), the difference in AGN fraction in barred and unbarred disks was measured. A weak, but statistically significant, effect was found in that the population of AGN hosts exhibited a 16.0% increase in bar fraction as compared to their unbarred counterparts at fixed mass and color. These results are consistent with a cosmological model in which bar-driven fueling contributes to the growth of black holes, but other dynamical mechanisms must also play a significant role. Next, the morphological dependence on wavelength is studied in Chapter 5 by comparing the optical morphological classifications from GZ2 to classifications done on infrared images in GZ:UKIDSS. Consistent morphologies were found in both sets and similar bar fractions, which confirms that for most galaxies, both old and young stellar populations follow similar spatial distributions. Last, the morphological changes in galaxy populations are computed as a function of their age using classifications from Galaxy Zoo: Hubble (Chapter 6). The evolution of the passive disc population from z = 1 to z = 0.3 was studied in a sample of 20,000 galaxies from the COSMOS field and morphologically classified by the Galaxy Zoo: Hubble project. It was found that the fraction of disc galaxies that are red, as well as the fraction of red sequence galaxies that are discs, decreases for the most massive galaxies (log(M/M solar masses) > 11) but increases for lower masses. The observations are consistent with a physical scenario in which more massive galaxies are more likely to enter a red disc phase, and more massive red discs are more likely to morphologically transform into ellipticals than their less massive counterparts. Additionally, the challenges of visual classification that are particular to galaxies at high redshift were investigated. To address these biases, a new correction technique is presented using simulated images of nearby SDSS galaxies which were artificially redshifted using the FERENGI code and classified in GZH.

Confirmation of Two Undescribed Fungal Species from Dokdo of Korea Based on Current Classification System Using Multi Loci

PubMed Central

Lee, Hye Won; Nguyen, Thi Thuong Thuong; Mun, Hye Yeon; Lee, Haengsub; Kim, Changmu

2015-01-01

Using dilution plating method, 47 fungal isolates were obtained from a soil sample collected from Dokdo in the East Sea of Korea in 2013. In this study, two fungal isolates, EML-MFS30-1 and EML-DDSF4, were confirmed as undescribed species, Metarhizium guizhouense and Mortierella oligospora in Korea based on current classification system using multi loci including rDNA internal transcribed spacer, large subunit, small subunit, and β-tubulin (BTUB) genes. Herein, detailed morphological descriptions on characters of the undescribed fungal species as well as their molecular phylogenetic status are provided with comparisons to related species. PMID:26839498

Neural network classification of sweet potato embryos

NASA Astrophysics Data System (ADS)

Molto, Enrique; Harrell, Roy C.

1993-05-01

Somatic embryogenesis is a process that allows for the in vitro propagation of thousands of plants in sub-liter size vessels and has been successfully applied to many significant species. The heterogeneity of maturity and quality of embryos produced with this technique requires sorting to obtain a uniform product. An automated harvester is being developed at the University of Florida to sort embryos in vitro at different stages of maturation in a suspension culture. The system utilizes machine vision to characterize embryo morphology and a fluidic based separation device to isolate embryos associated with a pre-defined, targeted morphology. Two different backpropagation neural networks (BNN) were used to classify embryos based on information extracted from the vision system. One network utilized geometric features such as embryo area, length, and symmetry as inputs. The alternative network utilized polar coordinates of an embryo's perimeter with respect to its centroid as inputs. The performances of both techniques were compared with each other and with an embryo classification method based on linear discriminant analysis (LDA). Similar results were obtained with all three techniques. Classification efficiency was improved by reducing the dimension of the feature vector trough a forward stepwise analysis by LDA. In order to enhance the purity of the sample selected as harvestable, a reject to classify option was introduced in the model and analyzed. The best classifier performances (76% overall correct classifications, 75% harvestable objects properly classified, homogeneity improvement ratio 1.5) were obtained using 8 features in a BNN.

THE CLASSIFICATION OF SERBO-CROATIAN DIALECTS.

ERIC Educational Resources Information Center

NAYLOR, KENNETH E.

THE CAKAVIAN GROUP OF SERBO-CROATIAN DIALECTS CAN BE RECLASSIFIED USING SYNCHRONIC CRITERIA RATHER THAN TRADITIONALLY USED DIACHRONIC CRITERIA. THE APPROACH IS TYPOLOGICAL RATHER THAN GENETIC AND COMPARES THE NOMINAL MORPHOLOGICAL AND MORPHOPHONEMIC SYSTEMS OF SEVEN DIALECTS SELECTED TO PROVIDE A GEOGRAPHICAL SAMPLING OF THE CAKAVIAN GROUP.…

Urothelial dysplasia and other flat lesions of the urinary bladder: clinicopathologic and molecular features.

PubMed

Hodges, Kurt B; Lopez-Beltran, Antonio; Davidson, Darrell D; Montironi, Rodolfo; Cheng, Liang

2010-02-01

The 2004 World Health Organization classification system for urothelial neoplasia classifies flat-related preneoplastic lesions as urothelial hyperplasia (flat and papillary), reactive urothelial atypia, urothelial atypia of unknown significance, urothelial dysplasia (low-grade intraurothelial neoplasia), and urothelial carcinoma in situ (high-grade intraurothelial neoplasia). Each lesion is defined with precise nomenclature and strict morphologic criteria. In many cases, morphologic features alone suffice for diagnosis. Other cases may require a panel of immunohistochemical antibodies consisting of cytokeratin 20, p53, and CD44 for diagnosis. Recent molecular studies have provided further insight into the premalignant potential of these urothelial lesions. Herein, we present a review of flat urothelial lesions of the urinary bladder as defined by the 2004 World Health Organization classification with focus on the clinicopathologic, immunohistochemical, and molecular features. Copyright 2010 Elsevier Inc. All rights reserved.

The Comprehensive AOCMF Classification: Skull Base and Cranial Vault Fractures – Level 2 and 3 Tutorial

PubMed Central

Ieva, Antonio Di; Audigé, Laurent; Kellman, Robert M.; Shumrick, Kevin A.; Ringl, Helmut; Prein, Joachim; Matula, Christian

2014-01-01

The AOCMF Classification Group developed a hierarchical three-level craniomaxillofacial classification system with increasing level of complexity and details. The highest level 1 system distinguish four major anatomical units, including the mandible (code 91), midface (code 92), skull base (code 93), and cranial vault (code 94). This tutorial presents the level 2 and more detailed level 3 systems for the skull base and cranial vault units. The level 2 system describes fracture location outlining the topographic boundaries of the anatomic regions, considering in particular the endocranial and exocranial skull base surfaces. The endocranial skull base is divided into nine regions; a central skull base adjoining a left and right side are divided into the anterior, middle, and posterior skull base. The exocranial skull base surface and cranial vault are divided in regions defined by the names of the bones involved: frontal, parietal, temporal, sphenoid, and occipital bones. The level 3 system allows assessing fracture morphology described by the presence of fracture fragmentation, displacement, and bone loss. A documentation of associated intracranial diagnostic features is proposed. This tutorial is organized in a sequence of sections dealing with the description of the classification system with illustrations of the topographical skull base and cranial vault regions along with rules for fracture location and coding, a series of case examples with clinical imaging and a general discussion on the design of this classification. PMID:25489394

Geophysical phenomena classification by artificial neural networks

NASA Technical Reports Server (NTRS)

Gough, M. P.; Bruckner, J. R.

1995-01-01

Space science information systems involve accessing vast data bases. There is a need for an automatic process by which properties of the whole data set can be assimilated and presented to the user. Where data are in the form of spectrograms, phenomena can be detected by pattern recognition techniques. Presented are the first results obtained by applying unsupervised Artificial Neural Networks (ANN's) to the classification of magnetospheric wave spectra. The networks used here were a simple unsupervised Hamming network run on a PC and a more sophisticated CALM network run on a Sparc workstation. The ANN's were compared in their geophysical data recognition performance. CALM networks offer such qualities as fast learning, superiority in generalizing, the ability to continuously adapt to changes in the pattern set, and the possibility to modularize the network to allow the inter-relation between phenomena and data sets. This work is the first step toward an information system interface being developed at Sussex, the Whole Information System Expert (WISE). Phenomena in the data are automatically identified and provided to the user in the form of a data occurrence morphology, the Whole Information System Data Occurrence Morphology (WISDOM), along with relationships to other parameters and phenomena.

An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

NASA Astrophysics Data System (ADS)

Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

2017-07-01

Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

Pāhoehoe, `a`ā, and block lava: an illustrated history of the nomenclature

NASA Astrophysics Data System (ADS)

Harris, Andrew J. L.; Rowland, Scott K.; Villeneuve, Nicolas; Thordarson, Thor

2017-01-01

Lava flows occur worldwide, and throughout history, various cultures (and geologists) have described flows based on their surface textures. As a result, surface morphology-based nomenclature schemes have been proposed in most languages to aid in the classification and distinction of lava surface types. One of the first to be published was likely the nine-class, Italian-language description-based classification proposed by Mario Gemmellaro in 1858. By far, the most commonly used terms to describe lava surfaces today are not descriptive but, instead, are merely words, specifically the Hawaiian words `a`ā (rough brecciated basalt lava) and pāhoehoe (smooth glassy basalt lava), plus block lava (thick brecciated lavas that are typically more silicic than basalt). `A`ā and pāhoehoe were introduced into the Western geological vocabulary by American geologists working in Hawai`i during the 1800s. They and other nineteenth century geologists proposed formal lava-type classification schemes for scientific use, and most of them used the Hawaiian words. In 1933, Ruy Finch added the third lava type, block lava, to the classification scheme, with the tripartite system being formalized in 1953 by Gordon Macdonald. More recently, particularly since the 1980s and based largely on studies of lava flow interiors, a number of sub-types and transitional forms of all three major lava types have been defined. This paper reviews the early history of the development of the pāhoehoe, `a`ā, and block lava-naming system and presents a new descriptive classification so as to break out the three parental lava types into their many morphological sub-types.

Validation of the Lung Subtyping Panel in Multiple Fresh-Frozen and Formalin-Fixed, Paraffin-Embedded Lung Tumor Gene Expression Data Sets.

PubMed

Faruki, Hawazin; Mayhew, Gregory M; Fan, Cheng; Wilkerson, Matthew D; Parker, Scott; Kam-Morgan, Lauren; Eisenberg, Marcia; Horten, Bruce; Hayes, D Neil; Perou, Charles M; Lai-Goldman, Myla

2016-06-01

Context .- A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective .- To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design .- The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription-polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results .- The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions .- The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Use of mutation profiles to refine the classification of endometrial carcinomas.

PubMed

McConechy, Melissa K; Ding, Jiarui; Cheang, Maggie Cu; Wiegand, Kimberly; Senz, Janine; Tone, Alicia; Yang, Winnie; Prentice, Leah; Tse, Kane; Zeng, Thomas; McDonald, Helen; Schmidt, Amy P; Mutch, David G; McAlpine, Jessica N; Hirst, Martin; Shah, Sohrab P; Lee, Cheng-Han; Goodfellow, Paul J; Gilks, C Blake; Huntsman, David G

2012-09-01

The classification of endometrial carcinomas is based on pathological assessment of tumour cell type; the different cell types (endometrioid, serous, carcinosarcoma, mixed, undifferentiated, and clear cell) are associated with distinct molecular alterations. This current classification system for high-grade subtypes, in particular the distinction between high-grade endometrioid (EEC-3) and serous carcinomas (ESC), is limited in its reproducibility and prognostic abilities. Therefore, a search for specific molecular classifiers to improve endometrial carcinoma subclassification is warranted. We performed target enrichment sequencing on 393 endometrial carcinomas from two large cohorts, sequencing exons from the following nine genes: ARID1A, PPP2R1A, PTEN, PIK3CA, KRAS, CTNNB1, TP53, BRAF, and PPP2R5C. Based on this gene panel, each endometrial carcinoma subtype shows a distinct mutation profile. EEC-3s have significantly different frequencies of PTEN and TP53 mutations when compared to low-grade endometrioid carcinomas. ESCs and EEC-3s are distinct subtypes with significantly different frequencies of mutations in PTEN, ARID1A, PPP2R1A, TP53, and CTNNB1. From the mutation profiles, we were able to identify subtype outliers, ie cases diagnosed morphologically as one subtype but with a mutation profile suggestive of a different subtype. Careful review of these diagnostically challenging cases suggested that the original morphological classification was incorrect in most instances. The molecular profile of carcinosarcomas suggests two distinct mutation profiles for these tumours: endometrioid-type (PTEN, PIK3CA, ARID1A, KRAS mutations) and serous-type (TP53 and PPP2R1A mutations). While this nine-gene panel does not allow for a purely molecularly based classification of endometrial carcinoma, it may prove useful as an adjunct to morphological classification and serve as an aid in the classification of problematic cases. If used in practice, it may lead to improved diagnostic reproducibility and may also serve to stratify patients for targeted therapeutics. Copyright © 2012 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Morphological variation, taxonomic distribution, and phylogenetic significance of cornuti in Tortricinae (Lepidoptera: Tortricidae)

USDA-ARS?s Scientific Manuscript database

Based on the examination of 4,218 slide-mounted preparations of male and female genitalia of tortricine moths, representing all major clades of the subfamily worldwide, we propose a classification system for cornuti based on four criteria: (1) presence/absence; (2) deciduous/non-deciduous; (3) type ...

Gold-standard for computer-assisted morphological sperm analysis.

PubMed

Chang, Violeta; Garcia, Alejandra; Hitschfeld, Nancy; Härtel, Steffen

2017-04-01

Published algorithms for classification of human sperm heads are based on relatively small image databases that are not open to the public, and thus no direct comparison is available for competing methods. We describe a gold-standard for morphological sperm analysis (SCIAN-MorphoSpermGS), a dataset of sperm head images with expert-classification labels in one of the following classes: normal, tapered, pyriform, small or amorphous. This gold-standard is for evaluating and comparing known techniques and future improvements to present approaches for classification of human sperm heads for semen analysis. Although this paper does not provide a computational tool for morphological sperm analysis, we present a set of experiments for comparing sperm head description and classification common techniques. This classification base-line is aimed to be used as a reference for future improvements to present approaches for human sperm head classification. The gold-standard provides a label for each sperm head, which is achieved by majority voting among experts. The classification base-line compares four supervised learning methods (1- Nearest Neighbor, naive Bayes, decision trees and Support Vector Machine (SVM)) and three shape-based descriptors (Hu moments, Zernike moments and Fourier descriptors), reporting the accuracy and the true positive rate for each experiment. We used Fleiss' Kappa Coefficient to evaluate the inter-expert agreement and Fisher's exact test for inter-expert variability and statistical significant differences between descriptors and learning techniques. Our results confirm the high degree of inter-expert variability in the morphological sperm analysis. Regarding the classification base line, we show that none of the standard descriptors or classification approaches is best suitable for tackling the problem of sperm head classification. We discovered that the correct classification rate was highly variable when trying to discriminate among non-normal sperm heads. By using the Fourier descriptor and SVM, we achieved the best mean correct classification: only 49%. We conclude that the SCIAN-MorphoSpermGS will provide a standard tool for evaluation of characterization and classification approaches for human sperm heads. Indeed, there is a clear need for a specific shape-based descriptor for human sperm heads and a specific classification approach to tackle the problem of high variability within subcategories of abnormal sperm cells. Copyright © 2017 Elsevier Ltd. All rights reserved.

On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

NASA Astrophysics Data System (ADS)

Gao, Liang; Li, Fuhai; Thrall, Michael J.; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A.; Zhao, Hong; Massoud, Yehia; Cagle, Philip T.; Fan, Yubo; Wong, Kelvin K.; Wang, Zhiyong; Wong, Stephen T. C.

2011-09-01

We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

Topobathymetric LiDAR point cloud processing and landform classification in a tidal environment

NASA Astrophysics Data System (ADS)

Skovgaard Andersen, Mikkel; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Brandbyge Ernstsen, Verner

2017-04-01

Historically it has been difficult to create high resolution Digital Elevation Models (DEMs) in land-water transition zones due to shallow water depth and often challenging environmental conditions. This gap of information has been reflected as a "white ribbon" with no data in the land-water transition zone. In recent years, the technology of airborne topobathymetric Light Detection and Ranging (LiDAR) has proven capable of filling out the gap by simultaneously capturing topographic and bathymetric elevation information, using only a single green laser. We collected green LiDAR point cloud data in the Knudedyb tidal inlet system in the Danish Wadden Sea in spring 2014. Creating a DEM from a point cloud requires the general processing steps of data filtering, water surface detection and refraction correction. However, there is no transparent and reproducible method for processing green LiDAR data into a DEM, specifically regarding the procedure of water surface detection and modelling. We developed a step-by-step procedure for creating a DEM from raw green LiDAR point cloud data, including a procedure for making a Digital Water Surface Model (DWSM) (see Andersen et al., 2017). Two different classification analyses were applied to the high resolution DEM: A geomorphometric and a morphological classification, respectively. The classification methods were originally developed for a small test area; but in this work, we have used the classification methods to classify the complete Knudedyb tidal inlet system. References Andersen MS, Gergely Á, Al-Hamdani Z, Steinbacher F, Larsen LR, Ernstsen VB (2017). Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment. Hydrol. Earth Syst. Sci., 21: 43-63, doi:10.5194/hess-21-43-2017. Acknowledgements This work was funded by the Danish Council for Independent Research | Natural Sciences through the project "Process-based understanding and prediction of morphodynamics in a natural coastal system in response to climate change" (Steno Grant no. 10-081102) and by the Geocenter Denmark through the project "Closing the gap! - Coherent land-water environmental mapping (LAWA)" (Grant no. 4-2015).

Classifying Physical Morphology of Cocoa Beans Digital Images using Multiclass Ensemble Least-Squares Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Adhitya, Yudhi

2018-03-01

The objective of this research is to determine the quality of cocoa beans through morphology of their digital images. Samples of cocoa beans were scattered on a bright white paper under a controlled lighting condition. A compact digital camera was used to capture the images. The images were then processed to extract their morphological parameters. Classification process begins with an analysis of cocoa beans image based on morphological feature extraction. Parameters for extraction of morphological or physical feature parameters, i.e., Area, Perimeter, Major Axis Length, Minor Axis Length, Aspect Ratio, Circularity, Roundness, Ferret Diameter. The cocoa beans are classified into 4 groups, i.e.: Normal Beans, Broken Beans, Fractured Beans, and Skin Damaged Beans. The model of classification used in this paper is the Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM), a proposed improvement model of SVM using ensemble method in which the separate hyperplanes are obtained by least square approach and the multiclass procedure uses One-Against- All method. The result of our proposed model showed that the classification with morphological feature input parameters were accurately as 99.705% for the four classes, respectively.

Automated Classification of Pathology Reports.

PubMed

Oleynik, Michel; Finger, Marcelo; Patrão, Diogo F C

2015-01-01

This work develops an automated classifier of pathology reports which infers the topography and the morphology classes of a tumor using codes from the International Classification of Diseases for Oncology (ICD-O). Data from 94,980 patients of the A.C. Camargo Cancer Center was used for training and validation of Naive Bayes classifiers, evaluated by the F1-score. Measures greater than 74% in the topographic group and 61% in the morphologic group are reported. Our work provides a successful baseline for future research for the classification of medical documents written in Portuguese and in other domains.

Importance of recurrence rating, morphology, hernial gap size, and risk factors in ventral and incisional hernia classification.

PubMed

Dietz, U A; Winkler, M S; Härtel, R W; Fleischhacker, A; Wiegering, A; Isbert, C; Jurowich, Ch; Heuschmann, P; Germer, C-T

2014-02-01

There is limited evidence on the natural course of ventral and incisional hernias and the results of hernia repair, what might partially be explained by the lack of an accepted classification system. The aim of the present study is to investigate the association of the criteria included in the Wuerzburg classification system of ventral and incisional hernias with postoperative complications and long-term recurrence. In a retrospective cohort study, the data on 330 consecutive patients who underwent surgery to repair ventral and incisional hernias were analyzed. The following four classification criteria were applied: (a) recurrence rating (ventral, incisional or incisional recurrent); (b) morphology (location); (c) size of the hernial gap; and (d) risk factors. The primary endpoint was the occurrence of a recurrence during follow-up. Secondary endpoints were incidence of postoperative complications. Independent association between classification criteria, type of surgical procedures and postoperative complications was calculated by multivariate logistic regression analysis and between classification criteria, type of surgical procedures and risk of long-term recurrence by Cox regression analysis. Follow-up lasted a mean 47.7 ± 23.53 months (median 45 months) or 3.9 ± 1.96 years. The criterion "recurrence rating" was found as predictive factor for postoperative complications in the multivariate analysis (OR 2.04; 95 % CI 1.09-3.84; incisional vs. ventral hernia). The criterion "morphology" had influence neither on the incidence of the critical event "recurrence during follow-up" nor on the incidence of postoperative complications. Hernial gap "width" predicted postoperative complications in the multivariate analysis (OR 1.98; 95 % CI 1.19-3.29; ≤5 vs. >5 cm). Length of the hernial gap was found to be an independent prognostic factor for the critical event "recurrence during follow-up" (HR 2.05; 95 % CI 1.25-3.37; ≤5 vs. >5 cm). The presence of 3 or more risk factors was a consistent predictor for "recurrence during follow-up" (HR 2.25; 95 % CI 1.28-9.92). Mesh repair was an independent protective factor for "recurrence during follow-up" compared to suture (HR 0.53; 95 % CI 0.32-0.86). The ventral and incisional hernia classification of Dietz et al. employs a clinically proven terminology and has an open classification structure. Hernial gap size and the number of risk factors are independent predictors for "recurrence during follow-up", whereas recurrence rating and hernial gap size correlated significantly with the incidence of postoperative complications. We propose the application of these criteria for future clinical research, as larger patient numbers will be needed to refine the results.

Voice classification and vocal tract of singers: a study of x-ray images and morphology.

PubMed

Roers, Friederike; Mürbe, Dirk; Sundberg, Johan

2009-01-01

This investigation compares vocal tract dimensions and the classification of singer voices by examining an x-ray material assembled between 1959 and 1991 of students admitted to the solo singing education at the University of Music, Dresden, Germany. A total of 132 images were available to analysis. Different classifications' values of the lengths of the total vocal tract, the pharynx, and mouth cavities as well as of the relative position of the larynx, the height of the palatal arch, and the estimated vocal fold length were analyzed statistically, and some significant differences were found. The length of the pharynx cavity seemed particularly influential on the total vocal tract length, which varied systematically with classification. Also studied were the relationships between voice classification and the body height and weight and the body mass index. The data support the hypothesis that there are consistent morphological vocal tract differences between singers of different voice classifications.

Pollen Bearing Honey Bee Detection in Hive Entrance Video Recorded by Remote Embedded System for Pollination Monitoring

NASA Astrophysics Data System (ADS)

Babic, Z.; Pilipovic, R.; Risojevic, V.; Mirjanic, G.

2016-06-01

Honey bees have crucial role in pollination across the world. This paper presents a simple, non-invasive, system for pollen bearing honey bee detection in surveillance video obtained at the entrance of a hive. The proposed system can be used as a part of a more complex system for tracking and counting of honey bees with remote pollination monitoring as a final goal. The proposed method is executed in real time on embedded systems co-located with a hive. Background subtraction, color segmentation and morphology methods are used for segmentation of honey bees. Classification in two classes, pollen bearing honey bees and honey bees that do not have pollen load, is performed using nearest mean classifier, with a simple descriptor consisting of color variance and eccentricity features. On in-house data set we achieved correct classification rate of 88.7% with 50 training images per class. We show that the obtained classification results are not far behind from the results of state-of-the-art image classification methods. That favors the proposed method, particularly having in mind that real time video transmission to remote high performance computing workstation is still an issue, and transfer of obtained parameters of pollination process is much easier.

A new documentation system for congenital absent digits.

PubMed

Jones, Neil F; Kaplan, Jesse

2012-12-01

Congenital absent digits continue to be described by many confusing terms and are currently classified in categories I, V, and VI of the International Federation of Societies for Surgery of the Hand classification and seven subclassification systems. Very few classification systems provide any logical basis for surgical reconstruction. The purpose of this study was to develop a simple alphanumerical documentation system to reproducibly describe the morphological or radiographic appearance of congenital absent digits and facilitate communication of these childrens' hand anomalies from one hand surgeon to another. Dorsal and palmar photographs and PA radiographs of 235 hands in 204 children born with congenital absent digits over a 15-year period were analyzed to determine which digital rays were missing and their level of absence. Each hand can be described by three letters, R (radial), C (central), and U (ulnar), as well as numbers 1-5. The first letter and number designate which rays are missing and the second and third letters and numbers designate which rays remain present. There are 15 morphological phenotypes of congenital absent digits. The three most common phenotypes are U4R1 (a thumb but absence of all four fingers), R1U4 (absent thumb), and R5 (aplastic hand). This new documentation system allows hand surgeons to describe the simple morphological or radiographic appearance of congenital absent digits; incorporates all the previous subclassification systems that have attempted to describe congenital absent digits in radial, central, and ulnar deficiencies, symbrachydactyly, and congenital constriction ring syndrome; and has subsequently allowed the development of an algorithm which predicts whether conventional or microsurgical reconstruction is indicated for each specific phenotype.

Computer-aided Prognosis of Neuroblastoma on Whole-slide Images: Classification of Stromal Development

PubMed Central

Sertel, O.; Kong, J.; Shimada, H.; Catalyurek, U.V.; Saltz, J.H.; Gurcan, M.N.

2009-01-01

We are developing a computer-aided prognosis system for neuroblastoma (NB), a cancer of the nervous system and one of the most malignant tumors affecting children. Histopathological examination is an important stage for further treatment planning in routine clinical diagnosis of NB. According to the International Neuroblastoma Pathology Classification (the Shimada system), NB patients are classified into favorable and unfavorable histology based on the tissue morphology. In this study, we propose an image analysis system that operates on digitized H&E stained whole-slide NB tissue samples and classifies each slide as either stroma-rich or stroma-poor based on the degree of Schwannian stromal development. Our statistical framework performs the classification based on texture features extracted using co-occurrence statistics and local binary patterns. Due to the high resolution of digitized whole-slide images, we propose a multi-resolution approach that mimics the evaluation of a pathologist such that the image analysis starts from the lowest resolution and switches to higher resolutions when necessary. We employ an offine feature selection step, which determines the most discriminative features at each resolution level during the training step. A modified k-nearest neighbor classifier is used to determine the confidence level of the classification to make the decision at a particular resolution level. The proposed approach was independently tested on 43 whole-slide samples and provided an overall classification accuracy of 88.4%. PMID:20161324

Toward Biological Subtyping of Papillary Renal Cell Carcinoma With Clinical Implications Through Histologic, Immunohistochemical, and Molecular Analysis.

PubMed

Saleeb, Rola M; Brimo, Fadi; Farag, Mina; Rompré-Brodeur, Alexis; Rotondo, Fabio; Beharry, Vidya; Wala, Samantha; Plant, Pamela; Downes, Michelle R; Pace, Kenneth; Evans, Andrew; Bjarnason, Georg; Bartlett, John M S; Yousef, George M

2017-12-01

Papillary renal cell carcinoma (PRCC) has 2 histologic subtypes. Almost half of the cases fail to meet all morphologic criteria for either type, hence are characterized as PRCC not otherwise specified (NOS). There are yet no markers to resolve the PRCC NOS category. Accurate classification can better guide the management of these patients. In our previous PRCC study we identified markers that can distinguish between the subtypes. A PRCC patient cohort of 108 cases was selected for the current study. A panel of potentially distinguishing markers was chosen from our previous genomic analysis, and assessed by immunohistochemistry. The panel exhibited distinct staining patterns between the 2 classic PRCC subtypes; and successfully reclassified the NOS (45%) cases. Moreover, these immunomarkers revealed a third subtype, PRCC3 (35% of the cohort). Molecular testing using miRNA expression and copy number variation analysis confirmed the presence of 3 distinct molecular signatures corresponding to the 3 subtypes. Disease-free survival was significantly enhanced in PRCC1 versus 2 and 3 (P=0.047) on univariate analysis. The subtypes stratification was also significant on multivariate analysis (P=0.025; hazard ratio, 6; 95% confidence interval, 1.25-32.2). We propose a new classification system of PRCC integrating morphologic, immunophenotypical, and molecular analysis. The newly described PRCC3 has overlapping morphology between PRCC1 and PRCC2, hence would be subtyped as NOS in the current classification. Molecularly PRCC3 has a distinct signature and clinically it behaves similar to PRCC2. The new classification stratifies PRCC patients into clinically relevant subgroups and has significant implications on the management of PRCC.

Automatic plankton image classification combining multiple view features via multiple kernel learning.

PubMed

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system outperforms state-of-the-art plankton image classification systems in terms of accuracy and robustness. This study demonstrated automatic plankton image classification system combining multiple view features using multiple kernel learning. The results indicated that multiple view features combined by NLMKL using three kernel functions (linear, polynomial and Gaussian kernel functions) can describe and use information of features better so that achieve a higher classification accuracy.

The morphology and classification of α ganglion cells in the rat retinae: a fractal analysis study.

PubMed

Jelinek, Herbert F; Ristanović, Dušan; Milošević, Nebojša T

2011-09-30

Rat retinal ganglion cells have been proposed to consist of a varying number of subtypes. Dendritic morphology is an essential aspect of classification and a necessary step toward understanding structure-function relationships of retinal ganglion cells. This study aimed at using a heuristic classification procedure in combination with the box-counting analysis to classify the alpha ganglion cells in the rat retinae based on the dendritic branching pattern and to investigate morphological changes with retinal eccentricity. The cells could be divided into two groups: cells with simple dendritic pattern (box dimension lower than 1.390) and cells with complex dendritic pattern (box dimension higher than 1.390) according to their dendritic branching pattern complexity. Both were further divided into two subtypes due to the stratification within the inner plexiform layer. In the present study we have shown that the alpha rat RCGs can be classified further by their dendritic branching complexity and thus extend those of previous reports that fractal analysis can be successfully used in neuronal classification, particularly that the fractal dimension represents a robust and sensitive tool for the classification of retinal ganglion cells. A hypothesis of possible functional significance of our classification scheme is also discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

[Morphological characterization of annatto fruits 9bixa orellana L.) and its correspondence with protein and isoenzym patterns].

PubMed

Medina, A M; Michelangeli, C; Ramis, C; Díaz, A

2001-01-01

A group of 32 annatto genotypes collected in five Venezuelan regions (Oriente, Centro, Llanos, Andes and Amazonas) and in Brazil were used for morphological studies. The fruit variables with the greatest discriminatory power in the formation of groups were capsule size, spinosity and seed size. On the other hand, an association group among the variables spinosity, spine length, dehiscence and apex shape were formed, also a proportional association between capsule and seed size, and between dehiscent capsule and brown coloured seeds. Additionally, in order to discriminate morphological variables behaviour in respond to electrophoretic variables, a group of protein and isozyme bands associated with fruit characteristics were established. Therefore, a classification system of this species was possible using morphological studies of the capsules, even though a determined association relating morphological and molecular patterns was not found.

Evaluation of a Diagnostic Encyclopedia Workstation for ovarian pathology.

PubMed

van Ginneken, A M; Baak, J P; Jansen, W; Smeulders, A W

1990-10-01

The Diagnostic Encyclopedia Workstation (DEW) is a computer system that provides completely integrated pictorial and textual information as reference knowledge in the field of ovarian pathology. The textual component comprises information per diagnosis such as descriptions of macroscopic and microscopic images, clinical signs, and prognosis. In addition, the system offers lists of differential diagnoses and criteria to differentiate among lists of differential diagnoses and criteria to differentiate among them. The present study evaluates to what extent the system influences the diagnostic process in efficiency and outcome. Therefore, two groups of six pathologists each, covering a wide spectrum of experience in ovarian pathology, participated in the evaluation of the DEW. The quality of the resulting diagnoses was statistically analyzed with the Wilcoxon rank sum test with respect to five different viewpoints: classification, morphology, clinical consequences, duration of diagnostic process, and consensus among the participants. The results are discussed and it is concluded that classification and morphology showed better results when books were used. The evaluation experiment was, however, very rigid and negatively biased with respect to the DEW system. Positive aspects of the encyclopedia are the easy access to diagnostic and differential diagnostic information and the large set of illustrations. Insight is acquired with respect to existing bottlenecks and how they may be overcome.

Morphologic observation and classification criteria of atretic follicles in guinea pigs.

PubMed

Wang, Wei; Liu, Hong-Lin; Tian, Wei; Zhang, Fen-Fen; Gong, Yan; Chen, Jin-Wei; Mao, Da-Gan; Shi, Fang-Xiong

2010-05-01

There is a lack of appropriate classification criteria for the determination of atretic follicles in guinea pigs. In the present study, new criteria were established based on the latest morphologic criteria for cell death proposed by the Nomenclature Committee on Cell Death (NCCD) in 2009. Ovaries of guinea pigs were sampled on different stages of estrous cycle, and the morphologic observations of atretic follicles were investigated in serial sections. The results showed that the process of follicular atresia could be classified into four continuous stages: (1) the granulosa layer became loose, and some apoptotic bodies began to appear; (2) the granulosa cells were massively eliminated; (3) the theca interna cells differentiated; and (4) the residual follicular cells degenerated. In addition, the examination revealed that these morphologic criteria were accurate and feasible. In conclusion, this study provides new criteria for the classification of atretic follicles in guinea pigs, and this knowledge can inform future research in the area.

Brain tumor classification using AFM in combination with data mining techniques.

PubMed

Huml, Marlene; Silye, René; Zauner, Gerald; Hutterer, Stephan; Schilcher, Kurt

2013-01-01

Although classification of astrocytic tumors is standardized by the WHO grading system, which is mainly based on microscopy-derived, histomorphological features, there is great interobserver variability. The main causes are thought to be the complexity of morphological details varying from tumor to tumor and from patient to patient, variations in the technical histopathological procedures like staining protocols, and finally the individual experience of the diagnosing pathologist. Thus, to raise astrocytoma grading to a more objective standard, this paper proposes a methodology based on atomic force microscopy (AFM) derived images made from histopathological samples in combination with data mining techniques. By comparing AFM images with corresponding light microscopy images of the same area, the progressive formation of cavities due to cell necrosis was identified as a typical morphological marker for a computer-assisted analysis. Using genetic programming as a tool for feature analysis, a best model was created that achieved 94.74% classification accuracy in distinguishing grade II tumors from grade IV ones. While utilizing modern image analysis techniques, AFM may become an important tool in astrocytic tumor diagnosis. By this way patients suffering from grade II tumors are identified unambiguously, having a less risk for malignant transformation. They would benefit from early adjuvant therapies.

Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

2016-09-01

We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

[Systematization of diseases and lesions of the endometrium by etiological and pathogenetical mechanisms of development to choose an optimal treatment].

PubMed

Boroda, A M

2004-03-01

Current clinical gynecology considers pathological states of endometrium (PSE) as one of the most challenging issue of the day. Many questions of etiology, pathogenesis, diagnostics, and treatment of PSE are still under discussion. Nowadays there isn't a whole agreed classification of PSE. Morphological classification remains the most widely used one, but morphological changes occurring in the endometrium don't show a wide variety of disorders related to these pathological states. A new clinicopathogenetic classification of PSE was proposed, which is based on choosing the optimal treatment with functional state of the disease taken into account. This classification helps us to perceive the problem as a whole with choosing functionally based treatment for each patient.

Root Morphology and Canal Configuration of First and Second Maxillary Molars in a Selected Iranian Population: A Cone-Beam Computed Tomography Evaluation

PubMed Central

Khademi, Abbasali; Zamani Naser, Asieh; Bahreinian, Zahra; Mehdizadeh, Mojdeh; Najarian, Mojtaba; Khazaei, Saber

2017-01-01

Introduction: The aim of this investigation was to evaluate root canal morphology of maxillary first and second molars and also to assess the prevalence and morphology of the second mesiobuccal canal (MB2) in these teeth, using cone-beam computed tomography (CBCT). Methods and Materials: In this cross-sectional study, the total of 470 CBCT images from the archive of Radiology Department of Isfahan University of Medical Sciences (IUMS), Iran, was evaluated and 295 images were selected. The number of roots, and canal configuration were determined based on Vertucci’s classification system. The data was analyzed using SPSS 20, and P-values less than 0.05 were considered significant. Results: A total of 295 images from 295 patients (165 females and 130 males), including 389 maxillary first (197 right and 192 left) and 460 maxillary second (235 right and 225 left) molars were evaluated. The prevalence of MB2 canals were 70.2% and 43.4% in the maxillary first and second molars, respectively. The most common type of Vertucci’s classification was type II (53.1%), followed by type I. Conclusion: The second mesiobuccal canal was present in almost two thirds of first and less than half of second molars. The morphology and canal configuration of a maxillary molar can almost predict the morphology of contralateral molar. However, it does not relate to the ipsilateral molar. PMID:28808452

Algorithms for Hyperspectral Endmember Extraction and Signature Classification with Morphological Dendritic Networks

NASA Astrophysics Data System (ADS)

Schmalz, M.; Ritter, G.

Accurate multispectral or hyperspectral signature classification is key to the nonimaging detection and recognition of space objects. Additionally, signature classification accuracy depends on accurate spectral endmember determination [1]. Previous approaches to endmember computation and signature classification were based on linear operators or neural networks (NNs) expressed in terms of the algebra (R, +, x) [1,2]. Unfortunately, class separation in these methods tends to be suboptimal, and the number of signatures that can be accurately classified often depends linearly on the number of NN inputs. This can lead to poor endmember distinction, as well as potentially significant classification errors in the presence of noise or densely interleaved signatures. In contrast to traditional CNNs, autoassociative morphological memories (AMM) are a construct similar to Hopfield autoassociatived memories defined on the (R, +, ?,?) lattice algebra [3]. Unlimited storage and perfect recall of noiseless real valued patterns has been proven for AMMs [4]. However, AMMs suffer from sensitivity to specific noise models, that can be characterized as erosive and dilative noise. On the other hand, the prior definition of a set of endmembers corresponds to material spectra lying on vertices of the minimum convex region covering the image data. These vertices can be characterized as morphologically independent patterns. It has further been shown that AMMs can be based on dendritic computation [3,6]. These techniques yield improved accuracy and class segmentation/separation ability in the presence of highly interleaved signature data. In this paper, we present a procedure for endmember determination based on AMM noise sensitivity, which employs morphological dendritic computation. We show that detected endmembers can be exploited by AMM based classification techniques, to achieve accurate signature classification in the presence of noise, closely spaced or interleaved signatures, and simulated camera optical distortions. In particular, we examine two critical cases: (1) classification of multiple closely spaced signatures that are difficult to separate using distance measures, and (2) classification of materials in simulated hyperspectral images of spaceborne satellites. In each case, test data are derived from a NASA database of space material signatures. Additional analysis pertains to computational complexity and noise sensitivity, which are superior to classical NN based techniques.

Comprehensive 4-stage categorization of bicuspid aortic valve leaflet morphology by cardiac MRI in 386 patients.

PubMed

Murphy, I G; Collins, J; Powell, A; Markl, M; McCarthy, P; Malaisrie, S C; Carr, J C; Barker, A J

2017-08-01

Bicuspid aortic valve (BAV) disease is heterogeneous and related to valve dysfunction and aortopathy. Appropriate follow up and surveillance of patients with BAV may depend on correct phenotypic categorization. There are multiple classification schemes, however a need exists to comprehensively capture commissure fusion, leaflet asymmetry, and valve orifice orientation. Our aim was to develop a BAV classification scheme for use at MRI to ascertain the frequency of different phenotypes and the consistency of BAV classification. The BAV classification scheme builds on the Sievers surgical BAV classification, adding valve orifice orientation, partial leaflet fusion and leaflet asymmetry. A single observer successfully applied this classification to 386 of 398 Cardiac MRI studies. Repeatability of categorization was ascertained with intraobserver and interobserver kappa scores. Sensitivity and specificity of MRI findings was determined from operative reports, where available. Fusion of the right and left leaflets accounted for over half of all cases. Partial leaflet fusion was seen in 46% of patients. Good interobserver agreement was seen for orientation of the valve opening (κ = 0.90), type (κ = 0.72) and presence of partial fusion (κ = 0.83, p < 0.0001). Retrospective review of operative notes showed sensitivity and specificity for orientation (90, 93%) and for Sievers type (73, 87%). The proposed BAV classification schema was assessed by MRI for its reliability to classify valve morphology in addition to illustrating the wide heterogeneity of leaflet size, orifice orientation, and commissural fusion. The classification may be helpful in further understanding the relationship between valve morphology, flow derangement and aortopathy.

Classifying Radio Galaxies with the Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Aniyan, A. K.; Thorat, K.

2017-06-01

We present the application of a deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks (CNN). In this study, we have taken the case of the Fanaroff-Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA)—Faint Images of the Radio Sky at Twenty Centimeters survey and existing visually classified samples available in the literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categories is ˜200 sources, which has been augmented by rotated versions of the same. Our study shows that CNNs can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and a “fusion classifier,” which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while the bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification, while being much faster. Finally, we discuss the computational and data-related challenges associated with the morphological classification of radio galaxies with CNNs.

Image classification of human carcinoma cells using complex wavelet-based covariance descriptors.

PubMed

Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A Enis; Cetin-Atalay, Rengul

2013-01-01

Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-[Formula: see text]WT) coefficients and several morphological attributes are computed. Directionally selective DT-[Formula: see text]WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html.

Image Classification of Human Carcinoma Cells Using Complex Wavelet-Based Covariance Descriptors

PubMed Central

Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A. Enis; Cetin-Atalay, Rengul

2013-01-01

Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-WT) coefficients and several morphological attributes are computed. Directionally selective DT-WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html. PMID:23341908

A discrete wavelet based feature extraction and hybrid classification technique for microarray data analysis.

PubMed

Bennet, Jaison; Ganaprakasam, Chilambuchelvan Arul; Arputharaj, Kannan

2014-01-01

Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN), naive Bayes, and support vector machine (SVM). Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT) and moving window technique (MWT) is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

Multilocus resolution of Mugilidae phylogeny (Teleostei: Mugiliformes): Implications for the family's taxonomy.

PubMed

Xia, Rong; Durand, Jean-Dominique; Fu, Cuizhang

2016-03-01

The interrelationships among mugilids (Mugiliformes: Mugilidae) remain highly debated. Using a mitochondrial gene-based phylogeny as criterion, a revised classification with 25 genera in the Mugilidae has recently been proposed. However, phylogenetic relationships of major mitochondrial lineages remain unresolved and to gain a general acceptance the classification requires confirmation based on multilocus evidence and diagnostic morphological characters. Here, we construct a species-tree using twelve nuclear and three mitochondrial loci and infer the evolution of 71 morphological characters. Our multilocus phylogeny does not agree with previous morphology-based hypotheses for the relationships within Mugilidae, confirms the revised classification with 25 genera and further resolves their phylogenetic relationships. Using the well-resolved multilocus phylogeny as the criterion, we reclassify Mugilidae genera into three new subfamilies (Myxinae, Rhinomugilinae, and Cheloninae) and one new, recombined, subfamily (Mugilinae). The Rhinomugilinae subfamily is further divided into four tribes. The revised classification of Mugilidae is supported by morpho-anatomical synapomorphies or a combination of characters. These characters are used to erect a key to the subfamilies and genera. Copyright © 2015 Elsevier Inc. All rights reserved.

Classification of wet aged related macular degeneration using optical coherence tomographic images

NASA Astrophysics Data System (ADS)

Haq, Anam; Mir, Fouwad Jamil; Yasin, Ubaid Ullah; Khan, Shoab A.

2013-12-01

Wet Age related macular degeneration (AMD) is a type of age related macular degeneration. In order to detect Wet AMD we look for Pigment Epithelium detachment (PED) and fluid filled region caused by choroidal neovascularization (CNV). This form of AMD can cause vision loss if not treated in time. In this article we have proposed an automated system for detection of Wet AMD in Optical coherence tomographic (OCT) images. The proposed system extracts PED and CNV from OCT images using segmentation and morphological operations and then detailed feature set are extracted. These features are then passed on to the classifier for classification. Finally performance measures like accuracy, sensitivity and specificity are calculated and the classifier delivering the maximum performance is selected as a comparison measure. Our system gives higher performance using SVM as compared to other methods.

An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.

Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

PubMed

Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

2015-12-01

We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality

NASA Astrophysics Data System (ADS)

Krappe, Sebastian; Benz, Michaela; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

2015-03-01

The morphological analysis of bone marrow smears is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually with the use of bright field microscope. This is a time consuming, partly subjective and tedious process. Furthermore, repeated examinations of a slide yield intra- and inter-observer variances. For this reason an automation of morphological bone marrow analysis is pursued. This analysis comprises several steps: image acquisition and smear detection, cell localization and segmentation, feature extraction and cell classification. The automated classification of bone marrow cells is depending on the automated cell segmentation and the choice of adequate features extracted from different parts of the cell. In this work we focus on the evaluation of support vector machines (SVMs) and random forests (RFs) for the differentiation of bone marrow cells in 16 different classes, including immature and abnormal cell classes. Data sets of different segmentation quality are used to test the two approaches. Automated solutions for the morphological analysis for bone marrow smears could use such a classifier to pre-classify bone marrow cells and thereby shortening the examination duration.

Comparison Between Supervised and Unsupervised Classifications of Neuronal Cell Types: A Case Study

PubMed Central

Guerra, Luis; McGarry, Laura M; Robles, Víctor; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2011-01-01

In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 71: 71–82, 2011 PMID:21154911

Very Deep Convolutional Neural Networks for Morphologic Classification of Erythrocytes.

PubMed

Durant, Thomas J S; Olson, Eben M; Schulz, Wade L; Torres, Richard

2017-12-01

Morphologic profiling of the erythrocyte population is a widely used and clinically valuable diagnostic modality, but one that relies on a slow manual process associated with significant labor cost and limited reproducibility. Automated profiling of erythrocytes from digital images by capable machine learning approaches would augment the throughput and value of morphologic analysis. To this end, we sought to evaluate the performance of leading implementation strategies for convolutional neural networks (CNNs) when applied to classification of erythrocytes based on morphology. Erythrocytes were manually classified into 1 of 10 classes using a custom-developed Web application. Using recent literature to guide architectural considerations for neural network design, we implemented a "very deep" CNN, consisting of >150 layers, with dense shortcut connections. The final database comprised 3737 labeled cells. Ensemble model predictions on unseen data demonstrated a harmonic mean of recall and precision metrics of 92.70% and 89.39%, respectively. Of the 748 cells in the test set, 23 misclassification errors were made, with a correct classification frequency of 90.60%, represented as a harmonic mean across the 10 morphologic classes. These findings indicate that erythrocyte morphology profiles could be measured with a high degree of accuracy with "very deep" CNNs. Further, these data support future efforts to expand classes and optimize practical performance in a clinical environment as a prelude to full implementation as a clinical tool. © 2017 American Association for Clinical Chemistry.

Classification of threespine stickleback along the benthic-limnetic axis.

PubMed

Willacker, James J; von Hippel, Frank A; Wilton, Peter R; Walton, Kelly M

2010-11-01

Many species of fish display morphological divergence between individuals feeding on macroinvertebrates associated with littoral habitats (benthic morphotypes) and individuals feeding on zooplankton in the limnetic zone (limnetic morphotypes). Threespine stickleback (Gasterosteus aculeatus L.) have diverged along the benthic-limnetic axis into allopatric morphotypes in thousands of populations and into sympatric species pairs in several lakes. However, only a few well known populations have been studied because identifying additional populations as either benthic or limnetic requires detailed dietary or observational studies. Here we develop a Fisher's linear discriminant function based on the skull morphology of known benthic and limnetic stickleback populations from the Cook Inlet Basin of Alaska and test the feasibility of using this function to identify other morphologically divergent populations. Benthic and limnetic morphotypes were separable using this technique and of 45 populations classified, three were identified as morphologically extreme (two benthic and one limnetic), nine as moderately divergent (three benthic and six limnetic) and the remaining 33 populations as morphologically intermediate. Classification scores were found to correlate with eye size, the depth profile of lakes, and the presence of invasive northern pike (Esox lucius). This type of classification function provides a means of integrating the complex morphological differences between morphotypes into a single score that reflects the position of a population along the benthic-limnetic axis and can be used to relate that position to other aspects of stickleback biology.

Classification of threespine stickleback along the benthic-limnetic axis

PubMed Central

Willacker, James J.; von Hippel, Frank A.; Wilton, Peter R.; Walton, Kelly M.

2010-01-01

Many species of fish display morphological divergence between individuals feeding on macroinvertebrates associated with littoral habitats (benthic morphotypes) and individuals feeding on zooplankton in the limnetic zone (limnetic morphotypes). Threespine stickleback (Gasterosteus aculeatus L.) have diverged along the benthic-limnetic axis into allopatric morphotypes in thousands of populations and into sympatric species pairs in several lakes. However, only a few well known populations have been studied because identifying additional populations as either benthic or limnetic requires detailed dietary or observational studies. Here we develop a Fisher’s linear discriminant function based on the skull morphology of known benthic and limnetic stickleback populations from the Cook Inlet Basin of Alaska and test the feasibility of using this function to identify other morphologically divergent populations. Benthic and limnetic morphotypes were separable using this technique and of 45 populations classified, three were identified as morphologically extreme (two benthic and one limnetic), nine as moderately divergent (three benthic and six limnetic) and the remaining 33 populations as morphologically intermediate. Classification scores were found to correlate with eye size, the depth profile of lakes, and the presence of invasive northern pike (Esox lucius). This type of classification function provides a means of integrating the complex morphological differences between morphotypes into a single score that reflects the position of a population along the benthic-limnetic axis and can be used to relate that position to other aspects of stickleback biology. PMID:21221422

A new approach to children's footwear based on foot type classification.

PubMed

Mauch, M; Grau, S; Krauss, I; Maiwald, C; Horstmann, T

2009-08-01

Current shoe designs do not allow for the comprehensive 3-D foot shape, which means they are unable to reproduce the wide variability in foot morphology. Therefore, the purpose of this study was to capture these variations of children's feet by classifying them into groups (types) and thereby provide a basis for their implementation in the design of children's shoes. The feet of 2867 German children were measured using a 3-D foot scanner. Cluster analysis was then applied to classify the feet into three different foot types. The characteristics of these foot types differ regarding their volume and forefoot shape both within and between shoe sizes. This new approach is in clear contrast to previous systems, since it captures the variability of foot morphology in a more comprehensive way by using a foot typing system and therefore paves the way for the unimpaired development of children's feet. Previous shoe systems do not allow for the wide variations in foot morphology. A new approach was developed regarding different morphological foot types based on 3-D measurements relevant in shoe construction. This can be directly applied to create specific designs for children's shoes.

Image processing and machine learning in the morphological analysis of blood cells.

PubMed

Rodellar, J; Alférez, S; Acevedo, A; Molina, A; Merino, A

2018-05-01

This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears. The basics of the 3 core elements (segmentation, quantitative features, and classification) are outlined, and recent literature is discussed. Although red blood cells are a significant part of this context, this study focuses on malignant lymphoid cells and blast cells. There is no doubt that these technologies may help the cytologist to perform efficient, objective, and fast morphological analysis of blood cells. They may also help in the interpretation of some morphological features and may serve as learning and survey tools. Although research is still needed, it is important to define screening strategies to exploit the potential of image-based automatic recognition systems integrated in the daily routine of laboratories along with other analysis methodologies. © 2018 John Wiley & Sons Ltd.

Classifying Radio Galaxies with the Convolutional Neural Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aniyan, A. K.; Thorat, K.

We present the application of a deep machine learning technique to classify radio images of extended sources on a morphological basis using convolutional neural networks (CNN). In this study, we have taken the case of the Fanaroff–Riley (FR) class of radio galaxies as well as radio galaxies with bent-tailed morphology. We have used archival data from the Very Large Array (VLA)—Faint Images of the Radio Sky at Twenty Centimeters survey and existing visually classified samples available in the literature to train a neural network for morphological classification of these categories of radio sources. Our training sample size for each of these categoriesmore » is ∼200 sources, which has been augmented by rotated versions of the same. Our study shows that CNNs can classify images of the FRI and FRII and bent-tailed radio galaxies with high accuracy (maximum precision at 95%) using well-defined samples and a “fusion classifier,” which combines the results of binary classifications, while allowing for a mechanism to find sources with unusual morphologies. The individual precision is highest for bent-tailed radio galaxies at 95% and is 91% and 75% for the FRI and FRII classes, respectively, whereas the recall is highest for FRI and FRIIs at 91% each, while the bent-tailed class has a recall of 79%. These results show that our results are comparable to that of manual classification, while being much faster. Finally, we discuss the computational and data-related challenges associated with the morphological classification of radio galaxies with CNNs.« less

An Independent Inter- and Intraobserver Agreement Evaluation of the AOSpine Subaxial Cervical Spine Injury Classification System.

PubMed

Urrutia, Julio; Zamora, Tomas; Yurac, Ratko; Campos, Mauricio; Palma, Joaquin; Mobarec, Sebastian; Prada, Carlos

2017-03-01

An agreement study. The aim of this study was to perform an independent interobserver and intraobserver agreement assessment of the AOSpine subaxial cervical spine injury classification system. The AOSpine subaxial cervical spine injury classification system was recently described. It showed substantial inter- and intraobserver agreement in the study describing it; however, an independent evaluation has not been performed. Anteroposterior and lateral radiographs, computed tomography scans, and magnetic resonance imaging of 65 patients with acute traumatic subaxial cervical spine injuries were selected and classified using the morphologic grading of the subaxial cervical spine injury classification system by 6 evaluators (3 spine surgeons and 3 orthopedic surgery residents). After a 6-week interval, the 65 cases were presented to the same evaluators in a random sequence for repeat evaluation. The kappa coefficient (κ) was used to determine the inter- and intraobserver agreement. The interobserver agreement was substantial when considering the fracture main types (A, B, C, or F), with κ = 0.61 (0.57-0.64), but moderate when considering the subtypes: κ = 0.57 (0.54-0.60). The intraobserver agreement was substantial considering the fracture types, with κ = 0.68 (0.62-0.74) and considering subtypes, κ = 0.62 (0.57-0.66). No significant differences were observed between spine surgeons and orthopedic residents in the overall inter- and intraobserver agreement, or in the inter- and intraobserver agreement of specific A, B, C, or F type of injuries. This classification allows adequate agreement among different observers and by the same observer on separate occasions. Future prospective studies should determine whether this classification allows surgeons to decide the best treatment for patients with subaxial cervical spine injuries. 3.

Intrarater and interrater reliability and validity in the assessment of the mechanism of injury and integrity of the posterior ligamentous complex: a novel injury severity scoring system for thoracolumbar injuries. Invited submission from the Joint Section Meeting On Disorders of the Spine and Peripheral Nerves, March 2005.

PubMed

Harrop, James S; Vaccaro, Alexander R; Hurlbert, R John; Wilsey, Jared T; Baron, Eli M; Shaffrey, Christopher I; Fisher, Charles G; Dvorak, Marcel F; Oner, F C; Wood, Kirkham B; Anand, Neel; Anderson, D Greg; Lim, Moe R; Lee, Joon Y; Bono, Christopher M; Arnold, Paul M; Rampersaud, Y Raja; Fehlings, Michael G

2006-02-01

A new classification and treatment algorithm for thoracolumbar injuries was recently introduced by Vaccaro and colleagues in 2005. A thoracolumbar injury severity scale (TLISS) was proposed for grading and guiding treatment for these injuries. The scale is based on the following: 1) the mechanism of injury; 2) the integrity of the posterior ligamentous complex (PLC); and 3) the patient's neurological status. The reliability and validity of assessing injury mechanism and the integrity of the PLC was assessed. Forty-eight spine surgeons, consisting of neurosurgeons and orthopedic surgeons, reviewed 56 clinical thoracolumbar injury case histories. Each was classified and scored to determine treatment recommendations according to a novel classification system. After 3 months the case histories were reordered and the physicians repeated the exercise. Validity of this classification was good among reviewers; the vast majority (> 90%) agreed with the system's treatment recommendations. Surgeons were unclear as to a cogent description of PLC disruption and fracture mechanism. The TLISS demonstrated acceptable reliability in terms of intra- and interobserver agreement on the algorithm's treatment recommendations. Replacing injury mechanism with a description of injury morphology and better definition of PLC injury will improve inter- and intraobserver reliability of this injury classification system.

Diagnostic value of plasma morphology in patients with coronary heart disease

NASA Astrophysics Data System (ADS)

Malinova, Lidia I.; Sergeeva, Yuliya V.; Simonenko, Georgy V.; Tuchin, Valery V.; Denisova, Tatiana P.

2006-08-01

Blood plasma can be considered as a special water system with self-organization possibilities. Plasma slides as the results of wedge dehydration reflect its stereochemical interaction and their study can be used in diagnostic processes. 46 patients with coronary heart disease were studied. The main group was formed of men in age ranged from 54 to 72 years old with stable angina pectoris of II and III functional class (by Canadian classification) (n=25). The group of compare was of those who was hospitalized with diagnosis of acute coronary syndrome, men in age range 40-82. Clinical examination, basic biochemical tests and functional plasma morphology characteristics were studied. A number of qualitative and quantitative differences of blood plasma morphology of patients with chronic and acute coronary disease forms was revealed.

Neuromuscular disease classification system

NASA Astrophysics Data System (ADS)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Context-based automated defect classification system using multiple morphological masks

DOEpatents

Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

2002-01-01

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

National Seabed Mapping Programmes Collaborate to Advance Marine Geomorphological Mapping in Adjoining European Seas

NASA Astrophysics Data System (ADS)

Monteys, X.; Guinan, J.; Green, S.; Gafeira, J.; Dove, D.; Baeten, N. J.; Thorsnes, T.

2017-12-01

Marine geomorphological mapping is an effective means of characterising and understanding the seabed and its features with direct relevance to; offshore infrastructure placement, benthic habitat mapping, conservation & policy, marine spatial planning, fisheries management and pure research. Advancements in acoustic survey techniques and data processing methods resulting in the availability of high-resolution marine datasets e.g. multibeam echosounder bathymetry and shallow seismic mean that geological interpretations can be greatly improved by combining with geomorphological maps. Since December 2015, representatives from the national seabed mapping programmes of Norway (MAREANO), Ireland (INFOMAR) and the United Kingdom (MAREMAP) have collaborated and established the MIM geomorphology working group) with the common aim of advancing best practice for geological mapping in their adjoining sea areas in north-west Europe. A recently developed two-part classification system for Seabed Geomorphology (`Morphology' and Geomorphology') has been established as a result of an initiative led by the British Geological Survey (BGS) with contributions from the MIM group (Dove et al. 2016). To support the scheme, existing BGS GIS tools (SIGMA) have been adapted to apply this two-part classification system and here we present on the tools effectiveness in mapping geomorphological features, along with progress in harmonising the classification and feature nomenclature. Recognising that manual mapping of seabed features can be time-consuming and subjective, semi-automated approaches for mapping seabed features and improving mapping efficiency is being developed using Arc-GIS based tools. These methods recognise, spatially delineate and morphologically describe seabed features such as pockmarks (Gafeira et al., 2012) and cold-water coral mounds. Such tools utilise multibeam echosounder data or any other bathymetric dataset (e.g. 3D seismic, Geldof et al., 2014) that can produce a depth digital model. The tools have the capability to capture an extensive list of morphological attributes. The MIM geomorphology working group's strategy to develop methods for more efficient marine geomorphological mapping is presented with data examples and case studies showing the latest results.

Analyzing Sub-Classifications of Glaucoma via SOM Based Clustering of Optic Nerve Images.

PubMed

Yan, Sanjun; Abidi, Syed Sibte Raza; Artes, Paul Habib

2005-01-01

We present a data mining framework to cluster optic nerve images obtained by Confocal Scanning Laser Tomography (CSLT) in normal subjects and patients with glaucoma. We use self-organizing maps and expectation maximization methods to partition the data into clusters that provide insights into potential sub-classification of glaucoma based on morphological features. We conclude that our approach provides a first step towards a better understanding of morphological features in optic nerve images obtained from glaucoma patients and healthy controls.

Listening to galaxies tuning at z ~ 2.5-3.0: The first strikes of the Hubble fork

NASA Astrophysics Data System (ADS)

Talia, M.; Cimatti, A.; Mignoli, M.; Pozzetti, L.; Renzini, A.; Kurk, J.; Halliday, C.

2014-02-01

Aims: We investigate the morphological properties of 494 galaxies selected from the Galaxy Mass Assembly ultra-deep Spectroscopic Survey (GMASS) at z > 1, primarily in their optical rest frame, using Hubble Space Telescope (HST) infrared images, from the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS). Methods: The morphological analysis of Wield Field Camera (WFC3) H160 band images was performed using two different methods: a visual classification identifying traditional Hubble types, and a quantitative analysis using parameters that describe structural properties, such as the concentration of light and the rotational asymmetry. The two classifications are compared. We then analysed how apparent morphologies correlate with the physical properties of galaxies. Results: The fractions of both elliptical and disk galaxies decrease between redshifts z ~ 1 to z ~ 3, while at z > 3 the galaxy population is dominated by irregular galaxies. The quantitative morphological analysis shows that, at 1 < z < 3, morphological parameters are not as effective in distinguishing the different morphological Hubble types as they are at low redshift. No significant morphological k-correction was found to be required for the Hubble type classification, with some exceptions. In general, different morphological types occupy the two peaks of the (U - B)rest colour bimodality of galaxies: most irregulars occupy the blue peak, while ellipticals are mainly found in the red peak, though with some level of contamination. Disks are more evenly distributed than either irregulars and ellipticals. We find that the position of a galaxy in a UVJ diagram is related to its morphological type: the "quiescent" region of the plot is mainly occupied by ellipticals and, to a lesser extent, by disks. We find that only ~33% of all morphological ellipticals in our sample are red and passively evolving galaxies, a percentage that is consistent with previous results obtained at z < 1. Blue galaxies morphologically classified as ellipticals show a remarkable structural similarity to red ones. We search for correlations between our morphological and spectroscopic galaxy classifications. Almost all irregulars have a star-forming galaxy spectrum. In addition, the majority of disks show some sign of star-formation activity in their spectra, though in some cases their red continuum is indicative of old stellar populations. Finally, an elliptical morphology may be associated with either passively evolving or strongly star-forming galaxies. Conclusions: We propose that the Hubble sequence of galaxy morphologies takes shape at redshift 2.5 < z < 3. The fractions of both ellipticals and disks decrease with increasing lookback time at z > 1, such that at redshifts z = 2.5-2.7 and above, the Hubble types cannot be identified, and most galaxies are classified as irregular. Appendix A is available in electronic form at http://www.aanda.org

Improving galaxy morphologies for SDSS with Deep Learning

NASA Astrophysics Data System (ADS)

Domínguez Sánchez, H.; Huertas-Company, M.; Bernardi, M.; Tuccillo, D.; Fischer, J. L.

2018-05-01

We present a morphological catalogue for ˜670 000 galaxies in the Sloan Digital Sky Survey in two flavours: T-type, related to the Hubble sequence, and Galaxy Zoo 2 (GZ2 hereafter) classification scheme. By combining accurate existing visual classification catalogues with machine learning, we provide the largest and most accurate morphological catalogue up to date. The classifications are obtained with Deep Learning algorithms using Convolutional Neural Networks (CNNs). We use two visual classification catalogues, GZ2 and Nair & Abraham (2010), for training CNNs with colour images in order to obtain T-types and a series of GZ2 type questions (disc/features, edge-on galaxies, bar signature, bulge prominence, roundness, and mergers). We also provide an additional probability enabling a separation between pure elliptical (E) from S0, where the T-type model is not so efficient. For the T-type, our results show smaller offset and scatter than previous models trained with support vector machines. For the GZ2 type questions, our models have large accuracy (>97 per cent), precision and recall values (>90 per cent), when applied to a test sample with the same characteristics as the one used for training. The catalogue is publicly released with the paper.

Classification of Pelteobagrus fish in Poyang Lake based on mitochondrial COI gene sequence.

PubMed

Zhong, Bin; Chen, Ting-Ting; Gong, Rui-Yue; Zhao, Zhe-Xia; Wang, Binhua; Fang, Chunlin; Mao, Hui-Ling

2016-11-01

We use DNA molecular marker technology to correct the deficiency of traditional morphological taxonomy. Totality 770 Pelteobagrus fish from Poyang Lake were collected. After preliminary morphological classification, random selected eight samples in each species for DNA extraction. Mitochondrial COI gene sequence was cloned with universal primers and sequenced. The results showed that there are four species of Pelteobagrus living in Poyang Lake. The average of intraspecific genetic distance value was 0.003, while the average interspecific genetic distance was 0.128. The interspecific genetic distance is far more than intraspecific genetic distance. Besides, phylogenetic tree analysis revealed that molecular systematics was in accord with morphological classification. It indicated that COI gene is an effective DNA molecular marker in Pelteobagrus classification. Surprisingly, the intraspecific difference of some individuals (P. e6, P. n6, P. e5, and P. v4) from their original named exceeded species threshold (2%), which should be renewedly classified into Pelteobagrus fulvidraco. However, another individual P. v3 was very different, because its genetic distance was over 8.4% difference from original named Pelteobagrus vachelli. Its taxonomic status remained to be further studied.

A signature dissimilarity measure for trabecular bone texture in knee radiographs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.

Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size,more » anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (>64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND-CHARM system (64.2%). Conclusions: The SDM is well suited for the classification of TB texture images in knee OA detection and may be useful for the texture classification of medical images in general.« less

Quantitative morphometrical characterization of human pronuclear zygotes.

PubMed

Beuchat, A; Thévenaz, P; Unser, M; Ebner, T; Senn, A; Urner, F; Germond, M; Sorzano, C O S

2008-09-01

Identification of embryos with high implantation potential remains a challenge in in vitro fertilization (IVF). Subjective pronuclear (PN) zygote scoring systems have been developed for that purpose. The aim of this work was to provide a software tool that enables objective measuring of morphological characteristics of the human PN zygote. A computer program was created to analyse zygote images semi-automatically, providing precise morphological measurements. The accuracy of this approach was first validated by comparing zygotes from two different IVF centres with computer-assisted measurements or subjective scoring. Computer-assisted measurement and subjective scoring were then compared for their ability to classify zygotes with high and low implantation probability by using a linear discriminant analysis. Zygote images coming from the two IVF centres were analysed with the software, resulting in a series of precise measurements of 24 variables. Using subjective scoring, the cytoplasmic halo was the only feature which was significantly different between the two IVF centres. Computer-assisted measurements revealed significant differences between centres in PN centring, PN proximity, cytoplasmic halo and features related to nucleolar precursor bodies distribution. The zygote classification error achieved with the computer-assisted measurements (0.363) was slightly inferior to that of the subjective ones (0.393). A precise and objective characterization of the morphology of human PN zygotes can be achieved by the use of an advanced image analysis tool. This computer-assisted analysis allows for a better morphological characterization of human zygotes and can be used for classification.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Morphological classification of plant cell deaths.

PubMed

van Doorn, W G; Beers, E P; Dangl, J L; Franklin-Tong, V E; Gallois, P; Hara-Nishimura, I; Jones, A M; Kawai-Yamada, M; Lam, E; Mundy, J; Mur, L A J; Petersen, M; Smertenko, A; Taliansky, M; Van Breusegem, F; Wolpert, T; Woltering, E; Zhivotovsky, B; Bozhkov, P V

2011-08-01

Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about the classification of PCD in plants. Here we suggest a classification based on morphological criteria. According to this classification, the use of the term 'apoptosis' is not justified in plants, but at least two classes of PCD can be distinguished: vacuolar cell death and necrosis. During vacuolar cell death, the cell contents are removed by a combination of autophagy-like process and release of hydrolases from collapsed lytic vacuoles. Necrosis is characterised by early rupture of the plasma membrane, shrinkage of the protoplast and absence of vacuolar cell death features. Vacuolar cell death is common during tissue and organ formation and elimination, whereas necrosis is typically found under abiotic stress. Some examples of plant PCD cannot be ascribed to either major class and are therefore classified as separate modalities. These are PCD associated with the hypersensitive response to biotrophic pathogens, which can express features of both necrosis and vacuolar cell death, PCD in starchy cereal endosperm and during self-incompatibility. The present classification is not static, but will be subject to further revision, especially when specific biochemical pathways are better defined.

Intraclass Evolution and Classification of the Colpodea (Ciliophora)

PubMed Central

FOISSNER, WILHELM; STOECK, THORSTEN; AGATHA, SABINE; DUNTHORN, MICAH

2012-01-01

Using nine new taxa and statistical inferences based on morphological and molecular data, we analyze the evolution within the class Colpodea. The molecular and cladistic analyses show four well-supported clades: platyophryids, bursariomorphids, cyrtolophosidids, and colpodids. There is a widespread occurrence of homoplasies, affecting even conspicuous morphological characteristics, e.g. the inclusion of the micronucleus in the perinuclear space of the macronucleus. The most distinct changes in the morphological classification are the lack of a basal divergence into two subclasses and the split of the cyrtolophosidids into two main clades, differing mainly by the presence vs. absence of an oral cavity. The most complex clade is that of the colpodids. We partially reconcile the morphological and molecular data using evolutionary systematics, providing a scenario in which the colpodids evolved from a Bardeliella-like ancestor and the genus Colpoda performed an intense adaptive radiation, giving rise to three main clades: Colpodina n. subord., Grossglockneriina, and Bryophryina. Three new taxa are established: Colpodina n. subord., Tillinidae n. fam., and Ottowphryidae n. fam. Colpodean evolution and classification are far from being understood because sequences are lacking for most species and half of their diversity is possibly undescribed. PMID:21762424

Secretin-stimulated MRI characterization of pancreatic morphology and function in patients with chronic pancreatitis.

PubMed

Madzak, Adnan; Olesen, Søren Schou; Haldorsen, Ingfrid Salvesen; Drewes, Asbjørn Mohr; Frøkjær, Jens Brøndum

Chronic pancreatitis (CP) is characterized by abnormal pancreatic morphology and impaired endocrine and exocrine function. However, little is known about the relationship between pancreatic morphology and function, and also the association with the etiology and clinical manifestations of CP. The aim was to explore pancreatic morphology and function with advanced MRI in patients with CP and healthy controls (HC) METHODS: Eighty-two patients with CP and 22 HC were enrolled in the study. Morphological imaging parameters included pancreatic main duct diameter, gland volume, fat signal fraction and apparent diffusion coefficient (ADC) values. Functional secretin-stimulated MRI (s-MRI) parameters included pancreatic secretion (bowel fluid volume) and changes in pancreatic ADC value before and after secretin stimulation. Patients were classified according to the modified Cambridge and M-ANNHEIM classification system and fecal elastase was collected. All imaging parameters differentiated CP patients from HC; however, correlations between morphological and functional parameters in CP were weak. Patients with alcoholic and non-alcoholic etiology had comparable s-MRI findings. Fecal elastase was positively correlated to pancreatic gland volume (r = 0.68, P = 0.0016) and negatively correlated to Cambridge classification (r = -0.35, P < 0.001). Additionally, gland volume was negatively correlated to the duration of CP (r = -0.39, P < 0.001) and baseline ADC (r = -0.35, P = 0.027). When stratified by clinical stage (M-ANNHEIM), the pancreatic gland volume was significantly decreased in the severe stages of CP (P = 0.001). S-MRI provides detailed information about pancreatic morphology and function and represents a promising non-invasive imaging method to characterize pancreatic pathophysiology and may enable monitoring of disease progression in patients with CP. Copyright © 2017 IAP and EPC. Published by Elsevier B.V. All rights reserved.

The chemotaxonomic classification of Rhodiola plants and its correlation with morphological characteristics and genetic taxonomy.

PubMed

Liu, Zhenli; Liu, Yuanyan; Liu, Chunsheng; Song, Zhiqian; Li, Qing; Zha, Qinglin; Lu, Cheng; Wang, Chun; Ning, Zhangchi; Zhang, Yuxin; Tian, Cheng; Lu, Aiping

2013-07-12

Rhodiola plants are used as a natural remedy in the western world and as a traditional herbal medicine in China, and are valued for their ability to enhance human resistance to stress or fatigue and to promote longevity. Due to the morphological similarities among different species, the identification of the genus remains somewhat controversial, which may affect their safety and effectiveness in clinical use. In this paper, 47 Rhodiola samples of seven species were collected from thirteen local provinces of China. They were identified by their morphological characteristics and genetic and phytochemical taxonomies. Eight bioactive chemotaxonomic markers from four chemical classes (phenylpropanoids, phenylethanol derivatives, flavonoids and phenolic acids) were determined to evaluate and distinguish the chemotaxonomy of Rhodiola samples using an HPLC-DAD/UV method. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to compare the two classification methods between genetic and phytochemical taxonomy. The established chemotaxonomic classification could be effectively used for Rhodiola species identification.

The chemotaxonomic classification of Rhodiola plants and its correlation with morphological characteristics and genetic taxonomy

PubMed Central

2013-01-01

Background Rhodiola plants are used as a natural remedy in the western world and as a traditional herbal medicine in China, and are valued for their ability to enhance human resistance to stress or fatigue and to promote longevity. Due to the morphological similarities among different species, the identification of the genus remains somewhat controversial, which may affect their safety and effectiveness in clinical use. Results In this paper, 47 Rhodiola samples of seven species were collected from thirteen local provinces of China. They were identified by their morphological characteristics and genetic and phytochemical taxonomies. Eight bioactive chemotaxonomic markers from four chemical classes (phenylpropanoids, phenylethanol derivatives, flavonoids and phenolic acids) were determined to evaluate and distinguish the chemotaxonomy of Rhodiola samples using an HPLC-DAD/UV method. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to compare the two classification methods between genetic and phytochemical taxonomy. Conclusions The established chemotaxonomic classification could be effectively used for Rhodiola species identification. PMID:23844866

Enhancing and Archiving the APS Catalog of the POSS I

NASA Technical Reports Server (NTRS)

Humphreys, Roberta M.

2003-01-01

We have worked on two different projects: 1) Archiving the APS Catalog of the POSS I for distribution to NASA's NED at IPAC, SIMBAD in France, and individual astronomers and 2) The automated morphological classification of galaxies. We have completed archiving the Catalog into easily readable binary files. The database together with the software to read it has been distributed on DVD's to the national and international data centers and to individual astronomers. The archived Catalog contains more than 89 million objects in 632 fields in the first epoch Palomar Observatory Sky Survey. Additional image parameters not available in the original on-line version are also included in the archived version. The archived Catalog is also available and can be queried at the APS web site (URL: http://aps.umn.edu) which has been improved with a much faster and more efficient querying system. The Catalog can be downloaded as binary datafiles with the source code for reading it. It is also being integrated into the SkyQuery system which includes the Sloan Digital Sky Survey, 2MASS, and the FIRST radio sky survey. We experimented with different classification algorithms to automate the morphological classification of galaxies. This is an especially difficult problem because there are not only a large number of attributes or parameters and measurement uncertainties, but also the added complication of human disagreement about the adopted types. To solve this problem we used 837 galaxy images from nine POSS I fields at the North Galactic Pole classified by two independent astronomers for which they agree on the morphological types. The initial goal was to separate the galaxies into the three broad classes relevant to issues of large scale structure and galaxy formation and evolution: early (ellipticals and lenticulars), spirals, and late (irregulars) with an accuracy or success rate that rivals the best astronomer classifiers. We also needed to identify a set of parameters derived from the digitized images that separate the galaxies by type. The human eye can easily recognize complicated patterns in images such as spiral arms which can be spotty, blotchy affairs that are difficult for automated techniques. A galaxy image can potentially be described by hundreds of parameters, all of which may have some relation to the morphological type. In the set of initial experiments we used 624 such parameters, in two colors, blue and red. These parameters include the surface brightness and color measured at different radii, ratios of these parameters at different radii, concentration indices, Fourier transforms and wavelet decomposition coefficients. We experimented with three different classes of classification algorithms; decision trees, k-nearest neighbors, and support vector machines (SVM). A range of experiments were conducted and we eventually narrowed the parameters to 23 selected parameters. SVM consistently outperformed the other algorithms with both sets of features. By combining the results from the different algorithms in a weighted scheme we achieved an overall classification success of 86%.

Recognition and classification of colon cells applying the ensemble of classifiers.

PubMed

Kruk, M; Osowski, S; Koktysz, R

2009-02-01

The paper presents the application of an ensemble of classifiers for the recognition of colon cells on the basis of the microscope colon image. The solved task include: segmentation of the individual cells from the image using the morphological operations, the preprocessing stages, leading to the extraction of features, selection of the most important features, and the classification stage applying the classifiers arranged in the form of ensemble. The paper presents and discusses the results concerning the recognition of four most important colon cell types: eosinophylic granulocyte, neutrophilic granulocyte, lymphocyte and plasmocyte. The proposed system is able to recognize the cells with the accuracy comparable to the human expert (around 5% of discrepancy of both results).

Classification of Magnetic Nanoparticle Systems—Synthesis, Standardization and Analysis Methods in the NanoMag Project

PubMed Central

Bogren, Sara; Fornara, Andrea; Ludwig, Frank; del Puerto Morales, Maria; Steinhoff, Uwe; Fougt Hansen, Mikkel; Kazakova, Olga; Johansson, Christer

2015-01-01

This study presents classification of different magnetic single- and multi-core particle systems using their measured dynamic magnetic properties together with their nanocrystal and particle sizes. The dynamic magnetic properties are measured with AC (dynamical) susceptometry and magnetorelaxometry and the size parameters are determined from electron microscopy and dynamic light scattering. Using these methods, we also show that the nanocrystal size and particle morphology determines the dynamic magnetic properties for both single- and multi-core particles. The presented results are obtained from the four year EU NMP FP7 project, NanoMag, which is focused on standardization of analysis methods for magnetic nanoparticles. PMID:26343639

Automated artery-venous classification of retinal blood vessels based on structural mapping method

NASA Astrophysics Data System (ADS)

Joshi, Vinayak S.; Garvin, Mona K.; Reinhardt, Joseph M.; Abramoff, Michael D.

2012-03-01

Retinal blood vessels show morphologic modifications in response to various retinopathies. However, the specific responses exhibited by arteries and veins may provide a precise diagnostic information, i.e., a diabetic retinopathy may be detected more accurately with the venous dilatation instead of average vessel dilatation. In order to analyze the vessel type specific morphologic modifications, the classification of a vessel network into arteries and veins is required. We previously described a method for identification and separation of retinal vessel trees; i.e. structural mapping. Therefore, we propose the artery-venous classification based on structural mapping and identification of color properties prominent to the vessel types. The mean and standard deviation of each of green channel intensity and hue channel intensity are analyzed in a region of interest around each centerline pixel of a vessel. Using the vector of color properties extracted from each centerline pixel, it is classified into one of the two clusters (artery and vein), obtained by the fuzzy-C-means clustering. According to the proportion of clustered centerline pixels in a particular vessel, and utilizing the artery-venous crossing property of retinal vessels, each vessel is assigned a label of an artery or a vein. The classification results are compared with the manually annotated ground truth (gold standard). We applied the proposed method to a dataset of 15 retinal color fundus images resulting in an accuracy of 88.28% correctly classified vessel pixels. The automated classification results match well with the gold standard suggesting its potential in artery-venous classification and the respective morphology analysis.

Classification of self-assembling protein nanoparticle architectures for applications in vaccine design

NASA Astrophysics Data System (ADS)

Indelicato, G.; Burkhard, P.; Twarock, R.

2017-04-01

We introduce here a mathematical procedure for the structural classification of a specific class of self-assembling protein nanoparticles (SAPNs) that are used as a platform for repetitive antigen display systems. These SAPNs have distinctive geometries as a consequence of the fact that their peptide building blocks are formed from two linked coiled coils that are designed to assemble into trimeric and pentameric clusters. This allows a mathematical description of particle architectures in terms of bipartite (3,5)-regular graphs. Exploiting the relation with fullerene graphs, we provide a complete atlas of SAPN morphologies. The classification enables a detailed understanding of the spectrum of possible particle geometries that can arise in the self-assembly process. Moreover, it provides a toolkit for a systematic exploitation of SAPNs in bioengineering in the context of vaccine design, predicting the density of B-cell epitopes on the SAPN surface, which is critical for a strong humoral immune response.

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

NASA Astrophysics Data System (ADS)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

Automated classification of cell morphology by coherence-controlled holographic microscopy

NASA Astrophysics Data System (ADS)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

Automated classification of cell morphology by coherence-controlled holographic microscopy.

PubMed

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

[LiLa classification for paediatric long bone fractures. Intraobserver and interobserver reliability].

PubMed

Kamphaus, A; Rapp, M; Wessel, L M; Buchholz, M; Massalme, E; Schneidmüller, D; Roeder, C; Kaiser, M M

2015-04-01

There are two child-specific fracture classification systems for long bone fractures: the AO classification of pediatric long-bone fractures (PCCF) and the LiLa classification of pediatric fractures of long bones (LiLa classification). Both are still not widely established in comparison to the adult AO classification for long bone fractures. During a period of 12 months all long bone fractures in children were documented and classified according to the LiLa classification by experts and non-experts. Intraobserver and interobserver reliability were calculated according to Cohen (kappa). A total of 408 fractures were classified. The intraobserver reliability for location in the skeletal and bone segment showed an almost perfect agreement (K = 0.91-0.95) and also the morphology (joint/shaft fracture) (K = 0.87-0.93). Due to different judgment of the fracture displacement in the second classification round, the intraobserver reliability of the whole classification revealed moderate agreement (K = 0.53-0.58). Interobserver reliability showed moderate agreement (K = 0.55) often due to the low quality of the X-rays. Further differences occurred due to difficulties in assigning the precise transition from metaphysis to diaphysis. The LiLa classification is suitable and in most cases user-friendly for classifying long bone fractures in children. Reliability is higher than in established fracture specific classifications and comparable to the AO classification of pediatric long bone fractures. Some mistakes were due to a low quality of the X-rays and some due to difficulties to classify the fractures themselves. Improvements include a more precise definition of the metaphysis and the kind of displacement. Overall the LiLa classification should still be considered as an alternative for classifying pediatric long bone fractures.

A new classification scheme of plastic wastes based upon recycling labels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Özkan, Kemal, E-mail: kozkan@ogu.edu.tr; Ergin, Semih, E-mail: sergin@ogu.edu.tr; Işık, Şahin, E-mail: sahini@ogu.edu.tr

Highlights: • PET, HPDE or PP types of plastics are considered. • An automated classification of plastic bottles based on the feature extraction and classification methods is performed. • The decision mechanism consists of PCA, Kernel PCA, FLDA, SVD and Laplacian Eigenmaps methods. • SVM is selected to achieve the classification task and majority voting technique is used. - Abstract: Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize thesemore » materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher’s Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP.« less

Galactic rings revisited - I. CVRHS classifications of 3962 ringed galaxies from the Galaxy Zoo 2 Database

NASA Astrophysics Data System (ADS)

Buta, Ronald J.

2017-11-01

Rings are important and characteristic features of disc-shaped galaxies. This paper is the first in a series that re-visits galactic rings with the goals of further understanding the nature of the features and for examining their role in the secular evolution of galaxy structure. The series begins with a new sample of 3962 galaxies drawn from the Galaxy Zoo 2 citizen science data base, selected because zoo volunteers recognized a ring-shaped pattern in the morphology as seen in Sloan Digital Sky Survey colour images. The galaxies are classified within the framework of the Comprehensive de Vaucouleurs revised Hubble-Sandage system. It is found that zoo volunteers cued on the same kinds of ring-like features that were recognized in the 1995 Catalogue of Southern Ringed Galaxies. This paper presents the full catalogue of morphological classifications, comparisons with other sources of classifications and some histograms designed mainly to highlight the content of the catalogue. The advantages of the sample are its large size and the generally good quality of the images; the main disadvantage is the low physical resolution that limits the detectability of linearly small rings such as nuclear rings. The catalogue includes mainly inner and outer disc rings and lenses. Cataclysmic (`encounter-driven') rings (such as ring and polar ring galaxies) are recognized in less than 1 per cent of the sample.

Classification of grass pollen through the quantitative analysis of surface ornamentation and texture.

PubMed

Mander, Luke; Li, Mao; Mio, Washington; Fowlkes, Charless C; Punyasena, Surangi W

2013-11-07

Taxonomic identification of pollen and spores uses inherently qualitative descriptions of morphology. Consequently, identifications are restricted to categories that can be reliably classified by multiple analysts, resulting in the coarse taxonomic resolution of the pollen and spore record. Grass pollen represents an archetypal example; it is not routinely identified below family level. To address this issue, we developed quantitative morphometric methods to characterize surface ornamentation and classify grass pollen grains. This produces a means of quantifying morphological features that are traditionally described qualitatively. We used scanning electron microscopy to image 240 specimens of pollen from 12 species within the grass family (Poaceae). We classified these species by developing algorithmic features that quantify the size and density of sculptural elements on the pollen surface, and measure the complexity of the ornamentation they form. These features yielded a classification accuracy of 77.5%. In comparison, a texture descriptor based on modelling the statistical distribution of brightness values in image patches yielded a classification accuracy of 85.8%, and seven human subjects achieved accuracies between 68.33 and 81.67%. The algorithmic features we developed directly relate to biologically meaningful features of grass pollen morphology, and could facilitate direct interpretation of unsupervised classification results from fossil material.

How well do the rosgen classification and associated "natural channel design" methods integrate and quantify fluvial processes and channel response?

USGS Publications Warehouse

Simon, A.; Doyle, M.; Kondolf, M.; Shields, F.D.; Rhoads, B.; Grant, G.; Fitzpatrick, F.; Juracek, K.; McPhillips, M.; MacBroom, J.

2005-01-01

Over the past 10 years the Rosgen classification system and its associated methods of "natural channel design" have become synonymous (to many without prior knowledge of the field) with the term "stream restoration" and the science of fluvial geomorphology. Since the mid 1990s, this classification approach has become widely, and perhaps dominantly adopted by governmental agencies, particularly those funding restoration projects. For example, in a request for proposals for the restoration of Trout Creek in Montana, the Natural Resources Conservation Service required "experience in the use and application of a stream classification system and its implementation." Similarly, classification systems have been used in evaluation guides for riparian areas and U.S. Forest Service management plans. Most notably, many highly trained geomorphologists and hydraulic engineers are often held suspect, or even thought incorrect, if their approach does not include reference to or application of a classification system. This, combined with the para-professional training provided by some involved in "natural channel design" empower individuals and groups with limited backgrounds in stream and watershed sciences to engineer wholesale re-patterning of stream reaches using 50-year old technology that was never intended for engineering design. At Level I, the Rosgen classification system consists of eight or nine major stream types, based on hydraulic-geometry relations and four other measures of channel shape to distinguish the dimensions of alluvial stream channels as a function of the bankfull stage. Six classes of the particle size of the boundary sediments are used to further sub-divide each of the major stream types, resulting in 48 or 54 stream types. Aside from the difficulty in identifying bankfull stage, particularly in incising channels, and the issue of sampling from two distinct populations (beds and banks) to classify the boundary sediments, the classification provides a consistent and reproducible means for practitioners to describe channel morphology although difficulties have been encountered in lower-gradient stream systems. Use of the scheme to communicate between users or as a conceptual model, however, has not justified its use for engineering design or for predicting river behavior; its use for designing mitigation projects, therefore, seems beyond its technical scope. Copyright ASCE 2005.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries.

PubMed

Peres, Marines Bertolo; Silveira, Landulfo; Zângaro, Renato Amaro; Pacheco, Marcos Tadeu Tavares; Pasqualucci, Carlos Augusto

2011-09-01

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Classification of male lower torso for underwear design

NASA Astrophysics Data System (ADS)

Cheng, Z.; Kuzmichev, V. E.

2017-10-01

By means of scanning technology we have got new information about the morphology of male bodies and have redistricted the classification of men’s underwear by adopting one to consumer demands. To build the new classification in accordance with male body characteristic factors of lower torso, we make the method of underwear designing which allow to get the accurate and convenience for consumers products.

Examining the effectiveness of discriminant function analysis and cluster analysis in species identification of male field crickets based on their calling songs.

PubMed

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

Physiological and morphological characterization of ganglion cells in the salamander retina

PubMed Central

Wang, Jing; Jacoby, Roy; Wu, Samuel M.

2016-01-01

Retinal ganglion cells (RGCs) integrate visual information from the retina and transmit collective signals to the brain. A systematic investigation of functional and morphological characteristics of various types of RGCs is important to comprehensively understand how the visual system encodes and transmits information via various RGC pathways. This study evaluated both physiological and morphological properties of 67 RGCs in dark-adapted flat-mounted salamander retina by examining light-evoked cation and chloride current responses via voltage-clamp recordings and visualizing morphology by Lucifer yellow fluorescence with a confocal microscope. Six groups of RGCs were described: asymmetrical ON–OFF RGCs, symmetrical ON RGCs, OFF RGCs, and narrow-, medium- and wide-field ON–OFF RGCs. Dendritic field diameters of RGCs ranged 102–490 µm: narrow field (<200 µm, 31% of RGCs), medium field (200–300 µm, 45%) and wide field (>300 µm, 24%). Dendritic ramification patterns of RGCs agree with the sub-lamina A/B rule. 34% of RGCs were monostratified, 24% bistratified and 42% diffusely stratified. 70% of ON RGCs and OFF RGCs were monostratified. Wide-field RGCs were diffusely stratified. 82% of RGCs generated light-evoked ON–OFF responses, while 11% generated ON responses and 7% OFF responses. Response sensitivity analysis suggested that some RGCs obtained separated rod/cone bipolar cell inputs whereas others obtained mixed bipolar cell inputs. 25% of neurons in the RGC layer were displaced amacrine cells. Although more types may be defined by more refined classification criteria, this report is to incorporate more physiological properties into RGC classification. PMID:26731645

Electrocardiogram ST-Segment Morphology Delineation Method Using Orthogonal Transformations

PubMed Central

2016-01-01

Differentiation between ischaemic and non-ischaemic transient ST segment events of long term ambulatory electrocardiograms is a persisting weakness in present ischaemia detection systems. Traditional ST segment level measuring is not a sufficiently precise technique due to the single point of measurement and severe noise which is often present. We developed a robust noise resistant orthogonal-transformation based delineation method, which allows tracing the shape of transient ST segment morphology changes from the entire ST segment in terms of diagnostic and morphologic feature-vector time series, and also allows further analysis. For these purposes, we developed a new Legendre Polynomials based Transformation (LPT) of ST segment. Its basis functions have similar shapes to typical transient changes of ST segment morphology categories during myocardial ischaemia (level, slope and scooping), thus providing direct insight into the types of time domain morphology changes through the LPT feature-vector space. We also generated new Karhunen and Lo ève Transformation (KLT) ST segment basis functions using a robust covariance matrix constructed from the ST segment pattern vectors derived from the Long Term ST Database (LTST DB). As for the delineation of significant transient ischaemic and non-ischaemic ST segment episodes, we present a study on the representation of transient ST segment morphology categories, and an evaluation study on the classification power of the KLT- and LPT-based feature vectors to classify between ischaemic and non-ischaemic ST segment episodes of the LTST DB. Classification accuracy using the KLT and LPT feature vectors was 90% and 82%, respectively, when using the k-Nearest Neighbors (k = 3) classifier and 10-fold cross-validation. New sets of feature-vector time series for both transformations were derived for the records of the LTST DB which is freely available on the PhysioNet website and were contributed to the LTST DB. The KLT and LPT present new possibilities for human-expert diagnostics, and for automated ischaemia detection. PMID:26863140

Phylogenetic versus functional signals in the evolution of form-function relationships in terrestrial vision.

PubMed

Motani, Ryosuke; Schmitz, Lars

2011-08-01

Phylogeny is deeply pertinent to evolutionary studies. Traits that perform a body function are expected to be strongly influenced by physical "requirements" of the function. We investigated if such traits exhibit phylogenetic signals, and, if so, how phylogenetic noises bias quantification of form-function relationships. A form-function system that is strongly influenced by physics, namely the relationship between eye morphology and visual optics in amniotes, was used. We quantified the correlation between form (i.e., eye morphology) and function (i.e., ocular optics) while varying the level of phylogenetic bias removal through adjusting Pagel's λ. Ocular soft-tissue dimensions exhibited the highest correlation with ocular optics when 1% of phylogenetic bias expected from Brownian motion was removed (i.e., λ= 0.01); the value for hard-tissue data were 8%. A small degree of phylogenetic bias therefore exists in morphology despite of the stringent functional constraints. We also devised a phylogenetically informed discriminant analysis and recorded the effects of phylogenetic bias on this method using the same data. Use of proper λ values during phylogenetic bias removal improved misidentification rates in resulting classifications when prior probabilities were assumed to be equal. Even a small degree of phylogenetic bias affected the classification resulting from phylogenetically informed discriminant analysis. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Integrating image processing and classification technology into automated polarizing film defect inspection

NASA Astrophysics Data System (ADS)

Kuo, Chung-Feng Jeffrey; Lai, Chun-Yu; Kao, Chih-Hsiang; Chiu, Chin-Hsun

2018-05-01

In order to improve the current manual inspection and classification process for polarizing film on production lines, this study proposes a high precision automated inspection and classification system for polarizing film, which is used for recognition and classification of four common defects: dent, foreign material, bright spot, and scratch. First, the median filter is used to remove the impulse noise in the defect image of polarizing film. The random noise in the background is smoothed by the improved anisotropic diffusion, while the edge detail of the defect region is sharpened. Next, the defect image is transformed by Fourier transform to the frequency domain, combined with a Butterworth high pass filter to sharpen the edge detail of the defect region, and brought back by inverse Fourier transform to the spatial domain to complete the image enhancement process. For image segmentation, the edge of the defect region is found by Canny edge detector, and then the complete defect region is obtained by two-stage morphology processing. For defect classification, the feature values, including maximum gray level, eccentricity, the contrast, and homogeneity of gray level co-occurrence matrix (GLCM) extracted from the images, are used as the input of the radial basis function neural network (RBFNN) and back-propagation neural network (BPNN) classifier, 96 defect images are then used as training samples, and 84 defect images are used as testing samples to validate the classification effect. The result shows that the classification accuracy by using RBFNN is 98.9%. Thus, our proposed system can be used by manufacturing companies for a higher yield rate and lower cost. The processing time of one single image is 2.57 seconds, thus meeting the practical application requirement of an industrial production line.

Molecular Phylogeny of the Widely Distributed Marine Protists, Phaeodaria (Rhizaria, Cercozoa).

PubMed

Nakamura, Yasuhide; Imai, Ichiro; Yamaguchi, Atsushi; Tuji, Akihiro; Not, Fabrice; Suzuki, Noritoshi

2015-07-01

Phaeodarians are a group of widely distributed marine cercozoans. These plankton organisms can exhibit a large biomass in the environment and are supposed to play an important role in marine ecosystems and in material cycles in the ocean. Accurate knowledge of phaeodarian classification is thus necessary to better understand marine biology, however, phylogenetic information on Phaeodaria is limited. The present study analyzed 18S rDNA sequences encompassing all existing phaeodarian orders, to clarify their phylogenetic relationships and improve their taxonomic classification. The monophyly of Phaeodaria was confirmed and strongly supported by phylogenetic analysis with a larger data set than in previous studies. The phaeodarian clade contained 11 subclades which generally did not correspond to the families and orders of the current classification system. Two families (Challengeriidae and Aulosphaeridae) and two orders (Phaeogromida and Phaeocalpida) are possibly polyphyletic or paraphyletic, and consequently the classification needs to be revised at both the family and order levels by integrative taxonomy approaches. Two morphological criteria, 1) the scleracoma type and 2) its surface structure, could be useful markers at the family level. Copyright © 2015 Elsevier GmbH. All rights reserved.

Detection and classification of interstitial lung diseases and emphysema using a joint morphological-fuzzy approach

NASA Astrophysics Data System (ADS)

Chang Chien, Kuang-Che; Fetita, Catalin; Brillet, Pierre-Yves; Prêteux, Françoise; Chang, Ruey-Feng

2009-02-01

Multi-detector computed tomography (MDCT) has high accuracy and specificity on volumetrically capturing serial images of the lung. It increases the capability of computerized classification for lung tissue in medical research. This paper proposes a three-dimensional (3D) automated approach based on mathematical morphology and fuzzy logic for quantifying and classifying interstitial lung diseases (ILDs) and emphysema. The proposed methodology is composed of several stages: (1) an image multi-resolution decomposition scheme based on a 3D morphological filter is used to detect and analyze the different density patterns of the lung texture. Then, (2) for each pattern in the multi-resolution decomposition, six features are computed, for which fuzzy membership functions define a probability of association with a pathology class. Finally, (3) for each pathology class, the probabilities are combined up according to the weight assigned to each membership function and two threshold values are used to decide the final class of the pattern. The proposed approach was tested on 10 MDCT cases and the classification accuracy was: emphysema: 95%, fibrosis/honeycombing: 84% and ground glass: 97%.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

PubMed

Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

PubMed Central

Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

Classifying Structures in the ISM with Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Beaumont, Christopher; Goodman, A. A.; Williams, J. P.

2011-01-01

The processes which govern molecular cloud evolution and star formation often sculpt structures in the ISM: filaments, pillars, shells, outflows, etc. Because of their morphological complexity, these objects are often identified manually. Manual classification has several disadvantages; the process is subjective, not easily reproducible, and does not scale well to handle increasingly large datasets. We have explored to what extent machine learning algorithms can be trained to autonomously identify specific morphological features in molecular cloud datasets. We show that the Support Vector Machine algorithm can successfully locate filaments and outflows blended with other emission structures. When the objects of interest are morphologically distinct from the surrounding emission, this autonomous classification achieves >90% accuracy. We have developed a set of IDL-based tools to apply this technique to other datasets.

Comments on the 2001 WHO proposal for the classification of haematopoietic neoplasms.

PubMed

Paietta, Elisabeth

2003-12-01

In the preface, the World Health Organization (WHO) classification vows to offer pathologists, oncologists and geneticists worldwide a system of classification for human neoplasms based on histopathological and genetic features. Standardization of nomenclature and agreed-upon criteria for definition of the various types of cancer are felt to be a prerequisite for progress in clinical oncology, multicentre therapy trials and comparative studies in different countries. In fact, the WHO effort represents the first worldwide comprehensive consensus classification of the haematological malignancies. Consensus was reached among a subgroup of investigators, carefully selected for their experience and contributions to existing classifications. In the present climate of daily new discoveries that yield a constant stream of fascinating insights into the biology of leukaemias and lymphomas and, above all, resulting in an explosion of potential therapeutic targets, the WHO system has taken the stand of compiling established classification approaches and providing order to known facts. This furnishes an essential skeleton upon which to build in the future. The WHO committee decided that sorting neoplasms according to prognosis was neither practical nor necessary and could be misleading. While justifiable at the present time, it is important to realize that the classifications of the haematological malignancies are a moving target and that the trend is to move away from currently accepted gold standards, such as morphological evaluations, in favour of genetic characterizations, especially those with therapeutic relevance. The goal of this chapter is to fill in some gaps that, as per the author's opinion, exist in the WHO classification, predominantly, where it concerns the role of immunophenotyping as a complementary discipline for genotyping through its potential to generate surrogate marker profiles for molecular lesions. By introducing some state-of-the-art classification modalities, some of which are still awaiting confirmation, this chapter also aims to spark excitement and provide a glimpse at the future.

Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

PubMed

Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

2016-01-01

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

[Achene morphology cluster analysis of Taraxacum F. H. Wigg. from northeast China and molecule systematics evidence determined by SRAP].

PubMed

Li, Hai-juan; Zhao, Xin; Jia, Qing-fei; Li, Tian-lai; Ning, Wei

2012-08-01

The achenes morphological and micro-morphological characteristics of six species of genus Taraxacum from northeastern China as well as SRAP cluster analysis were observed for their classification evidences. The achenes were observed by microscope and EPMA. Cluster analysis was given on the basis of the size, shape, cone proportion, color and surface sculpture of achenes. The Taraxacum inter-species achene shape characteristic difference is obvious, particularly spinulose distribution and size, achene color and achene size; with the Taraxacum plant achene shape the cluster method T. antungense Kitag. and the T. urbanum Kitag. should combine for the identical kind; the achene morphology cluster analysis and the SRAP tagged molecule systematics's cluster result retrieves in the table with "the Chinese flora". The class group to divide the result is consistent. Taraxacum plant achene shape characteristic stable conservative, may carry on the inter-species division and the sibship analysis according to the achene shape characteristic combination difference; the achene morphology cluster analysis as well as the SRAP tagged molecule systematics confirmation support dandelion classification result of "the Chinese flora".

A new classification scheme of plastic wastes based upon recycling labels.

PubMed

Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, Idil

2015-01-01

Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher's Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP. Copyright © 2014 Elsevier Ltd. All rights reserved.

Describing Peripancreatic Collections According to the Revised Atlanta Classification of Acute Pancreatitis: An International Interobserver Agreement Study.

PubMed

Bouwense, Stefan A; van Brunschot, Sandra; van Santvoort, Hjalmar C; Besselink, Marc G; Bollen, Thomas L; Bakker, Olaf J; Banks, Peter A; Boermeester, Marja A; Cappendijk, Vincent C; Carter, Ross; Charnley, Richard; van Eijck, Casper H; Freeny, Patrick C; Hermans, John J; Hough, David M; Johnson, Colin D; Laméris, Johan S; Lerch, Markus M; Mayerle, Julia; Mortele, Koenraad J; Sarr, Michael G; Stedman, Brian; Vege, Santhi Swaroop; Werner, Jens; Dijkgraaf, Marcel G; Gooszen, Hein G; Horvath, Karen D

2017-08-01

Severe acute pancreatitis is associated with peripancreatic morphologic changes as seen on imaging. Uniform communication regarding these morphologic findings is crucial for accurate diagnosis and treatment. For the original 1992 Atlanta classification, interobserver agreement is poor. We hypothesized that for the revised Atlanta classification, interobserver agreement will be better. An international, interobserver agreement study was performed among expert and nonexpert radiologists (n = 14), surgeons (n = 15), and gastroenterologists (n = 8). Representative computed tomographies of all stages of acute pancreatitis were selected from 55 patients and were assessed according to the revised Atlanta classification. The interobserver agreement was calculated among all reviewers and subgroups, that is, expert and nonexpert reviewers; interobserver agreement was defined as poor (≤0.20), fair (0.21-0.40), moderate (0.41-0.60), good (0.61-0.80), or very good (0.81-1.00). Interobserver agreement among all reviewers was good (0.75 [standard deviation, 0.21]) for describing the type of acute pancreatitis and good (0.62 [standard deviation, 0.19]) for the type of peripancreatic collection. Expert radiologists showed the best and nonexpert clinicians the lowest interobserver agreement. Interobserver agreement was good for the revised Atlanta classification, supporting the importance for widespread adaption of this revised classification for clinical and research communications.

Automated Morphological Classification in Deep Hubble Space Telescope UBVI Fields: Rapidly and Passively Evolving Faint Galaxy Populations

NASA Astrophysics Data System (ADS)

Odewahn, Stephen C.; Windhorst, Rogier A.; Driver, Simon P.; Keel, William C.

1996-11-01

We analyze deep Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) images in U, B, V, I using artificial neural network (ANN) classifiers, which are based on galaxy surface brightness and light profile (but not on color nor on scale length, rhl). The ANN distinguishes quite well between E/S0, Sabc, and Sd/Irr+M galaxies (M for merging systems) for BJ <~ 27 mag. We discuss effects from the cosmological surface brightness (SB) dimming and from the redshifted UV morphology on the classifications, and we correct for the latter. We present classifications in UBVI from (a) four independent human classifiers; (b) ANNs trained on V606 and I814 images; and (c) an ANN trained on images in the rest-frame UBV according to the expected redshift distribution as a function of BJ. For each of the three methods, we find that the fraction of galaxy types does not depend significantly on wavelength, and that they produce consistent counts as a function of type. The median scale length at BJ ~= 27 mag is rhl ~= 0."25--0."3 (1--2 kpc at z ~ 1--2). Early- and late-type galaxies are fairly well separated in BVI color-magnitude diagrams for B <~ 27 mag, with E/S0 galaxies being the reddest and Sd/Irr+M galaxies generally blue. We present the B-band galaxy counts for five WFPC2 fields as a function of morphological type for BJ <~ 27 mag. E/S0 galaxies are only marginally above the no-evolution predictions, and Sabc galaxies are at most 0.5 dex above the nonevolving models for BJ >~ 24 mag. The faint blue galaxy counts in the B band are dominated by Sd/Irr+M galaxies and can be explained by a moderately steep local luminosity function (LF) undergoing strong luminosity evolution. We suggest that these faint late-type objects (24 mag <~ BJ <~ 28 mag) are a combination of low-luminosity lower redshift dwarf galaxies, plus compact star-forming galaxies and merging systems at z ~= 1--3, possibly the building blocks of the luminous early-type galaxies seen today.

Molecular phylogeny of Gymnocalycium (Cactaceae): assessment of alternative infrageneric systems, a new subgenus, and trends in the evolution of the genus.

PubMed

Demaio, Pablo H; Barfuss, Michael H J; Kiesling, Roberto; Till, Walter; Chiapella, Jorge O

2011-11-01

The South American genus Gymnocalycium (Cactoideae-Trichocereae) demonstrates how the sole use of morphological data in Cactaceae results in conflicts in assessing phylogeny, constructing a taxonomic system, and analyzing trends in the evolution of the genus. Molecular phylogenetic analysis was performed using parsimony and Bayesian methods on a 6195-bp data matrix of plastid DNA sequences (atpI-atpH, petL-psbE, trnK-matK, trnT-trnL-trnF) of 78 samples, including 52 species and infraspecific taxa representing all the subgenera of Gymnocalycium. We assessed morphological character evolution using likelihood methods to optimize characters on a Bayesian tree and to reconstruct possible ancestral states. The results of the phylogenetic study confirm the monophyly of the genus, while supporting overall the available infrageneric classification based on seed morphology. Analysis showed the subgenera Microsemineum and Macrosemineum to be polyphyletic and paraphyletic. Analysis of morphological characters showed a tendency toward reduction of stem size, reduction in quantity and hardiness of spines, increment of seed size, development of napiform roots, and change from juicy and colorful fruits to dry and green fruits. Gymnocalycium saglionis is the only species of Microsemineum and a new name is required to identify the clade including the remaining species of Microsemineum; we propose the name Scabrosemineum in agreement with seed morphology. Identifying morphological trends and environmental features allows for a better understanding of the events that might have influenced the diversification of the genus.

Molecular phylogeny and biogeography of the fern genus Pteris (Pteridaceae).

PubMed

Chao, Yi-Shan; Rouhan, Germinal; Amoroso, Victor B; Chiou, Wen-Liang

2014-07-01

Pteris (Pteridaceae), comprising over 250 species, had been thought to be a monophyletic genus until the three monotypic genera Neurocallis, Ochropteris and Platyzoma were included. However, the relationships between the type species of the genus Pteris, P. longifolia, and other species are still unknown. Furthermore, several infrageneric morphological classifications have been proposed, but are debated. To date, no worldwide phylogenetic hypothesis has been proposed for the genus, and no comprehensive biogeographical history of Pteris, crucial to understanding its cosmopolitan distribution, has been presented. A molecular phylogeny of Pteris is presented for 135 species, based on cpDNA rbcL and matK and using maximum parsimony, maximum likelihood and Bayesian inference approaches. The inferred phylogeny was used to assess the biogeographical history of Pteris and to reconstruct the evolution of one ecological and four morphological characters commonly used for infrageneric classifications. The monophyly of Pteris remains uncertain, especially regarding the relationship of Pteris with Actiniopteris + Onychium and Platyzoma. Pteris comprises 11 clades supported by combinations of ecological and morphological character states, but none of the characters used in previous classifications were found to be exclusive synapomorphies. The results indicate that Pteris diversified around 47 million years ago, and when species colonized new geographical areas they generated new lineages, which are associated with morphological character transitions. This first phylogeny of Pteris on a global scale and including more than half of the diversity of the genus should contribute to a new, more reliable infrageneric classification of Pteris, based not only on a few morphological characters but also on ecological traits and geographical distribution. The inferred biogeographical history highlights long-distance dispersal as a major process shaping the worldwide distribution of the species. Colonization of different niches was followed by subsequent morphological diversification. Dispersal events followed by allopatric and parapatric speciation contribute to the species diversity of Pteris. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Human red blood cell recognition enhancement with three-dimensional morphological features obtained by digital holographic imaging

NASA Astrophysics Data System (ADS)

Jaferzadeh, Keyvan; Moon, Inkyu

2016-12-01

The classification of erythrocytes plays an important role in the field of hematological diagnosis, specifically blood disorders. Since the biconcave shape of red blood cell (RBC) is altered during the different stages of hematological disorders, we believe that the three-dimensional (3-D) morphological features of erythrocyte provide better classification results than conventional two-dimensional (2-D) features. Therefore, we introduce a set of 3-D features related to the morphological and chemical properties of RBC profile and try to evaluate the discrimination power of these features against 2-D features with a neural network classifier. The 3-D features include erythrocyte surface area, volume, average cell thickness, sphericity index, sphericity coefficient and functionality factor, MCH and MCHSD, and two newly introduced features extracted from the ring section of RBC at the single-cell level. In contrast, the 2-D features are RBC projected surface area, perimeter, radius, elongation, and projected surface area to perimeter ratio. All features are obtained from images visualized by off-axis digital holographic microscopy with a numerical reconstruction algorithm, and four categories of biconcave (doughnut shape), flat-disc, stomatocyte, and echinospherocyte RBCs are interested. Our experimental results demonstrate that the 3-D features can be more useful in RBC classification than the 2-D features. Finally, we choose the best feature set of the 2-D and 3-D features by sequential forward feature selection technique, which yields better discrimination results. We believe that the final feature set evaluated with a neural network classification strategy can improve the RBC classification accuracy.

Attribution of local climate zones using a multitemporal land use/land cover classification scheme

NASA Astrophysics Data System (ADS)

Wicki, Andreas; Parlow, Eberhard

2017-04-01

Worldwide, the number of people living in an urban environment exceeds the rural population with increasing tendency. Especially in relation to global climate change, cities play a major role considering the impacts of extreme heat waves on the population. For urban planners, it is important to know which types of urban structures are beneficial for a comfortable urban climate and which actions can be taken to improve urban climate conditions. Therefore, it is essential to differ between not only urban and rural environments, but also between different levels of urban densification. To compare these built-up types within different cities worldwide, Stewart and Oke developed the concept of local climate zones (LCZ) defined by morphological characteristics. The original LCZ scheme often has considerable problems when adapted to European cities with historical city centers, including narrow streets and irregular patterns. In this study, a method to bridge the gap between a classical land use/land cover (LULC) classification and the LCZ scheme is presented. Multitemporal Landsat 8 data are used to create a high accuracy LULC map, which is linked to the LCZ by morphological parameters derived from a high-resolution digital surface model and cadastral data. A bijective combination of the different classification schemes could not be achieved completely due to overlapping threshold values and the spatially homogeneous distribution of morphological parameters, but the attribution of LCZ to the LULC classification was successful.

Micro-computed tomographic analysis of the root canal morphology of the distal root of mandibular first molar.

PubMed

Filpo-Perez, Carolina; Bramante, Clovis Monteiro; Villas-Boas, Marcelo Haas; Húngaro Duarte, Marco Antonio; Versiani, Marco Aurélio; Ordinola-Zapata, Ronald

2015-02-01

The aim of this study was to evaluate the morphologic aspects of the root canal anatomy of the distal root of a mandibular first molar using micro-computed tomographic analysis. One-hundred distal roots of mandibular first molars were scanned using a micro-computed tomographic device at an isotropic resolution of 19.6 μm. The percentage frequency distribution of the morphologic configuration of the root canal was performed according to the Vertucci classification system. Two-dimensional parameters (area, perimeter, roundness, aspect ratio, and major and minor diameters) and the cross-sectional shape of the root canal were analyzed in the apical third at every 1-mm interval from the main apical foramen in roots presenting Vertucci types I and II configurations (n = 79). Data were statistically compared using the Kruskal-Wallis and Dunn tests with a significance level set at 5%. Seventy-six percent of the distal roots had a single root canal. Two, three, and four canals were found in 13%, 8%, and 3% of the sample, respectively. In 13 specimens, the configuration of the root canal did not fit into Vertucci's classification. Overall, 2-dimensional parameter values significantly increased at the 3-mm level (P < .05). The prevalence of oval canals was higher at the 1-mm level and decreased at the 5-mm level in which long oval and flattened canals were more prevalent. The distal roots of the mandibular first molars showed a high prevalence of single root canals. The prevalence of long oval and flattened canals increased in the coronal direction. In 13% of the samples, canal configurations that were not included in Vertucci's configuration system were found. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

3D texture analysis for classification of second harmonic generation images of human ovarian cancer

NASA Astrophysics Data System (ADS)

Wen, Bruce; Campbell, Kirby R.; Tilbury, Karissa; Nadiarnykh, Oleg; Brewer, Molly A.; Patankar, Manish; Singh, Vikas; Eliceiri, Kevin. W.; Campagnola, Paul J.

2016-10-01

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83-91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Le Predicat Adjectif en Esperanto (The Predicate Adjective in Esperanto)

ERIC Educational Resources Information Center

Lo Jocomo, Francois

1977-01-01

A study of the predicate adjective in Esperanto based on the opposition established between the complementary classifications, monemes and words. Because morphological complications do not exist in Esperanto, study of the two classifications could proceed to the benefit of the study of other languages. (Text is in French.) (AMH)

Is geography an accurate predictor of evolutionary history in the millipede family Xystodesmidae?

PubMed Central

Marek, Paul E.

2017-01-01

For the past several centuries, millipede taxonomists have used the morphology of male copulatory structures (modified legs called gonopods), which are strongly variable and suggestive of species-level differences, as a source to understand taxon relationships. Millipedes in the family Xystodesmidae are blind, dispersal-limited and have narrow habitat requirements. Therefore, geographical proximity may instead be a better predictor of evolutionary relationship than morphology, especially since gonopodal anatomy is extremely divergent and similarities may be masked by evolutionary convergence. Here we provide a phylogenetics-based test of the power of morphological versus geographical character sets for resolving phylogenetic relationships in xystodesmid millipedes. Molecular data from 90 species-group taxa in the family were included in a six-gene phylogenetic analysis to provide the basis for comparing trees generated from these alternative character sets. The molecular phylogeny was compared to topologies representing three hypotheses: (1) a prior classification formulated using morphological and geographical data, (2) hierarchical groupings derived from Euclidean geographical distance, and (3) one based solely on morphological data. Euclidean geographical distance was not found to be a better predictor of evolutionary relationship than the prior classification, the latter of which was the most similar to the molecular topology. However, all three of the alternative topologies were highly divergent (Bayes factor >10) from the molecular topology, with the tree inferred exclusively from morphology being the most divergent. The results of this analysis show that a high degree of morphological convergence from substantial gonopod shape divergence generated spurious phylogenetic relationships. These results indicate the impact that a high degree of morphological homoplasy may have had on prior treatments of the family. Using the results of our phylogenetic analysis, we make several changes to the classification of the family, including transferring the rare state-threatened species Sigmoria whiteheadi Shelley, 1986 to the genus Apheloria Chamberlin, 1921—a relationship not readily apparent based on morphology alone. We show that while gonopod differences are a premier source of taxonomic characters to diagnose species pairwise, the traits should be viewed critically as taxonomic features uniting higher levels. PMID:29038750

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

PubMed

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis. Published by Elsevier Ltd.

Max-plus and min-plus projection autoassociative morphological memories and their compositions for pattern classification.

PubMed

Dos Santos, Alex Santana; Valle, Marcos Eduardo

2018-04-01

Autoassociative morphological memories (AMMs) are robust and computationally efficient memory models with unlimited storage capacity. In this paper, we present the max-plus and min-plus projection autoassociative morphological memories (PAMMs) as well as their compositions. Briefly, the max-plus PAMM yields the largest max-plus combination of the stored vectors which is less than or equal to the input. Dually, the vector recalled by the min-plus PAMM corresponds to the smallest min-plus combination which is larger than or equal to the input. Apart from unlimited absolute storage capacity and one step retrieval, PAMMs and their compositions exhibit an excellent noise tolerance. Furthermore, the new memories yielded quite promising results in classification problems with a large number of features and classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images

NASA Astrophysics Data System (ADS)

Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kusumoto, Masahiro; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2004-05-01

The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved: 1) to categorize the nodule database with respect to morphological and internal features, 2) to quickly search nodule images similar to an indeterminate nodule from a large database, and 3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule.

Assessment of the Activation State of RAS and Map Kinase in Human Breast Cancer Specimens (96Breast)

DTIC Science & Technology

1999-09-01

Cancer 16. PRICE CODE 17. SECURITY CLASSIFICATION 18 . SECURITY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITATION OF ABSTRACT OF REPORT OF...THIS PAGE OF ABSTRACT Unclassified Unclassified Unclassified Unlimited NSN 7640-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI Std. Z39- 18 ...transformation and regulate cell morphology, adhesion and motility through cytoskeletal dynamics and play an important role in carcinogenesis ( 18 ). Rho

Endometrial stromal tumors: the new WHO classification.

PubMed

Conklin, Christopher M J; Longacre, Teri A

2014-11-01

Endometrial stromal tumors are rare uterine mesenchymal neoplasms that have intrigued pathologists for years, not only because they commonly pose diagnostic dilemmas, but also because the classification and pathogenesis of these tumors has been widely debated. The current World Health Organization recognizes 4 categories of endometrial stromal tumor: endometrial stromal nodule (ESN), low-grade endometrial stromal sarcoma (LG-ESS), high-grade endometrial stromal sarcoma (HG-ESS), and undifferentiated uterine sarcoma (UUS). uterine sarcoma. These categories are defined by the presence of distinct translocations as well as tumor morphology and prognosis. Specifically, the JAZF1-SUZ12 (formerly JAZF1-JJAZ1) fusion identifies a large proportion of ESN and LG-ESSs, whereas the YWHAE-FAM22 translocation identifies HG-ESSs. The latter tumors appear to have a prognosis intermediate between LG-ESS and UUS, which exhibits no specific translocation pattern. This review (1) presents the clinicopathologic features of endometrial stromal tumors; (2) discusses their immunophenotype; and (3) highlights the recent advances in molecular genetics which explain their pathogenesis and lend support for a new classification system.

Proposed morphologic classification of prostate cancer with neuroendocrine differentiation.

PubMed

Epstein, Jonathan I; Amin, Mahul B; Beltran, Himisha; Lotan, Tamara L; Mosquera, Juan-Miguel; Reuter, Victor E; Robinson, Brian D; Troncoso, Patricia; Rubin, Mark A

2014-06-01

On July 31, 2013, the Prostate Cancer Foundation assembled a working committee on the molecular biology and pathologic classification of neuroendocrine (NE) differentiation in prostate cancer. New clinical and molecular data emerging from prostate cancers treated by contemporary androgen deprivation therapies, as well as primary lesions, have highlighted the need for refinement of diagnostic terminology to encompass the full spectrum of NE differentiation. The classification system consists of: Usual prostate adenocarcinoma with NE differentiation; 2) Adenocarcinoma with Paneth cell NE differentiation; 3) Carcinoid tumor; 4) Small cell carcinoma; 5) Large cell NE carcinoma; and 5) Mixed NE carcinoma - acinar adenocarcinoma. The article also highlights "prostate carcinoma with overlapping features of small cell carcinoma and acinar adenocarcinoma" and "castrate-resistant prostate cancer with small cell cancer-like clinical presentation". It is envisioned that specific criteria associated with the refined diagnostic terminology will lead to clinically relevant pathologic diagnoses that will stimulate further clinical and molecular investigation and identification of appropriate targeted therapies.

Tumor Heterogeneity in Breast Cancer

PubMed Central

Turashvili, Gulisa; Brogi, Edi

2017-01-01

Breast cancer is a heterogeneous disease and differs greatly among different patients (intertumor heterogeneity) and even within each individual tumor (intratumor heterogeneity). Clinical and morphologic intertumor heterogeneity is reflected by staging systems and histopathologic classification of breast cancer. Heterogeneity in the expression of established prognostic and predictive biomarkers, hormone receptors, and human epidermal growth factor receptor 2 oncoprotein is the basis for targeted treatment. Molecular classifications are indicators of genetic tumor heterogeneity, which is probed with multigene assays and can lead to improved stratification into low- and high-risk groups for personalized therapy. Intratumor heterogeneity occurs at the morphologic, genomic, transcriptomic, and proteomic levels, creating diagnostic and therapeutic challenges. Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Despite the improved knowledge of the complex genetic and phenotypic features underpinning tumor heterogeneity, there has been only limited advancement in diagnostic, prognostic, or predictive strategies for breast cancer. The current guidelines for reporting of biomarkers aim to maximize patient eligibility for targeted therapy, but do not take into account intratumor heterogeneity. The molecular classification of breast cancer is not implemented in routine clinical practice. Additional studies and in-depth analysis are required to understand the clinical significance of rapidly accumulating data. This review highlights inter- and intratumor heterogeneity of breast carcinoma with special emphasis on pathologic findings, and provides insights into the clinical significance of molecular and cellular mechanisms of heterogeneity. PMID:29276709

Classification of orbital morphology for decompression surgery in Graves' orbitopathy: two-dimensional versus three-dimensional orbital parameters.

PubMed

Borumandi, Farzad; Hammer, Beat; Noser, Hansrudi; Kamer, Lukas

2013-05-01

Three-dimensional (3D) CT reconstruction of the bony orbit for accurate measurement and classification of the complex orbital morphology may not be suitable for daily practice. We present an easily measurable two-dimensional (2D) reference dataset of the bony orbit for study of individual orbital morphology prior to decompression surgery in Graves' orbitopathy. CT images of 70 European adults (140 orbits) with unaffected orbits were included. On axial views, the following orbital dimensions were assessed: orbital length (OL), globe length (GL), GL/OL ratio and cone angle. Postprocessed CT data were required to measure the corresponding 3D orbital parameters. The 2D and 3D orbital parameters were correlated. The 2D orbital parameters were significantly correlated to the corresponding 3D parameters (significant at the 0.01 level). The average GL was 25 mm (SD±1.0), the average OL was 42 mm (SD±2.0) and the average GL/OL ratio was 0.6 (SD±0.03). The posterior cone angle was, on average, 50.2° (SD±4.1). Three orbital sizes were classified: short (OL≤40 mm), medium (OL>40 to <45 mm) and large (OL≥45 mm). We present easily measurable reference data for the orbit that can be used for preoperative study and classification of individual orbital morphology. A short and shallow orbit may require a different decompression technique than a large and deep orbit. Prospective clinical trials are needed to demonstrate how individual orbital morphology affects the outcome of decompression surgery.

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

NASA Technical Reports Server (NTRS)

Hoover, Richard B.; Storrie-Lombardi, Michael C.

2004-01-01

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Automatic identification of species with neural networks.

PubMed

Hernández-Serna, Andrés; Jiménez-Segura, Luz Fernanda

2014-01-01

A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.

Accurate label-free 3-part leukocyte recognition with single cell lens-free imaging flow cytometry.

PubMed

Li, Yuqian; Cornelis, Bruno; Dusa, Alexandra; Vanmeerbeeck, Geert; Vercruysse, Dries; Sohn, Erik; Blaszkiewicz, Kamil; Prodanov, Dimiter; Schelkens, Peter; Lagae, Liesbet

2018-05-01

Three-part white blood cell differentials which are key to routine blood workups are typically performed in centralized laboratories on conventional hematology analyzers operated by highly trained staff. With the trend of developing miniaturized blood analysis tool for point-of-need in order to accelerate turnaround times and move routine blood testing away from centralized facilities on the rise, our group has developed a highly miniaturized holographic imaging system for generating lens-free images of white blood cells in suspension. Analysis and classification of its output data, constitutes the final crucial step ensuring appropriate accuracy of the system. In this work, we implement reference holographic images of single white blood cells in suspension, in order to establish an accurate ground truth to increase classification accuracy. We also automate the entire workflow for analyzing the output and demonstrate clear improvement in the accuracy of the 3-part classification. High-dimensional optical and morphological features are extracted from reconstructed digital holograms of single cells using the ground-truth images and advanced machine learning algorithms are investigated and implemented to obtain 99% classification accuracy. Representative features of the three white blood cell subtypes are selected and give comparable results, with a focus on rapid cell recognition and decreased computational cost. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

On the dynamical basis of the classification of normal galaxies

PubMed Central

Haass, J.; Bertin, G.; Lin, C. C.

1982-01-01

Some realistic galaxy models have been found to support discrete unstable spiral modes. Here, through the study of the relevant physical mechanisms and an extensive numerical investigation of the properties of the dominant modes in a wide class of galactic equilibria, we show how spiral structures are excited with different morphological features, depending on the properties of the equilibrium model. We identify the basic dynamical parameters and mechanisms and compare the resulting morphology of spiral modes with the actual classification of galaxies. The present study suggests a dynamical basis for the transition among various types and subclasses of normal and barred spiral galaxies. Images PMID:16593200

Surveying of morphological variations and Shoreline Classification of Bandar Abbas for providing Shoreline Management Plan

NASA Astrophysics Data System (ADS)

Ghobadi-Bistooni, Sadegh; Chegini, Vahid; Ershadi, Siroc; Tajziehchi, Mojtaba

2010-05-01

Since Bandar Abbas city is located in a strategic commercial, recreational, fishery, political and military region, its coastline has been employed for different application during last three decades, especially construction of Marian facilities. Therefore, conducting of research projects has become important for management decision making and development of coastal zone of the city. This fact becomes more realistic when the coast is classified based on different views and each part of the coast is investigated as a cell or sub cell due to its different behavior. In this, first, different methods for classification of coasts have been reviewed. Then, emphasizing on hydrodynamic and morphological classification, the slope, morphological aspects, kind of coastline and the gradation of its materials, as well as the slope of coastline have been determined. Moreover, the characteristics of wind waves in the region have been investigated using the SW module of MIKE21 software. On the other hands, the beach state has been determined using Masselink & Short, Masselink & Hegge, and Short & Hesp methods and employing RTR and Ω parameters. Finally, the regions of accretion and erosion in this coast line have been investigated using aerial and satellite images captured during last decades.

Development, characterization, and lethal effect of monoclonal antibodies against hemocytes in an adult female tick, Ornithodoros moubata (Acari: Argasidae).

PubMed

Matsuo, T; Tsukamoto, D; Inoue, N; Fujisaki, K

2003-12-01

In the present study, 19 monoclonal antibodies (mAbs) against adult Ornithodoros moubata hemocytes were established, and the reactivity of the hemocytes to these mAbs was examined by an indirect fluorescent antibody test (IFAT), Western blot and immunoprecipitation analyses. It was shown that the reactivities of the hemocytes to the mAbs varied among morphologically similar hemocyte types, and most mAbs produced in the present study showed the multiple band reactivity. However, the presence of shared epitopes among peptide subunits of the same protein or entirely different proteins are not common, so their reactivity could not be explained in detail. These results suggest that there are morphologically similar but functionally differentiated hemocytes. Therefore, in addition to morphological classification, the molecular-based classification of the hemocytes is also required. In order to assess the lethal effect of blood meal containing each mAb, artificial feeding was performed. The OmHC 31 showed the strongest lethal effect on adult female O. moubata. In conclusion, anti-hemocyte mAbs produced in this study are useful not only for the immunological classification of hemocytes but also for the immunological control of the tick.

3P: Personalized Pregnancy Prediction in IVF Treatment Process

NASA Astrophysics Data System (ADS)

Uyar, Asli; Ciray, H. Nadir; Bener, Ayse; Bahceci, Mustafa

We present an intelligent learning system for improving pregnancy success rate of IVF treatment. Our proposed model uses an SVM based classification system for training a model from past data and making predictions on implantation outcome of new embryos. This study employs an embryo-centered approach. Each embryo is represented with a data feature vector including 17 features related to patient characteristics, clinical diagnosis, treatment method and embryo morphological parameters. Our experimental results demonstrate a prediction accuracy of 82.7%. We have obtained the IVF dataset from Bahceci Women Health, Care Centre, in Istanbul, Turkey.

Effect of sperm concentration in an ejaculate on morphometric traits of spermatozoa in Duroc boars.

PubMed

Kondracki, S; Wysokińska, A; Iwanina, M; Banaszewska, D; Sitarz, D

2011-01-01

The experimental material consisted of 75 ejaculates collected form 8 Duroc boars. The ejaculates were divided into three groups according to sperm concentration in an ejaculate. An ejaculate was obtained from each boar monthly and it was used to make microscopic preparations to examine spermatozoa morphology. In each preparation morphometric measurements were taken of fifteen randomly selected spermatozoa characterized by normal morphology. The following measurements of spermatozoa were taken: length and width of the spermatozoa head, head area, length of the flagellum, perimeter of the spermatozoon head and total spermatozoon length. The results were used to calculate indicators of spermatozoa morphology. Moreover, assessments were made of frequency of morphological defects to isolate spermatozoa with primary and secondary abnormalities following the Blom classification system. It was found that the concentration of spermatozoa in the ejaculate influenced the morphometric characteristics of spermatozoa. Ejaculates with low sperm concentrations are characterized by larger spermatozoa as compared to ejaculates with high sperm concentrations. However, sperm concentration in the ejaculate does not much influence the shape of spermatozoa.

Waking the dead: morphological and molecular characterization of extant †Posoniella tricarinelloides (Thoracosphaeraceae, Dinophyceae).

PubMed

Gu, Haifeng; Kirsch, Monika; Zinssmeister, Carmen; Soehner, Sylvia; Meier, K J Sebastian; Liu, Tingting; Gottschling, Marc

2013-09-01

The Thoracosphaeraceae are dinophytes that produce calcareous shells during their life history, whose optical crystallography has been the basis for the division into subfamilies. To evaluate the validity of the classification (mainly applied by palaeontologists), living material of phylogenetic key species is necessary albeit frequently difficult to access for contemporary morphological and molecular analyses. We isolated and established five living strains of the rare fossil-taxon †Posoniella tricarinelloides from different sediment samples collected in the South China Sea, Yellow Sea and in the Mediterranean Sea (west coast off Italy). Here, we provide detailed descriptions of its morphology and conducted phylogenetic analyses based on hundreds of accessions and thousands of informative sites on concatenated rRNA datasets. Within the monophyletic Peridiniales, †P. tricarinelloides was reliably nested in the Thoracosphaeraceae and exhibited two distinct morphological types of coccoid cells. The two morphologies of coccoid cells would have been assigned to different taxa at the subfamily level if found separately in fossil samples. Our results thus challenge previous classification concepts within the dinophytes and underline the importance of comparative morphological and molecular studies to better understand the complex biology of unicellular organisms such as †P. tricarinelloides. Copyright © 2013 Elsevier GmbH. All rights reserved.

Taxonomic complexity of powdery mildew pathogens found on lentil and pea in the US Pacific Northwest

USDA-ARS?s Scientific Manuscript database

Classification of powdery mildews found on lentil and pea in greenhouse and field production conditions in the US Pacific Northwest was investigated using morphological and molecular characters. Isolates collected from lentil plants grown in the greenhouse or field displayed morphologies in substant...

A new taxonomic classification for species in Gomphus sensu lato

Treesearch

Admir J. Giachini; Michael A. Castellano

2011-01-01

Taxonomy of the Gomphales has been revisited by combining morphology and molecular data (DNA sequences) to provide a natural classification for the species of Gomphus sensu lato. Results indicate Gomphus s.l. to be non-monophyletic, leading to new combinations and the placement of its species into four genera: Gomphus...

Hamate-pisiform coalition: morphology, clinical significance, and a simplified classification scheme for carpal coalition.

PubMed

Burnett, Scott E

2011-03-01

Hamate-pisiform coalition is characterized by the abnormal union of the pisiform bone and hamulus of the hamate. Because most reported cases are isolated, and literature on the subject is sparse, relatively little is known about this condition and its clinical significance. The purpose of this report is to discuss the occurrence, morphology, and frequency of hamate-pisiform coalition identified in a skeletal sample of native South Africans, and to conduct a metaanalysis of all known cases in order to clarify the sex distribution, laterality, form, and clinical significance of this condition. Five new cases (three male, two female) of hamate-pisiform coalition were identified in 527 native South Africans. Results indicate that hamate-pisiform coalition is infrequent (0.76%) but may be more likely encountered in individuals of African ancestry. Morphologically, non-osseous examples ranged in appearance from minor expressions involving pitting of an expanded hamulus base, to a variably pitted articulation between an elongated pisiform and hamulus. Osseous union between the two bones tends to extend beyond the hamulus base to adjacent areas of the hamate. Cases involving osseous union appear predisposed to fracture while ulnar neuropathy is significantly more frequent in individuals exhibiting non-osseous coalition. As both non-osseous and osseous cases can have clinical significance, awareness of the variable manifestations of this condition is necessary for hand specialists. A simplified classification system is suggested to more consistently characterize carpal coalitions. Copyright © 2010 Wiley-Liss, Inc.

The Statistical Signal of Morphological Process in Stratigraphy

NASA Astrophysics Data System (ADS)

Esposito, C. R.; Straub, K. M.

2013-12-01

The most widely used classification of river delta morphologies, Galloway's ternary diagram, holds that the surface characteristics of a delta, including the distribution of depositional environments, and shoreline shape, can be predicted by the relative strengths of the fluvial and marine processes that influence the delta. Though almost 40 years old, Galloway's diagram of wave, river, and tide dominated deltas is still widely referred to in textbooks and in literature as a way of describing the relationship between morphological processes and the distribution of depositional environments over a single delta 'event' such as the progradation of one delta lobe. However, there is no complimentary classification scheme that addresses the ways in which deltaic stratigraphy under varying forcing conditions is preserved over sequences of many such events. Such sequences operating over a range of time scales set the architecture of sedimentary basins, so a method of classifying the stratigraphic result is an important goal. In this study, we use Delft3D to examine the autogenic behavior of thick packages of simulated deltaic stratigraphy (>10 channel depths) under the influence of a range of wave, tide, and flood-dominated conditions, as well as a variety of sedimentary inputs. We quantify the strength and type of autogenic behavior by measuring stratigraphic completeness and compensation index. Both metrics have been observed to vary systematically in field scale systems, and in experimental deltas deposited under a range of river dominated conditions. This work will extend that range into deltas with significant wave, tide, and flood influence.

Molecular systematics of the barklouse family Psocidae (Insecta: Psocodea: 'Psocoptera') and implications for morphological and behavioral evolution.

PubMed

Yoshizawa, Kazunori; Johnson, Kevin P

2008-02-01

We evaluated the higher level classification within the family Psocidae (Insecta: Psocodea: 'Psocoptera') based on combined analyses of nuclear 18S, Histone 3, wingless and mitochondrial 12S, 16S and COI gene sequences. Various analyses (inclusion/exclusion of incomplete taxa and/or rapidly evolving genes, data partitioning, and analytical method selection) all provided similar results, which were generally concordant with relationships inferred using morphological observations. Based on the phylogenetic trees estimated for Psocidae, we propose a revised higher level classification of this family, although uncertainty still exists regarding some aspects of this classification. This classification includes a basal division into two subfamilies, 'Amphigerontiinae' (possibly paraphyletic) and Psocinae. The Amphigerontiinae is divided into the tribes Kaindipsocini (new tribe), Blastini, Amphigerontini, and Stylatopsocini. Psocinae is divided into the tribes 'Ptyctini' (probably paraphyletic), Psocini, Atrichadenotecnini (new tribe), Sigmatoneurini, Metylophorini, and Thyrsophorini (the latter includes the taxon previously recognized as Cerastipsocini). We examined the evolution of symmetric/asymmetric male genitalia over this tree and found this character to be quite homoplasious.

[Surgical treatment of chronic pancreatitis based on classification of M. Buchler and coworkers].

PubMed

Krivoruchko, I A; Boĭko, V V; Goncharova, N N; Andreeshchev, S A

2011-08-01

The results of surgical treatment of 452 patients, suffering chronic pancreatitis (CHP), were analyzed. The CHP classification, elaborated by M. Buchler and coworkers (2009), based on clinical signs, morphological peculiarities and pancreatic function analysis, contains scientifically substantiated recommendations for choice of diagnostic methods and complex treatment of the disease. The classification proposed is simple in application and constitutes an instrument for studying and comparison of the CHP course severity, the patients prognosis and treatment.

An automatic taxonomy of galaxy morphology using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Hocking, Alex; Geach, James E.; Sun, Yi; Davey, Neil

2018-01-01

We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy we use no pre-selection or pre-filtering of target galaxy type to identify galaxies that are similar. We demonstrate the technique on the Hubble Space Telescope (HST) Frontier Fields. By training the algorithm using galaxies from one field (Abell 2744) and applying the result to another (MACS 0416.1-2403), we show how the algorithm can cleanly separate early and late type galaxies without any form of pre-directed training for what an 'early' or 'late' type galaxy is. We then apply the technique to the HST Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) fields, creating a catalogue of approximately 60 000 classifications. We show how the automatic classification groups galaxies of similar morphological (and photometric) type and make the classifications public via a catalogue, a visual catalogue and galaxy similarity search. We compare the CANDELS machine-based classifications to human-classifications from the Galaxy Zoo: CANDELS project. Although there is not a direct mapping between Galaxy Zoo and our hierarchical labelling, we demonstrate a good level of concordance between human and machine classifications. Finally, we show how the technique can be used to identify rarer objects and present lensed galaxy candidates from the CANDELS imaging.

A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification

NASA Astrophysics Data System (ADS)

Yang, Qiuju; Hu, Ze-Jun

2018-03-01

Aurora is a very important geophysical phenomenon in the high latitudes of Arctic and Antarctic regions, and it is important to make a comparative study of the auroral morphology between the two hemispheres. Based on the morphological characteristics of the four labeled dayside discrete auroral types (auroral arc, drapery corona, radial corona and hot-spot aurora) on the 8001 dayside auroral images at the Chinese Arctic Yellow River Station in 2003, and by extracting the local binary pattern (LBP) features and using a k-nearest classifier, this paper performs an automatic classification of the 65 361 auroral images of the Chinese Arctic Yellow River Station during 2004-2009 and the 39 335 auroral images of the South Pole Station between 2003 and 2005. Finally, it obtains the occurrence distribution of the dayside auroral morphology in the Northern and Southern Hemisphere. The statistical results indicate that the four dayside discrete auroral types present a similar occurrence distribution between the two stations. To the best of our knowledge, we are the first to report statistical comparative results of dayside auroral morphology distribution between the Northern and Southern Hemisphere.

[Review of current classification and terminology of vulvar disorders].

PubMed

Sláma, J

2012-08-01

To summarize current terminology and classification of vulvar disorders. Review article. Gynecologic oncology center, Department of Gynecology and Obstetrics, General Faculty Hospital and 1st Medical School of Charles University, Prague. Vulvar disorders include wide spectrum of different diagnoses. Multidisciplinary collaboration is frequently needed in diagnostical and therapeutical process. It is essential to use unified terminology using standard dermatological terms, and unified classification for comprehensible communication between different medical professions. Current classification, which is based on Clinical-pathological criteria, was established by International Society for the Study of Vulvovaginal Disease. Recently, there was introduced Clinical classification, which groups disorders according to main morphological finding. Adequate and unified classification and terminology are necessary for effective communication during the diagnostical process.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy.

PubMed

Welikala, R A; Fraz, M M; Dehmeshki, J; Hoppe, A; Tah, V; Mann, S; Williamson, T H; Barman, S A

2015-07-01

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Classification of anemia for gastroenterologists

PubMed Central

Moreno Chulilla, Jose Antonio; Romero Colás, Maria Soledad; Gutiérrez Martín, Martín

2009-01-01

Most anemia is related to the digestive system by dietary deficiency, malabsorption, or chronic bleeding. We review the World Health Organization definition of anemia, its morphological classification (microcytic, macrocytic and normocytic) and pathogenic classification (regenerative and hypo regenerative), and integration of these classifications. Interpretation of laboratory tests is included, from the simplest (blood count, routine biochemistry) to the more specific (iron metabolism, vitamin B12, folic acid, reticulocytes, erythropoietin, bone marrow examination and Schilling test). In the text and various algorithms, we propose a hierarchical and logical way to reach a diagnosis as quickly as possible, by properly managing the medical interview, physical examination, appropriate laboratory tests, bone marrow examination, and other complementary tests. The prevalence is emphasized in all sections so that the gastroenterologist can direct the diagnosis to the most common diseases, although the tables also include rare diseases. Digestive diseases potentially causing anemia have been studied in preference, but other causes of anemia have been included in the text and tables. Primitive hematological diseases that cause anemia are only listed, but are not discussed in depth. The last section is dedicated to simplifying all items discussed above, using practical rules to guide diagnosis and medical care with the greatest economy of resources and time. PMID:19787825

Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

PubMed Central

Jaiswara, Ranjana; Nandi, Diptarup; Balakrishnan, Rohini

2013-01-01

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6–7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification. PMID:24086666

Machine vision system for measuring conifer seedling morphology

NASA Astrophysics Data System (ADS)

Rigney, Michael P.; Kranzler, Glenn A.

1995-01-01

A PC-based machine vision system providing rapid measurement of bare-root tree seedling morphological features has been designed. The system uses backlighting and a 2048-pixel line- scan camera to acquire images with transverse resolutions as high as 0.05 mm for precise measurement of stem diameter. Individual seedlings are manually loaded on a conveyor belt and inspected by the vision system in less than 0.25 seconds. Designed for quality control and morphological data acquisition by nursery personnel, the system provides a user-friendly, menu-driven graphical interface. The system automatically locates the seedling root collar and measures stem diameter, shoot height, sturdiness ratio, root mass length, projected shoot and root area, shoot-root area ratio, and percent fine roots. Sample statistics are computed for each measured feature. Measurements for each seedling may be stored for later analysis. Feature measurements may be compared with multi-class quality criteria to determine sample quality or to perform multi-class sorting. Statistical summary and classification reports may be printed to facilitate the communication of quality concerns with grading personnel. Tests were conducted at a commercial forest nursery to evaluate measurement precision. Four quality control personnel measured root collar diameter, stem height, and root mass length on each of 200 conifer seedlings. The same seedlings were inspected four times by the machine vision system. Machine stem diameter measurement precision was four times greater than that of manual measurements. Machine and manual measurements had comparable precision for shoot height and root mass length.

Multi-classification of cell deformation based on object alignment and run length statistic.

PubMed

Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang

2014-01-01

Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

An FPGA-Based Rapid Wheezing Detection System

PubMed Central

Lin, Bor-Shing; Yen, Tian-Shiue

2014-01-01

Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

A clinico-pathological study of lupus nephritis based on the International Society of Nephrology-Renal Pathology Society 2003 classification system.

PubMed

Satish, Suchitha; Deka, Pallavi; Shetty, Manjunath Sanjeev

2017-01-01

Lupus nephritis (LN) is a major complication of systemic lupus erythematosus (SLE). Renal involvement is a major determinant of the prognosis of SLE. The histological classification of LN is a key factor in determining the renal survival of patients with LN. Prompt recognition and treatment of renal disease are important, as early response to therapy is correlated with better outcome and renal biopsy plays an important role in achieving this. The objective of this study was to correlate the clinical and laboratory findings with histopathological classes of LN as per the 2003 International Society of Nephrology-Renal Pathology Society (ISN/RPS) classification system. Fifty-six patients with SLE, undergoing a renal biopsy for renal dysfunction were studied. The comparison of data from multiple groups was made by Pearson's Chi-square test and between two groups by independent samples t -test. The values of P < 0.05 were considered statistically significant. Of the 56 cases studied, 51 (91.1%) were females. The most common presenting symptoms were edema, arthralgia, and hypertension. Class IV (55.4%) was the most common class. Thirty-nine (69.6%) cases showed full house immunostaining. Hypertension, hematuria, proteinuria, and tubulo-interstitial disease showed a significant correlation ( P < 0.05) with ISN/RPS classification, 2003. Assessment and management of patients with suspected LN are greatly facilitated through information obtained by renal biopsy. Since renal morphology may predict long-term prognosis, and no clinical or laboratory feature uniformly predicts prognosis, it is important to study the constellation of features in LN for better patient management.

Monitoring and Morphologic Classification of Pediatric Cataract Using Slit-Lamp-Adapted Photography.

PubMed

Long, Erping; Lin, Zhuoling; Chen, Jingjing; Liu, Zhenzhen; Cao, Qianzhong; Lin, Haotian; Chen, Weirong; Liu, Yizhi

2017-11-01

To investigate the feasibility of pediatric cataract monitoring and morphologic classification using slit lamp-adapted anterior segmental photography in a large cohort that included uncooperative children. Patients registered in the Childhood Cataract Program of the Chinese Ministry of Health were prospectively selected. Eligible patients underwent slit-lamp adapted anterior segmental photography to record and monitor the morphology of their cataractous lenses. A set of assistance techniques for slit lamp-adapted photography was developed to instruct the parents of uncooperative children how to help maintain the child's head position and keep the eyes open after sleep aid administration. Briefly, slit lamp-adapted photography was completed for all 438 children, including 260 (59.4%) uncooperative children with our assistance techniques. All 746 images of 438 patients successfully confirmed the diagnoses and classifications. Considering the lesion location, pediatric cataract morphologies could be objectively classified into the seven following types: total; nuclear; polar, including two subtypes (anterior and posterior); lamellar; nuclear combined with cortical, including three subtypes (coral-like, dust-like, and blue-dot); cortical; and Y suture. The top three types of unilateral cataracts were polar (55, 42.3%), total (42, 32.3%), and nuclear (23, 17.7%); and the top three types of bilateral cataracts were nuclear (110, 35.8%), total (102, 33.2%), and lamellar (34, 11.1%). Slit lamp-adapted anterior segmental photography is applicable for monitoring and classifying the morphologies of pediatric cataracts and is even safe and feasible for uncooperative children with assistance techniques and sleep aid administration. This study proposes a novel strategy for the preoperative evaluation and evidence-based management of pediatric ophthalmology (Clinical Trials.gov, NCT02748031).

Using Different Standardized Methods for Species Identification: A Case Study Using Beaks from Three Ommastrephid Species

NASA Astrophysics Data System (ADS)

Hu, Guanyu; Fang, Zhou; Liu, Bilin; Chen, Xinjun; Staples, Kevin; Chen, Yong

2018-04-01

The cephalopod beak is a vital hard structure with a stable configuration and has been widely used for the identification of cephalopod species. This study was conducted to determine the best standardization method for identifying different species by measuring 12 morphological variables of the beaks of Illex argentinus, Ommastrephes bartramii, and Dosidicus gigas that were collected by Chinese jigging vessels. To remove the effects of size, these morphometric variables were standardized using three methods. The average ratios of the upper beak morphological variables and upper crest length of O. bartramii and D. gigas were found to be greater than those of I. argentinus. However, for lower beaks, only the average of LRL (lower rostrum length)/ LCL (lower crest length), LRW (lower rostrum width)/ LCL, and LLWL (lower lateral wall length)/ LCL of O. bartramii and D. gigas were greater than those of I. argentinus. The ratios of beak morphological variables and crest length were found to be all significantly different among the three species ( P < 0.001). Among the three standardization methods, the correct classification rate of stepwise discriminant analysis (SDA) was the highest using the ratios of beak morphological variables and crest length. Compared with hood length, the correct classification rate was slightly higher when using beak variables standardized by crest length using an allometric model. The correct classification rate of the lower beak was also found to be greater than that of the upper beak. This study indicates that the ratios of beak morphological variables to crest length could be used for interspecies and intraspecies identification. Meanwhile, the lower beak variables were found to be more effective than upper beak variables in classifying beaks found in the stomachs of predators.

A boosted optimal linear learner for retinal vessel segmentation

NASA Astrophysics Data System (ADS)

Poletti, E.; Grisan, E.

2014-03-01

Ocular fundus images provide important information about retinal degeneration, which may be related to acute pathologies or to early signs of systemic diseases. An automatic and quantitative assessment of vessel morphological features, such as diameters and tortuosity, can improve clinical diagnosis and evaluation of retinopathy. At variance with available methods, we propose a data-driven approach, in which the system learns a set of optimal discriminative convolution kernels (linear learner). The set is progressively built based on an ADA-boost sample weighting scheme, providing seamless integration between linear learner estimation and classification. In order to capture the vessel appearance changes at different scales, the kernels are estimated on a pyramidal decomposition of the training samples. The set is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). We tested the approach fundus images available from the DRIVE dataset. We show that the segmentation performance yields an accuracy of 0.94.

Assessment of respiratory flow cycle morphology in patients with chronic heart failure.

PubMed

Garde, Ainara; Sörnmo, Leif; Laguna, Pablo; Jané, Raimon; Benito, Salvador; Bayés-Genís, Antoni; Giraldo, Beatriz F

2017-02-01

Breathing pattern as periodic breathing (PB) in chronic heart failure (CHF) is associated with poor prognosis and high mortality risk. This work investigates the significance of a number of time domain parameters for characterizing respiratory flow cycle morphology in patients with CHF. Thus, our primary goal is to detect PB pattern and identify patients at higher risk. In addition, differences in respiratory flow cycle morphology between CHF patients (with and without PB) and healthy subjects are studied. Differences between these parameters are assessed by investigating the following three classification issues: CHF patients with PB versus with non-periodic breathing (nPB), CHF patients (both PB and nPB) versus healthy subjects, and nPB patients versus healthy subjects. Twenty-six CHF patients (8/18 with PB/nPB) and 35 healthy subjects are studied. The results show that the maximal expiratory flow interval is shorter and with lower dispersion in CHF patients than in healthy subjects. The flow slopes are much steeper in CHF patients, especially for PB. Both inspiration and expiration durations are reduced in CHF patients, mostly for PB. Using the classification and regression tree technique, the most discriminant parameters are selected. For signals shorter than 1 min, the time domain parameters produce better results than the spectral parameters, with accuracies for each classification of 82/78, 89/85, and 91/89 %, respectively. It is concluded that morphologic analysis in the time domain is useful, especially when short signals are analyzed.

Galaxy Zoo: Comparing the visual morphology of synthetic galaxies from the Illustris simulation with those in the real Universe.

NASA Astrophysics Data System (ADS)

Dickinson, Hugh; Lintott, Chris; Scarlata, Claudia; Fortson, Lucy; Bamford, Steven; Cardamone, Carolin; Keel, William C.; Kruk, Sandor; Masters, Karen; Simmons, Brooke D.; Vogelsberger, Mark; Torrey, Paul; Snyder, Gregory; Galaxy Zoo Science Team

2018-01-01

We present a comparision between the Illustris simulations and classifications from Galaxy Zoo, aiming to test the ability of modern large-scale cosmological simulations to accurately reproduce the local galaxy population. This comparison is enabled by the increasingly high spatial and temporal resolution obtained by such surveys.Using classifications that were accumulated via the Galaxy Zoo citizen science interface, we compare the visual morphologies for simulated images of Illustris galaxies with a compatible sample of images drawn from the Sloan Digital Sky Survey (SDSS) Legacy Survey.For simulated galaxies with stellar masses less than 1011 M⊙, significant differences are identified, which are most likely due to the limited resolution of the simulation, but could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Above 1011 M⊙, Illustris galaxy morphologies correspond better with those of their SDSS counterparts, although even in this mass range the simulation appears to underproduce obviously disk-like galaxies. Morphologies of Illustris galaxies less massive than 1011 M⊙ should be treated with care.

New Myositis Classification Criteria-What We Have Learned Since Bohan and Peter.

PubMed

Leclair, Valérie; Lundberg, Ingrid E

2018-03-17

Idiopathic inflammatory myopathy (IIM) classification criteria have been a subject of debate for many decades. Despite several limitations, the Bohan and Peter criteria are still widely used. The aim of this review is to discuss the evolution of IIM classification criteria. New IIM classification criteria are periodically proposed. The discovery of myositis-specific and myositis-associated autoantibodies led to the development of clinico-serological criteria, while in-depth description of IIM morphological features improved histopathology-based criteria. The long-awaited European League Against Rheumatism and American College of Rheumatology (EULAR/ACR) IIM classification criteria were recently published. The Bohan and Peter criteria are outdated and validated classification criteria are necessary to improve research in IIM. The new EULAR/ACR IIM classification criteria are thus a definite improvement and an important step forward in the field.

CP-CHARM: segmentation-free image classification made accessible.

PubMed

Uhlmann, Virginie; Singh, Shantanu; Carpenter, Anne E

2016-01-27

Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed on the whole image, thereby avoiding the need for segmentation. The algorithm obtained encouraging results but requires considerable computational expertise to execute. Furthermore, some benchmark sets have been shown to be subject to confounding artifacts that overestimate classification accuracy. We developed CP-CHARM, a user-friendly image-based classification algorithm inspired by WND-CHARM in (i) its ability to capture a wide variety of morphological aspects of the image, and (ii) the absence of requirement for segmentation. In order to make such an image-based classification method easily accessible to the biological research community, CP-CHARM relies on the widely-used open-source image analysis software CellProfiler for feature extraction. To validate our method, we reproduced WND-CHARM's results and ensured that CP-CHARM obtained comparable performance. We then successfully applied our approach on cell-based assay data and on tissue images. We designed these new training and test sets to reduce the effect of batch-related artifacts. The proposed method preserves the strengths of WND-CHARM - it extracts a wide variety of morphological features directly on whole images thereby avoiding the need for cell segmentation, but additionally, it makes the methods easily accessible for researchers without computational expertise by implementing them as a CellProfiler pipeline. It has been demonstrated to perform well on a wide range of bioimage classification problems, including on new datasets that have been carefully selected and annotated to minimize batch effects. This provides for the first time a realistic and reliable assessment of the whole image classification strategy.

Sessile serrated adenomas with dysplasia: morphological patterns and correlations with MLH1 immunohistochemistry.

PubMed

Liu, Cheng; Walker, Neal I; Leggett, Barbara A; Whitehall, Vicki Lj; Bettington, Mark L; Rosty, Christophe

2017-12-01

Sessile serrated adenomas are the precursor polyp of approximately 20% of colorectal carcinomas. Sessile serrated adenomas with dysplasia are rarely encountered and represent an intermediate step to malignant progression, frequently associated with loss of MLH1 expression. Accurate diagnosis of these lesions is important to facilitate appropriate surveillance, particularly because progression from dysplasia to carcinoma can be rapid. The current World Health Organization classification describes two main patterns of dysplasia occurring in sessile serrated adenomas, namely, serrated and conventional. However, this may not adequately reflect the spectrum of changes seen by pathologists in routine practice. Furthermore, subtle patterns of dysplasia that are nevertheless associated with loss of MLH1 expression are not encompassed in this classification. We performed a morphological analysis of 266 sessile serrated adenomas with dysplasia with concurrent MLH1 immunohistochemistry with the aims of better defining the spectrum of dysplasia occurring in these lesions and correlating dysplasia patterns with MLH1 expression. We found that dysplasia can be divided morphologically into four major patterns, comprising minimal deviation (19%), serrated (12%), adenomatous (8%) and not otherwise specified (79%) groups. Minimal deviation dysplasia is defined by minor architectural and cytological changes that typically requires loss of MLH1 immunohistochemical expression to support the diagnosis. Serrated dysplasia and adenomatous dysplasia have distinctive histological features and are less frequently associated with loss of MLH1 expression (13 and 5%, respectively). Finally, dysplasia not otherwise specified encompasses most cases and shows a diverse range of morphological changes that do not fall into the other subgroups and are frequently associated with loss of MLH1 expression (83%). This morphological classification of sessile serrated adenomas with dysplasia may represent an improvement on the current description as it correlates with the underlying mismatch repair protein status of the polyps and better highlights the range of morphologies seen by pathologists.

Are there pollination syndromes in the Australian epacrids (Ericaceae: Styphelioideae)? A novel statistical method to identify key floral traits per syndrome

PubMed Central

Johnson, Karen A.

2013-01-01

Background and Aims Convergent floral traits hypothesized as attracting particular pollinators are known as pollination syndromes. Floral diversity suggests that the Australian epacrid flora may be adapted to pollinator type. Currently there are empirical data on the pollination systems for 87 species (approx. 15 % of Australian epacrids). This provides an opportunity to test for pollination syndromes and their important morphological traits in an iconic element of the Australian flora. Methods Data on epacrid–pollinator relationships were obtained from published literature and field observation. A multivariate approach was used to test whether epacrid floral attributes related to pollinator profiles. Statistical classification was then used to rank floral attributes according to their predictive value. Data sets excluding mixed pollination systems were used to test the predictive power of statistical classification to identify pollination models. Key Results Floral attributes are correlated with bird, fly and bee pollination. Using floral attributes identified as correlating with pollinator type, bird pollination is classified with 86 % accuracy, red flowers being the most important predictor. Fly and bee pollination are classified with 78 and 69 % accuracy, but have a lack of individually important floral predictors. Excluding mixed pollination systems improved the accuracy of the prediction of both bee and fly pollination systems. Conclusions Although most epacrids have generalized pollination systems, a correlation between bird pollination and red, long-tubed epacrids is found. Statistical classification highlights the relative importance of each floral attribute in relation to pollinator type and proves useful in classifying epacrids to bird, fly and bee pollination systems. PMID:23681546

Automated system for characterization and classification of malaria-infected stages using light microscopic images of thin blood smears.

PubMed

Das, D K; Maiti, A K; Chakraborty, C

2015-03-01

In this paper, we propose a comprehensive image characterization cum classification framework for malaria-infected stage detection using microscopic images of thin blood smears. The methodology mainly includes microscopic imaging of Leishman stained blood slides, noise reduction and illumination correction, erythrocyte segmentation, feature selection followed by machine classification. Amongst three-image segmentation algorithms (namely, rule-based, Chan-Vese-based and marker-controlled watershed methods), marker-controlled watershed technique provides better boundary detection of erythrocytes specially in overlapping situations. Microscopic features at intensity, texture and morphology levels are extracted to discriminate infected and noninfected erythrocytes. In order to achieve subgroup of potential features, feature selection techniques, namely, F-statistic and information gain criteria are considered here for ranking. Finally, five different classifiers, namely, Naive Bayes, multilayer perceptron neural network, logistic regression, classification and regression tree (CART), RBF neural network have been trained and tested by 888 erythrocytes (infected and noninfected) for each features' subset. Performance evaluation of the proposed methodology shows that multilayer perceptron network provides higher accuracy for malaria-infected erythrocytes recognition and infected stage classification. Results show that top 90 features ranked by F-statistic (specificity: 98.64%, sensitivity: 100%, PPV: 99.73% and overall accuracy: 96.84%) and top 60 features ranked by information gain provides better results (specificity: 97.29%, sensitivity: 100%, PPV: 99.46% and overall accuracy: 96.73%) for malaria-infected stage classification. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Diagnosis of Diabetes Mellitus by Extraction of Morphological Features of Red Blood Cells Using an Artificial Neural Network.

PubMed

Palanisamy, Vinupritha; Mariamichael, Anburajan

2016-10-01

Background and Aim: Diabetes mellitus is a metabolic disorder characterized by varying hyperglycemias either due to insufficient secretion of insulin by the pancreas or improper utilization of glucose. The study was aimed to investigate the association of morphological features of erythrocytes among normal and diabetic subjects and its gender-based changes and thereby to develop a computer aided tool to diagnose diabetes using features extracted from RBC. Materials and Methods: The study involved 138 normal and 144 diabetic subjects. The blood was drawn from the subjects and the blood smear prepared was digitized using Zeiss fluorescent microscope. The digitized images were pre-processed and texture segmentation was performed to extract the various morphological features. The Pearson correlation test was performed and subsequently, classification of subjects as normal and diabetes was carried out by a neural network classifier based on the features that demonstrated significance at the level of P <0.05. Result: The proposed system demonstrated an overall accuracy, sensitivity, specificity, positive predictive value and negative predictive value of 93.3, 93.71, 92.8, 93.1 and 93.5% respectively. Conclusion: The morphological features exhibited a statistically significant difference (P<0.01) between the normal and diabetic cells, suggesting that it could be helpful in the diagnosis of Diabetes mellitus using a computer aided system. © Georg Thieme Verlag KG Stuttgart · New York.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects.

PubMed

Kim, Jinkwon; Min, Se Dong; Lee, Myoungho

2011-06-27

Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.

An arrhythmia classification algorithm using a dedicated wavelet adapted to different subjects

PubMed Central

2011-01-01

Background Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia. Methods In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm. Results A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%. Conclusions The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians. PMID:21707989

Molecular Pathology: Predictive, Prognostic, and Diagnostic Markers in Uterine Tumors.

PubMed

Ritterhouse, Lauren L; Howitt, Brooke E

2016-09-01

This article focuses on the diagnostic, prognostic, and predictive molecular biomarkers in uterine malignancies, in the context of morphologic diagnoses. The histologic classification of endometrial carcinomas is reviewed first, followed by the description and molecular classification of endometrial epithelial malignancies in the context of histologic classification. Taken together, the molecular and histologic classifications help clinicians to approach troublesome areas encountered in clinical practice and evaluate the utility of molecular alterations in the diagnosis and subclassification of endometrial carcinomas. Putative prognostic markers are reviewed. The use of molecular alterations and surrogate immunohistochemistry as prognostic and predictive markers is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Fascia: a morphological description and classification system based on a literature review

PubMed Central

Kumka, Myroslava; Bonar, Jason

2012-01-01

Fascia is virtually inseparable from all structures in the body and acts to create continuity amongst tissues to enhance function and support. In the past fascia has been difficult to study leading to ambiguities in nomenclature, which have only recently been addressed. Through review of the available literature, advances in fascia research were compiled, and issues related to terminology, descriptions, and clinical relevance of fascia were addressed. Our multimodal search strategy was conducted in Medline and PubMed databases, with other targeted searches in Google Scholar and by hand, utilizing reference lists and conference proceedings. In an effort to organize nomenclature for fascial structures provided by the Federative International Committee on Anatomical Terminology (FICAT), we developed a functional classification system which includes four categories of fascia: i) linking, ii) fascicular, iii) compression, and iv) separating fasciae. Each category was developed from descriptions in the literature on gross anatomy, histology, and biomechanics; the category names reflect the function of the fascia. An up-to-date definition of fascia is provided, as well as descriptions of its function and clinical features. Our classification demonstrates the use of internationally accepted terminology in an ontology which can improve understanding of major terms in each category of fascia. PMID:22997468

The target plant concept-a history and brief overview

Treesearch

Thomas D. Landis

2011-01-01

The target plant concept originated with morphological classification of conifer nursery stock in the 1930s, and the concept was enhanced through physiological research and seedling testing towards the end of the century. Morphological grading standards such as shoot height, stem diameter, and root mass are the most common use of the target plant concept, and some...

Soil geomorphic classification, soil taxonomy, and effects on soil richness assessments

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2007-01-01

The study of pedodiversity and soil richness depends on the notion of soils as discrete entities. Soil classifications are often criticized in this regard because they depend in part on arbitrary or subjective criteria. In this study soils were categorized on the basis of the presence or absence of six lithological and morphological characteristics. Richness vs. area...

Statistical analysis and data mining of digital reconstructions of dendritic morphologies.

PubMed

Polavaram, Sridevi; Gillette, Todd A; Parekh, Ruchi; Ascoli, Giorgio A

2014-01-01

Neuronal morphology is diverse among animal species, developmental stages, brain regions, and cell types. The geometry of individual neurons also varies substantially even within the same cell class. Moreover, specific histological, imaging, and reconstruction methodologies can differentially affect morphometric measures. The quantitative characterization of neuronal arbors is necessary for in-depth understanding of the structure-function relationship in nervous systems. The large collection of community-contributed digitally reconstructed neurons available at NeuroMorpho.Org constitutes a "big data" research opportunity for neuroscience discovery beyond the approaches typically pursued in single laboratories. To illustrate these potential and related challenges, we present a database-wide statistical analysis of dendritic arbors enabling the quantification of major morphological similarities and differences across broadly adopted metadata categories. Furthermore, we adopt a complementary unsupervised approach based on clustering and dimensionality reduction to identify the main morphological parameters leading to the most statistically informative structural classification. We find that specific combinations of measures related to branching density, overall size, tortuosity, bifurcation angles, arbor flatness, and topological asymmetry can capture anatomically and functionally relevant features of dendritic trees. The reported results only represent a small fraction of the relationships available for data exploration and hypothesis testing enabled by sharing of digital morphological reconstructions.

Detailed Quantitative Classifications of Galaxy Morphology

NASA Astrophysics Data System (ADS)

Nair, Preethi

2018-01-01

Understanding the physical processes responsible for the growth of galaxies is one of the key challenges in extragalactic astronomy. The assembly history of a galaxy is imprinted in a galaxy’s detailed morphology. The bulge-to-total ratio of galaxies, the presence or absence of bars, rings, spiral arms, tidal tails etc, all have implications for the past merger, star formation, and feedback history of a galaxy. However, current quantitative galaxy classification schemes are only useful for broad binning. They cannot classify or exploit the wide variety of galaxy structures seen in nature. Therefore, comparisons of observations with theoretical predictions of secular structure formation have only been conducted on small samples of visually classified galaxies. However large samples are needed to disentangle the complex physical processes of galaxy formation. With the advent of large surveys, like the Sloan Digital Sky Survey (SDSS) and the upcoming Large Synoptic Survey Telescope (LSST) and WFIRST, the problem of statistics will be resolved. However, the need for a robust quantitative classification scheme will still remain. Here I will present early results on promising machine learning algorithms that are providing detailed classifications, identifying bars, rings, multi-armed spiral galaxies, and Hubble type.

Bivariate mass-size relation as a function of morphology as determined by Galaxy Zoo 2 crowdsourced visual classifications

NASA Astrophysics Data System (ADS)

Beck, Melanie; Scarlata, Claudia; Fortson, Lucy; Willett, Kyle; Galloway, Melanie

2016-01-01

It is well known that the mass-size distribution evolves as a function of cosmic time and that this evolution is different between passive and star-forming galaxy populations. However, the devil is in the details and the precise evolution is still a matter of debate since this requires careful comparison between similar galaxy populations over cosmic time while simultaneously taking into account changes in image resolution, rest-frame wavelength, and surface brightness dimming in addition to properly selecting representative morphological samples.Here we present the first step in an ambitious undertaking to calculate the bivariate mass-size distribution as a function of time and morphology. We begin with a large sample (~3 x 105) of SDSS galaxies at z ~ 0.1. Morphologies for this sample have been determined by Galaxy Zoo crowdsourced visual classifications and we split the sample not only by disk- and bulge-dominated galaxies but also in finer morphology bins such as bulge strength. Bivariate distribution functions are the only way to properly account for biases and selection effects. In particular, we quantify the mass-size distribution with a version of the parametric Maximum Likelihood estimator which has been modified to account for measurement errors as well as upper limits on galaxy sizes.

A Tensile Strength of Bermuda Grass and Vetiver Grass in Terms of Root Reinforcement Ability Toward Soil Slope Stabilization

NASA Astrophysics Data System (ADS)

Noorasyikin, M. N.; Zainab, M.

2016-07-01

An examination on root characteristics and root properties has been implemented in this study. Two types of bioengineering were chose which are Vetiver grass and Bermuda grass as these grasses were widely applied for slope stabilization. The root samples were taken to the laboratory to investigate its classification, characteristics and strength. The root of both grasses was found grow with fibrous root matrix system. In terms of root anchorage, the root matrix system of Vetiver grass was exhibits more strengthen than the Bermuda grass. However, observation on root image from Scanning Electron Microscope test reveals that the root of Vetiver grass becomes non-porous as the moisture content reduced. Meanwhile, the root tensile strength of Bermuda grass was obtained acquired low value with higher percentage of moisture content, root morphology and bonding strength. The results indicated that the root tensile strength is mainly influence by percentage of moisture content and root morphology.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

PubMed

Salvatore, C; Cerasa, A; Castiglioni, I; Gallivanone, F; Augimeri, A; Lopez, M; Arabia, G; Morelli, M; Gilardi, M C; Quattrone, A

2014-01-30

Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP). Morphological T1-weighted Magnetic Resonance Images (MRIs) of PD patients (28), PSP patients (28) and healthy control subjects (28) were used by a supervised machine learning algorithm based on the combination of Principal Components Analysis as feature extraction technique and on Support Vector Machines as classification algorithm. The algorithm was able to obtain voxel-based morphological biomarkers of PD and PSP. The algorithm allowed individual diagnosis of PD versus controls, PSP versus controls and PSP versus PD with an Accuracy, Specificity and Sensitivity>90%. Voxels influencing classification between PD and PSP patients involved midbrain, pons, corpus callosum and thalamus, four critical regions known to be strongly involved in the pathophysiological mechanisms of PSP. Classification accuracy of individual PSP patients was consistent with previous manual morphological metrics and with other supervised machine learning application to MRI data, whereas accuracy in the detection of individual PD patients was significantly higher with our classification method. The algorithm provides excellent discrimination of PD patients from PSP patients at an individual level, thus encouraging the application of computer-based diagnosis in clinical practice. Copyright © 2013 Elsevier B.V. All rights reserved.

Classification of inflammatory bowel diseases by means of Raman spectroscopic imaging of epithelium cells

NASA Astrophysics Data System (ADS)

Bielecki, Christiane; Bocklitz, Thomas W.; Schmitt, Michael; Krafft, Christoph; Marquardt, Claudio; Gharbi, Akram; Knösel, Thomas; Stallmach, Andreas; Popp, Juergen

2012-07-01

We report on a Raman microspectroscopic characterization of the inflammatory bowel diseases (IBD) Crohn's disease (CD) and ulcerative colitis (UC). Therefore, Raman maps of human colon tissue sections were analyzed by utilizing innovative chemometric approaches. First, support vector machines were applied to highlight the tissue morphology (=Raman spectroscopic histopathology). In a second step, the biochemical tissue composition has been studied by analyzing the epithelium Raman spectra of sections of healthy control subjects (n=11), subjects with CD (n=14), and subjects with UC (n=13). These three groups exhibit significantly different molecular specific Raman signatures, allowing establishment of a classifier (support-vector-machine). By utilizing this classifier it was possible to separate between healthy control patients, patients with CD, and patients with UC with an accuracy of 98.90%. The automatic design of both classification steps (visualization of the tissue morphology and molecular classification of IBD) paves the way for an objective clinical diagnosis of IBD by means of Raman spectroscopy in combination with chemometric approaches.

Audio-guided audiovisual data segmentation, indexing, and retrieval

NASA Astrophysics Data System (ADS)

Zhang, Tong; Kuo, C.-C. Jay

1998-12-01

While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for automatic segmentation, indexing, and retrieval of audiovisual data, based on audio content analysis. The accompanying audio signal of audiovisual data is first segmented and classified into basic types, i.e., speech, music, environmental sound, and silence. This coarse-level segmentation and indexing step is based upon morphological and statistical analysis of several short-term features of the audio signals. Then, environmental sounds are classified into finer classes, such as applause, explosions, bird sounds, etc. This fine-level classification and indexing step is based upon time- frequency analysis of audio signals and the use of the hidden Markov model as the classifier. On top of this archiving scheme, an audiovisual data retrieval system is proposed. Experimental results show that the proposed approach has an accuracy rate higher than 90 percent for the coarse-level classification, and higher than 85 percent for the fine-level classification. Examples of audiovisual data segmentation and retrieval are also provided.

Oral and Cutaneous Lymphomas other than Mycosis Fungoides and Sézary Syndrome in a Mexican Cohort: Recategorization and Evaluation of International Geographical Disparities

PubMed Central

Hernández-Salazar, Amparo; García-Vera, Jorge Andrés; Charli-Joseph, Yann; Ortiz-Pedroza, Guadalupe; Méndez-Flores, Silvia; Orozco-Topete, Rocío; Morales-Leyte, Ana Lilia; Domínguez-Cherit, Judith; Lome-Maldonado, Carmen

2017-01-01

Background: Nonmycosis fungoides/Sézary syndrome (non-MF/SS) primary cutaneous lymphomas (PCL) are currently categorized under the 2005-World Health Organization/European Organization for Research and Treatment of Cancer (WHO-EORTC) classification for PCL. These differ in behavior from secondary cutaneous lymphomas (SCL) and to lymphomas limited to the oral cavity (primary oral lymphomas [POL]) both categorized under the 2016-WHO classification for lymphoid neoplasms. Aims: This study aims to report the first series of non-MF/SS PCL, SCL, and POL in a Mexican cohort, examine the applicability of current classification systems and compare our findings with those from foreign cohorts. Materials and Methods: Eighteen non-MF/SS PCL, four SCL, and two POL with available tissue for morphology and immunophenotypic assessment were reclassified according to the 2005-WHO/EORTC and 2016-WHO classifications. Results: Non-MF/SS PCLs were primarily of T-cell origin (61%) where CD30+ lymphoproliferative disorders predominated, followed by Epstein–Barr virus-induced lymphomas, and peripheral T-cell lymphomas, not otherwise specified. Primary cutaneous B-cell lymphomas (BCL) were primarily of follicle center cell origin followed by postgerminal lymphomas of the diffuse large BCL variety. Conclusions: Most non-MF/SS PCL, SCL, and POL can be adequately categorized according to the 2005-WHO/EORTC and 2016-WHO classification systems, even when dealing with clinically atypical cases. The relative frequencies in our cohort hold closer similarities to Asian registries than from those of Europe/USA, supporting the concept of individual and/or racial susceptibility, and the notion of geographical variances in the rate of lymphomas. In particular, such disparity may arise from viral-induced lymphomas which might show partial geographical restriction. PMID:28400635

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

PubMed

Shirahata, Mitsuaki; Iwao-Koizumi, Kyoko; Saito, Sakae; Ueno, Noriko; Oda, Masashi; Hashimoto, Nobuo; Takahashi, Jun A; Kato, Kikuya

2007-12-15

Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

Analysis of the English morphology by semantic networks

NASA Astrophysics Data System (ADS)

Žáček, Martin; Homola, Dan

2017-11-01

The article is devoted to study the morphology of natural language, in this case English language. The research is of the language is from the perspective of knowledge representation, when we look at the word as a concept in the Concept languages. The research is in the relationship of the individual words and their classification in the sentence. For the analysis there are used several methods (syntax, lexical categories, morphology). This article focuses mainly on the word, as the foundation of every natural language (English).

Automatic Picking of Foraminifera: Design of the Foraminifera Image Recognition and Sorting Tool (FIRST) Prototype and Results of the Image Classification Scheme

NASA Astrophysics Data System (ADS)

de Garidel-Thoron, T.; Marchant, R.; Soto, E.; Gally, Y.; Beaufort, L.; Bolton, C. T.; Bouslama, M.; Licari, L.; Mazur, J. C.; Brutti, J. M.; Norsa, F.

2017-12-01

Foraminifera tests are the main proxy carriers for paleoceanographic reconstructions. Both geochemical and taxonomical studies require large numbers of tests to achieve statistical relevance. To date, the extraction of foraminifera from the sediment coarse fraction is still done by hand and thus time-consuming. Moreover, the recognition of morphotypes, ecologically relevant, requires some taxonomical skills not easily taught. The automatic recognition and extraction of foraminifera would largely help paleoceanographers to overcome these issues. Recent advances in automatic image classification using machine learning opens the way to automatic extraction of foraminifera. Here we detail progress on the design of an automatic picking machine as part of the FIRST project. The machine handles 30 pre-sieved samples (100-1000µm), separating them into individual particles (including foraminifera) and imaging each in pseudo-3D. The particles are classified and specimens of interest are sorted either for Individual Foraminifera Analyses (44 per slide) and/or for classical multiple analyses (8 morphological classes per slide, up to 1000 individuals per hole). The classification is based on machine learning using Convolutional Neural Networks (CNNs), similar to the approach used in the coccolithophorid imaging system SYRACO. To prove its feasibility, we built two training image datasets of modern planktonic foraminifera containing approximately 2000 and 5000 images each, corresponding to 15 & 25 morphological classes. Using a CNN with a residual topology (ResNet) we achieve over 95% correct classification for each dataset. We tested the network on 160,000 images from 45 depths of a sediment core from the Pacific ocean, for which we have human counts. The current algorithm is able to reproduce the downcore variability in both Globigerinoides ruber and the fragmentation index (r2 = 0.58 and 0.88 respectively). The FIRST prototype yields some promising results for high-resolution paleoceanographic studies and evolutionary studies.

Genetic, morphological, and acoustic evidence reveals lack of diversification in the colonization process in an island bird.

PubMed

Illera, Juan Carlos; Palmero, Ana M; Laiolo, Paola; Rodríguez, Felipe; Moreno, Ángel C; Navascués, Miguel

2014-08-01

Songbirds with recently (i.e., early Holocene) founded populations are suitable models for studying incipient differentiation in oceanic islands. On such systems each colonization event represents a different evolutionary episode that can be studied by addressing sets of diverging phenotypic and genetic traits. We investigate the process of early differentiation in the spectacled warbler (Sylvia conspicillata) in 14 populations separated by sea barriers from three Atlantic archipelagos and from continental regions spanning from tropical to temperate latitudes. Our approach involved the study of sexual acoustic signals, morphology, and genetic data. Mitochondrial DNA did not provide clear population structure. However, microsatellites analyses consistently identified two genetic groups, albeit without correspondence to subspecies classification and little correspondence to geography. Coalescent analyses showed significant evidence for gene flow between the two genetic groups. Discriminant analyses could not correctly assign morphological or acoustic traits to source populations. Therefore, although theory predicting that in isolated populations genetic, morphological, or acoustic traits can lead to radiation, we have strikingly failed to document differentiation on these attributes in a resident passerine throughout three oceanic archipelagos. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Olfactory organ of Octopus vulgaris: morphology, plasticity, turnover and sensory characterization

PubMed Central

Polese, Gianluca; Bertapelle, Carla

2016-01-01

ABSTRACT The cephalopod olfactory organ was described for the first time in 1844 by von Kölliker, who was attracted to the pair of small pits of ciliated cells on each side of the head, below the eyes close to the mantle edge, in both octopuses and squids. Several functional studies have been conducted on decapods but very little is known about octopods. The morphology of the octopus olfactory system has been studied, but only to a limited extent on post-hatching specimens, and the only paper on adult octopus gives a minimal description of the olfactory organ. Here, we describe the detailed morphology of young male and female Octopus vulgaris olfactory epithelium, and using a combination of classical morphology and 3D reconstruction techniques, we propose a new classification for O. vulgaris olfactory sensory neurons. Furthermore, using specific markers such as olfactory marker protein (OMP) and proliferating cell nuclear antigen (PCNA) we have been able to identify and differentially localize both mature olfactory sensory neurons and olfactory sensory neurons involved in epithelium turnover. Taken together, our data suggest that the O. vulgaris olfactory organ is extremely plastic, capable of changing its shape and also proliferating its cells in older specimens. PMID:27069253

A Descriptive Genetic Classification for Glaciovolcanoes

NASA Astrophysics Data System (ADS)

Edwards, B. R.; Russell, K.; Porritt, L. A.

2014-12-01

We review the recently published descriptive genetic classification for glaciovolcanoes (Russell et al., Quat Sci Rv, 2014). The new classification uses 'tuya' as a root word for all glaciovolcanic edifices, and with modifiers that make the classification descriptive (e.g., andesitic, lava-dominated, flat topped tuya). Although tuyas can range in composition from basaltic to rhyolitic, many of the characteristics diagnostic of glaciovolcanic environments are largely independent of lava composition (e.g., edifice morphology, columnar jointing patterns, glass distributions, pyroclast shapes). Tuya subtypes are first classified on the basis of variations in edifice-scale morphologies (e.g., conical tuya) then, on the proportions of the essential lithofacies (e.g., tephra-dominated conical tuya), and lastly on magma composition (e.g., basaltic, tephra-dominated, conical tuya). The lithofacies associations within tuyas broadly record the interplay between magmatic and glaciohydraulic conditions extent during the active phases of the eruption, including the dominant style of eruption (e.g., explosive vs. effusive). We present nine distinct, endmember models for glaciovolcanic edifices that simultaneously record changes in eruption conditions (explosive, transitional, effusive) for different general glaciohydraulic conditions (closed/sealed, leaky/partly sealed, open/well-drained). To date we have identified potential examples for 7 of the 9 models. Use of a simplified, descriptive classification scheme for glaciovolcanoes will facilitate communications amongst volcanologists and planetary scientists and the use of tuyas for recovering critical paleo-environmental information, particularly the local glaciohydraulics extent during eruptions.

A molecular phylogeny of the nightjars (Aves: Caprimulgidae) suggests extensive conservation of primitive morphological traits across multiple lineages.

PubMed

Larsen, Carl; Speed, Michael; Harvey, Nicholas; Noyes, Harry A

2007-03-01

We report a molecular re-assessment of the classification of the nightjars which draws conclusions that are strongly at odds with the traditional, morphology-based classifications. We used maximum likelihood and Bayesian methods to compare the cytochrome b gene for 14 species from seven of the 15 genera of the Caprimulgidae and partial cytochrome b sequence data was available for a further seven species including three further genera. We found that within the Caprimulgidae there were four geographically isolated clades with bootstrap support greater than 70%. One of these clades contained just Chordeiles species, the remaining three clades each contained a mixture of genera including Caprimulgus sp. A clade of exclusively South American nightjars included the genera Caprimulgus, Uropsalis, Eleopthreptus and Hydropsalis. A clade of African and Eurasian birds included Caprimulgus and Macrodipteryx. Phalaenoptilus nuttallii and Caprimulgus vociferous formed a clade of North American birds. Two ecological factors appear to make morphological classification potentially misleading: first, the apparent retention of primitive anti-predator and foraging-related traits across genetically divergent groups; second, rapid divergence in other traits, especially those related to mating, which generate high levels of morphological divergence between species that are genetically very similar. The cytochrome b data suggests that the genus Caprimulgus is not monophyletic and is restricted to Africa and Eurasia and that Caprimulgus species from outside this area have been misclassified as a consequence of retention of primitive adaptations for crepuscular/nocturnal living. Some other genera also appear to have little support from the cytochrome b data.

Extraction and Classification of Human Gait Features

NASA Astrophysics Data System (ADS)

Ng, Hu; Tan, Wooi-Haw; Tong, Hau-Lee; Abdullah, Junaidi; Komiya, Ryoichi

In this paper, a new approach is proposed for extracting human gait features from a walking human based on the silhouette images. The approach consists of six stages: clearing the background noise of image by morphological opening; measuring of the width and height of the human silhouette; dividing the enhanced human silhouette into six body segments based on anatomical knowledge; applying morphological skeleton to obtain the body skeleton; applying Hough transform to obtain the joint angles from the body segment skeletons; and measuring the distance between the bottom of right leg and left leg from the body segment skeletons. The angles of joints, step-size together with the height and width of the human silhouette are collected and used for gait analysis. The experimental results have demonstrated that the proposed system is feasible and achieved satisfactory results.

Morphological feature extraction for the classification of digital images of cancerous tissues.

PubMed

Thiran, J P; Macq, B

1996-10-01

This paper presents a new method for automatic recognition of cancerous tissues from an image of a microscopic section. Based on the shape and the size analysis of the observed cells, this method provides the physician with nonsubjective numerical values for four criteria of malignancy. This automatic approach is based on mathematical morphology, and more specifically on the use of Geodesy. This technique is used first to remove the background noise from the image and then to operate a segmentation of the nuclei of the cells and an analysis of their shape, their size, and their texture. From the values of the extracted criteria, an automatic classification of the image (cancerous or not) is finally operated.

[Analysis of an ophthalmic pathology cohort of human fetal eyes with regard to interesting findings].

PubMed

Herwig, M C; Müller, A M; Holz, F G; Loeffler, K U

2010-11-01

Information on the evaluation of prenatal ocular findings is sparse. This article provides an overview of the morphology in a cohort of human fetal eyes, with particular emphasis on interesting findings. The study investigated 216 eyes from 115 human fetuses. The majority of fetal eyes presented with a regular phenotype. Rarely, unexpected findings were discovered in fetuses with or without systemic malformations. Routine evaluation of fetal eyes reveals-albeit rarely-new aspects providing further knowledge and occasionally enabling the exact classification of syndromes.

Phylogenetic Status of an Unrecorded Species of Curvularia, C. spicifera, Based on Current Classification System of Curvularia and Bipolaris Group Using Multi Loci.

PubMed

Jeon, Sun Jeong; Nguyen, Thi Thuong Thuong; Lee, Hyang Burm

2015-09-01

A seed-borne fungus, Curvularia sp. EML-KWD01, was isolated from an indigenous wheat seed by standard blotter method. This fungus was characterized based on the morphological characteristics and molecular phylogenetic analysis. Phylogenetic status of the fungus was determined using sequences of three loci: rDNA internal transcribed spacer, large ribosomal subunit, and glyceraldehyde 3-phosphate dehydrogenase gene. Multi loci sequencing analysis revealed that this fungus was Curvularia spicifera within Curvularia group 2 of family Pleosporaceae.

Arm structure in normal spiral galaxies, 1: Multivariate data for 492 galaxies

NASA Technical Reports Server (NTRS)

Magri, Christopher

1994-01-01

Multivariate data have been collected as part of an effort to develop a new classification system for spiral galaxies, one which is not necessarily based on subjective morphological properties. A sample of 492 moderately bright northern Sa and Sc spirals was chosen for future statistical analysis. New observations were made at 20 and 21 cm; the latter data are described in detail here. Infrared Astronomy Satellite (IRAS) fluxes were obtained from archival data. Finally, new estimates of arm pattern radomness and of local environmental harshness were compiled for most sample objects.

The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System.

PubMed

Epstein, Jonathan I; Egevad, Lars; Amin, Mahul B; Delahunt, Brett; Srigley, John R; Humphrey, Peter A

2016-02-01

In November, 2014, 65 prostate cancer pathology experts, along with 17 clinicians including urologists, radiation oncologists, and medical oncologists from 19 different countries gathered in a consensus conference to update the grading of prostate cancer, last revised in 2005. The major conclusions were: (1) Cribriform glands should be assigned a Gleason pattern 4, regardless of morphology; (2) Glomeruloid glands should be assigned a Gleason pattern 4, regardless of morphology; (3) Grading of mucinous carcinoma of the prostate should be based on its underlying growth pattern rather than grading them all as pattern 4; and (4) Intraductal carcinoma of the prostate without invasive carcinoma should not be assigned a Gleason grade and a comment as to its invariable association with aggressive prostate cancer should be made. Regarding morphologies of Gleason patterns, there was clear consensus on: (1) Gleason pattern 4 includes cribriform, fused, and poorly formed glands; (2) The term hypernephromatoid cancer should not be used; (3) For a diagnosis of Gleason pattern 4, it needs to be seen at 10x lens magnification; (4) Occasional/seemingly poorly formed or fused glands between well-formed glands is insufficient for a diagnosis of pattern 4; (5) In cases with borderline morphology between Gleason pattern 3 and pattern 4 and crush artifacts, the lower grade should be favored; (6) Branched glands are allowed in Gleason pattern 3; (7) Small solid cylinders represent Gleason pattern 5; (8) Solid medium to large nests with rosette-like spaces should be considered to represent Gleason pattern 5; and (9) Presence of unequivocal comedonecrosis, even if focal is indicative of Gleason pattern 5. It was recognized by both pathologists and clinicians that despite the above changes, there were deficiencies with the Gleason system. The Gleason grading system ranges from 2 to 10, yet 6 is the lowest score currently assigned. When patients are told that they have a Gleason score 6 out of 10, it implies that their prognosis is intermediate and contributes to their fear of having a more aggressive cancer. Also, in the literature and for therapeutic purposes, various scores have been incorrectly grouped together with the assumption that they have a similar prognosis. For example, many classification systems consider Gleason score 7 as a single score without distinguishing 3+4 versus 4+3, despite studies showing significantly worse prognosis for the latter. The basis for a new grading system was proposed in 2013 by one of the authors (J.I.E.) based on data from Johns Hopkins Hospital resulting in 5 prognostically distinct Grade Groups. This new system was validated in a multi-institutional study of over 20,000 radical prostatectomy specimens, over 16,000 needle biopsy specimens, and over 5,000 biopsies followed by radiation therapy. There was broad (90%) consensus for the adoption of this new prostate cancer Grading system in the 2014 consensus conference based on: (1) the new classification provided more accurate stratification of tumors than the current system; (2) the classification simplified the number of grading categories from Gleason scores 2 to 10, with even more permutations based on different pattern combinations, to Grade Groups 1 to 5; (3) the lowest grade is 1 not 6 as in Gleason, with the potential to reduce overtreatment of indolent cancer; and (4) the current modified Gleason grading, which forms the basis for the new grade groups, bears little resemblance to the original Gleason system. The new grades would, for the foreseeable future, be used in conjunction with the Gleason system [ie. Gleason score 3+3=6 (Grade Group 1)]. The new grading system and the terminology Grade Groups 1-5 have also been accepted by the World Health Organization for the 2016 edition of Pathology and Genetics: Tumours of the Urinary System and Male Genital Organs.

Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty.

PubMed

Mihaljević, Bojan; Bielza, Concha; Benavides-Piccione, Ruth; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists' classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial

PubMed Central

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-01-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the classification assesses a sideward displacement including the respective displacement sector at the neck or base fracture site as well as the angulation of the superior main fragment and also considers a potential displacement of the caudal fragment with regard to the fossa, which may occur in fractures affecting additional fracture locations in the mandible. The design of this classification is discussed along with a review of existing classification systems. The condylar process for fracture location was defined according to the level 2 system presented in a previous tutorial in this special issue. PMID:25489390

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial.

PubMed

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-12-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the classification assesses a sideward displacement including the respective displacement sector at the neck or base fracture site as well as the angulation of the superior main fragment and also considers a potential displacement of the caudal fragment with regard to the fossa, which may occur in fractures affecting additional fracture locations in the mandible. The design of this classification is discussed along with a review of existing classification systems. The condylar process for fracture location was defined according to the level 2 system presented in a previous tutorial in this special issue.

Development of a Support Vector Machine - Based Image Analysis System for Focal Liver Lesions Classification in Magnetic Resonance Images

NASA Astrophysics Data System (ADS)

Gatos, I.; Tsantis, S.; Karamesini, M.; Skouroliakou, A.; Kagadis, G.

2015-09-01

Purpose: The design and implementation of a computer-based image analysis system employing the support vector machine (SVM) classifier system for the classification of Focal Liver Lesions (FLLs) on routine non-enhanced, T2-weighted Magnetic Resonance (MR) images. Materials and Methods: The study comprised 92 patients; each one of them has undergone MRI performed on a Magnetom Concerto (Siemens). Typical signs on dynamic contrast-enhanced MRI and biopsies were employed towards a three class categorization of the 92 cases: 40-benign FLLs, 25-Hepatocellular Carcinomas (HCC) within Cirrhotic liver parenchyma and 27-liver metastases from Non-Cirrhotic liver. Prior to FLLs classification an automated lesion segmentation algorithm based on Marcov Random Fields was employed in order to acquire each FLL Region of Interest. 42 texture features derived from the gray-level histogram, co-occurrence and run-length matrices and 12 morphological features were obtained from each lesion. Stepwise multi-linear regression analysis was utilized to avoid feature redundancy leading to a feature subset that fed the multiclass SVM classifier designed for lesion classification. SVM System evaluation was performed by means of leave-one-out method and ROC analysis. Results: Maximum accuracy for all three classes (90.0%) was obtained by means of the Radial Basis Kernel Function and three textural features (Inverse- Different-Moment, Sum-Variance and Long-Run-Emphasis) that describe lesion's contrast, variability and shape complexity. Sensitivity values for the three classes were 92.5%, 81.5% and 96.2% respectively, whereas specificity values were 94.2%, 95.3% and 95.5%. The AUC value achieved for the selected subset was 0.89 with 0.81 - 0.94 confidence interval. Conclusion: The proposed SVM system exhibit promising results that could be utilized as a second opinion tool to the radiologist in order to decrease the time/cost of diagnosis and the need for patients to undergo invasive examination.

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

PubMed

Ramírez, J; Górriz, J M; Ortiz, A; Martínez-Murcia, F J; Segovia, F; Salas-Gonzalez, D; Castillo-Barnes, D; Illán, I A; Puntonet, C G

2018-05-15

Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have suggested that people with MCI tend to progress to AD at a rate of about 10-15% per year. However, the ability of clinicians and machine learning systems to predict AD based on MRI biomarkers at an early stage is still a challenging problem that can have a great impact in improving treatments. The proposed system, developed by the SiPBA-UGR team for this challenge, is based on feature standardization, ANOVA feature selection, partial least squares feature dimension reduction and an ensemble of One vs. Rest random forest classifiers. With the aim of improving its performance when discriminating healthy controls (HC) from MCI, a second binary classification level was introduced that reconsiders the HC and MCI predictions of the first level. The system was trained and evaluated on an ADNI datasets that consist of T1-weighted MRI morphological measurements from HC, stable MCI, converter MCI and AD subjects. The proposed system yields a 56.25% classification score on the test subset which consists of 160 real subjects. The classifier yielded the best performance when compared to: (i) One vs. One (OvO), One vs. Rest (OvR) and error correcting output codes (ECOC) as strategies for reducing the multiclass classification task to multiple binary classification problems, (ii) support vector machines, gradient boosting classifier and random forest as base binary classifiers, and (iii) bagging ensemble learning. A robust method has been proposed for the international challenge on MCI prediction based on MRI data. The system yielded the second best performance during the competition with an accuracy rate of 56.25% when evaluated on the real subjects of the test set. Copyright © 2017 Elsevier B.V. All rights reserved.

CANDELS Visual Classifications: Scheme, Data Release, and First Results

NASA Astrophysics Data System (ADS)

Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Harry; Koo, David; Bassett, Robert; Bernyk, Maksym; Blancato, Kirsten; Bournaud, Frederic; Cassata, Paolo; Castellano, Marco; Cheung, Edmond; Conselice, Christopher J.; Croton, Darren; Dahlen, Tomas; de Mello, Duilia F.; DeGroot, Laura; Donley, Jennifer; Guedes, Javiera; Grogin, Norman; Hathi, Nimish; Hilton, Matt; Hollon, Brett; Koekemoer, Anton; Liu, Nick; Lucas, Ray A.; Martig, Marie; McGrath, Elizabeth; McPartland, Conor; Mobasher, Bahram; Morlock, Alice; O'Leary, Erin; Peth, Mike; Pforr, Janine; Pillepich, Annalisa; Rosario, David; Soto, Emmaris; Straughn, Amber; Telford, Olivia; Sunnquist, Ben; Trump, Jonathan; Weiner, Benjamin; Wuyts, Stijn; Inami, Hanae; Kassin, Susan; Lani, Caterina; Poole, Gregory B.; Rizer, Zachary

2015-11-01

We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H < 24.5 involving the dedicated efforts of over 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies spanning 0 < z < 4 over all the fields, with classifications from 3 to 5 independent classifiers for each galaxy. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, k-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed—GOODS-S, which has been classified at various depths. The wide area coverage spanning the full field (wide+deep+ERS) includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all of the visual classifications in GOODS-S along with the Perl/Tk GUI that we developed to classify galaxies. We present our initial results here, including an analysis of our internal consistency and comparisons among multiple classifiers as well as a comparison to the Sérsic index. We find that the level of agreement among classifiers is quite good (>70% across the full magnitude range) and depends on both the galaxy magnitude and the galaxy type, with disks showing the highest level of agreement (>50%) and irregulars the lowest (<10%). A comparison of our classifications with the Sérsic index and rest-frame colors shows a clear separation between disk and spheroid populations. Finally, we explore morphological k-corrections between the V-band and H-band observations and find that a small fraction (84 galaxies in total) are classified as being very different between these two bands. These galaxies typically have very clumpy and extended morphology or are very faint in the V-band.

A morphologic characterisation of the 1963 Vajont Slide, Italy, using long-range terrestrial photogrammetry

NASA Astrophysics Data System (ADS)

Wolter, Andrea; Stead, Doug; Clague, John J.

2014-02-01

The 1963 Vajont Slide in northeast Italy is an important engineering and geological event. Although the landslide has been extensively studied, new insights can be derived by applying modern techniques such as remote sensing and numerical modelling. This paper presents the first digital terrestrial photogrammetric analyses of the failure scar, landslide deposits, and the area surrounding the failure, with a focus on the scar. We processed photogrammetric models to produce discontinuity stereonets, residual maps and profiles, and slope and aspect maps, all of which provide information on the failure scar morphology. Our analyses enabled the creation of a preliminary semi-quantitative morphologic classification of the Vajont failure scar based on the large-scale tectonic folds and step-paths that define it. The analyses and morphologic classification have implications for the kinematics, dynamics, and mechanism of the slide. Metre- and decametre-scale features affected the initiation, direction, and displacement rate of sliding. The most complexly folded and stepped areas occur close to the intersection of orthogonal synclinal features related to the Dinaric and Neoalpine deformation events. Our analyses also highlight, for the first time, the evolution of the Vajont failure scar from 1963 to the present.

CANDELS Visual Classifications: Scheme, Data Release, and First Results

NASA Technical Reports Server (NTRS)

Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Henry; Koo, David; Bassett, Robert;

Involvement of the central somatosensory system in restless legs syndrome: A neuroimaging study.

PubMed

Lee, Byeong-Yeul; Kim, Jongmyeong; Connor, James R; Podskalny, Gerald D; Ryu, Yeunchul; Yang, Qing X

2018-05-22

To investigate morphologic changes in the somatosensory cortex and the thickness of the corpus callosum subdivisions that provide interhemispheric connections between the 2 somatosensory cortical areas. Twenty-eight patients with severe restless legs syndrome (RLS) symptoms and 51 age-matched healthy controls were examined with high-resolution MRI at 3.0 tesla. The vertex-wise analysis in conjunction with a novel cortical surface classification method was performed to assess the cortical thickness across the whole-brain structures. In addition, the thickness of the midbody of the corpus callosum that links postcentral gyri in the 2 hemispheres was measured. We demonstrated that a morphologic change occurred in the brain somatosensory system in patients with RLS compared to controls. Patients with RLS exhibited a 7.5% decrease in average cortical thickness in the bilateral postcentral gyrus ( p < 0.0001). Accordingly, there was a substantial decrease in the corpus callosum posterior midbody ( p < 0.008) wherein the callosal fibers are connected to the postcentral gyrus, suggesting altered white matter properties in the somatosensory pathway. Our results provide in vivo evidence of morphologic changes in the primary somatosensory system, which could be responsible for the sensory functional symptoms of RLS. These results provide a better understanding of the pathophysiology underlying the RLS sensory symptoms and could lead to a potential imaging marker for RLS. © 2018 American Academy of Neurology.

Land use survey and mapping and water resources investigation in Korea

NASA Technical Reports Server (NTRS)

Choi, J. H.; Kim, W. I.; Son, D. S. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Land use imagery is applicable to land use classification for small scale land use mapping less than 1:250,000. Land use mapping by satellite is more efficient and more cost-effective than land use mapping from conventional medium altitude aerial photographs. Six categories of level 1 land use classification are recognizable from MSS imagery. A hydrogeomorphological study of the Han River basin indicates that band 7 is useful for recognizing the soil and the weathering part of bed rock. The morphological change of the main river is accurately recognized and the drainage system in the area observed is easily classified because of the more or less simple rock type. Although the direct hydrological characteristics are not obtained from the MSS imagery, the indirect information such as the permeability of the soil and the vegetation cover, is helpful in interpreting the hydrological aspects.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Galaxy And Mass Assembly: automatic morphological classification of galaxies using statistical learning

NASA Astrophysics Data System (ADS)

Sreejith, Sreevarsha; Pereverzyev, Sergiy, Jr.; Kelvin, Lee S.; Marleau, Francine R.; Haltmeier, Markus; Ebner, Judith; Bland-Hawthorn, Joss; Driver, Simon P.; Graham, Alister W.; Holwerda, Benne W.; Hopkins, Andrew M.; Liske, Jochen; Loveday, Jon; Moffett, Amanda J.; Pimbblet, Kevin A.; Taylor, Edward N.; Wang, Lingyu; Wright, Angus H.

2018-03-01

We apply four statistical learning methods to a sample of 7941 galaxies (z < 0.06) from the Galaxy And Mass Assembly survey to test the feasibility of using automated algorithms to classify galaxies. Using 10 features measured for each galaxy (sizes, colours, shape parameters, and stellar mass), we apply the techniques of Support Vector Machines, Classification Trees, Classification Trees with Random Forest (CTRF) and Neural Networks, and returning True Prediction Ratios (TPRs) of 75.8 per cent, 69.0 per cent, 76.2 per cent, and 76.0 per cent, respectively. Those occasions whereby all four algorithms agree with each other yet disagree with the visual classification (`unanimous disagreement') serves as a potential indicator of human error in classification, occurring in ˜ 9 per cent of ellipticals, ˜ 9 per cent of little blue spheroids, ˜ 14 per cent of early-type spirals, ˜ 21 per cent of intermediate-type spirals, and ˜ 4 per cent of late-type spirals and irregulars. We observe that the choice of parameters rather than that of algorithms is more crucial in determining classification accuracy. Due to its simplicity in formulation and implementation, we recommend the CTRF algorithm for classifying future galaxy data sets. Adopting the CTRF algorithm, the TPRs of the five galaxy types are : E, 70.1 per cent; LBS, 75.6 per cent; S0-Sa, 63.6 per cent; Sab-Scd, 56.4 per cent, and Sd-Irr, 88.9 per cent. Further, we train a binary classifier using this CTRF algorithm that divides galaxies into spheroid-dominated (E, LBS, and S0-Sa) and disc-dominated (Sab-Scd and Sd-Irr), achieving an overall accuracy of 89.8 per cent. This translates into an accuracy of 84.9 per cent for spheroid-dominated systems and 92.5 per cent for disc-dominated systems.

The evolutionary history of Mimosa (Leguminosae): toward a phylogeny of the sensitive plants.

PubMed

Simon, Marcelo F; Grether, Rosaura; de Queiroz, Luciano P; Särkinen, Tiina E; Dutra, Valquíria F; Hughes, Colin E

2011-07-01

Large genera provide remarkable opportunities to investigate patterns of morphological evolution and historical biogeography in plants. A molecular phylogeny of the species-rich and morphologically and ecologically diverse genus Mimosa was generated to evaluate its infrageneric classification, reconstruct the evolution of a set of morphological characters, and establish the relationships of Old World species to the rest of the genus. We used trnD-trnT plastid sequences for 259 species of Mimosa (ca. 50% of the total) to reconstruct the phylogeny of the genus. Six morphological characters (petiolar nectary, inflorescence type, number of stamens, number of petals, pollen type, and seismonasty) were optimized onto the molecular tree. Mimosa was recovered as a monophyletic clade nested within the Piptadenia group and includes the former members of Schrankia, corroborating transfer of that genus to Mimosa. Although we found good support for several infrageneric groups, only one section (Mimadenia) was recovered as monophyletic. All but one of the morphological characters analyzed showed high levels of homoplasy. High levels of geographic structure were found, with species from the same area tending to group together in the phylogeny. Old World species of Mimosa form a monophyletic clade deeply nested within New World groups, indicating recent (6-10 Ma) long-distance dispersal. Although based on a single plastid region, our results establish a preliminary phylogenetic framework for Mimosa that can be used to infer patterns of morphological evolution and relationships and which provides pointers toward a revised infrageneric classification.

Molecular Phylogenies Support Homoplasy of Multiple Morphological Characters Used in the Taxonomy of Heteroscleromorpha (Porifera: Demospongiae)

PubMed Central

Morrow, Christine C.; Redmond, Niamh E.; Picton, Bernard E.; Thacker, Robert W.; Collins, Allen G.; Maggs, Christine A.; Sigwart, Julia D.; Allcock, A. Louise

2013-01-01

Sponge classification has long been based mainly on morphocladistic analyses but is now being greatly challenged by more than 12 years of accumulated analyses of molecular data analyses. The current study used phylogenetic hypotheses based on sequence data from 18S rRNA, 28S rRNA, and the CO1 barcoding fragment, combined with morphology to justify the resurrection of the order Axinellida Lévi, 1953. Axinellida occupies a key position in different morphologically derived topologies. The abandonment of Axinellida and the establishment of Halichondrida Vosmaer, 1887 sensu lato to contain Halichondriidae Gray, 1867, Axinellidae Carter, 1875, Bubaridae Topsent, 1894, Heteroxyidae Dendy, 1905, and a new family Dictyonellidae van Soest et al., 1990 was based on the conclusion that an axially condensed skeleton evolved independently in separate lineages in preference to the less parsimonious assumption that asters (star-shaped spicules), acanthostyles (club-shaped spicules with spines), and sigmata (C-shaped spicules) each evolved more than once. Our new molecular trees are congruent and contrast with the earlier, morphologically based, trees. The results show that axially condensed skeletons, asters, acanthostyles, and sigmata are all homoplasious characters. The unrecognized homoplasious nature of these characters explains much of the incongruence between molecular-based and morphology-based phylogenies. We use the molecular trees presented here as a basis for re-interpreting the morphological characters within Heteroscleromorpha. The implications for the classification of Heteroscleromorpha are discussed and a new order Biemnida ord. nov. is erected. PMID:23753661

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

PubMed

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Cognition, culture and utility: plant classification by Paraguayan immigrant farmers in Misiones, Argentina.

PubMed

Kujawska, Monika; Jiménez-Escobar, N David; Nolan, Justin M; Arias-Mutis, Daniel

2017-07-25

This study was conducted in three rural communities of small farmers of Paraguayan origin living in the province of Misiones, Argentina. These Criollos (Mestizos) hail chiefly from departments located in the east of Paraguay, where the climate and flora have similar characteristics as those in Misiones. These ecological features contribute to the continuation and maintenance of knowledge and practices related to the use of plants. Fieldwork was conducted between September 2014 and August 2015. Forty five informants from three rural localities situated along the Parana River participated in an ethno-classification task. For the classification event, photographs of 30 medicinal and edible plants were chosen, specifically those yielding the highest frequency of mention among the members of that community (based on data obtained in the first stage of research in 2014). Variation in local plant classifications was examined and compared using principal component analysis and cluster analysis. We found that people classify plants according to application or use (primarily medicinal, to a lesser extent as edible). Morphology is rarely taken into account, even for very similar and closely-related species such as varieties of palms. In light of our findings, we highlight a dominant functionality model at work in the process of plant cognition and classification among farmers of Paraguayan origin. Salient cultural beliefs and practices associated with rural Paraguayan plant-based medicine are described. Additionally, the manner by which residents' concepts of plants articulate with local folk epistemology is discussed. Culturally constructed use patterns ultimately override morphological variables in rural Paraguayans' ethnobotanical classification.

Telangiectasia macularis eruptiva perstans: more than skin deep

PubMed Central

Watkins, Casey E.; Bokor, Winston B.; Leicht, Stuart; Youngberg, George; Krishnaswamy, Guha

2011-01-01

Systemic mastocytosis is a rare disease involving the infiltration and accumulation of active mast cells within any organ system. By far, the most common organ affected is the skin. Cutaneous manifestations of mastocytosis, including Urticaria Pigmentosa (UP), cutaneous mastocytoma or telangiectasia macularis eruptive perstans (TMEP), may indicate a more serious and potentially life-threatening underlying disease. The presence of either UP or TMEP in a patient with anaphylactic symptoms should suggest the likelihood of systemic mastocytosis, with the caveat that systemic complications are more likely to occur in patients with UP. TMEP can usually be identified by the typical morphology, but a skin biopsy is confirmative. In patients with elevated tryptase levels or those with frequent systemic manifestations, a bone marrow biopsy is essential in order to demonstrate mast cell infiltration. Further genetic testing for mutations of c-kit gene or the FIP1L1 gene may help with disease classification and/or therapeutic approaches. Rarely, TMEP has been described with malignancy, radiation therapy, and myeloproliferative disorders. A few familial cases have also been described. In this review, we discuss the clinical features, diagnosis and management of patients with TMEP. We also discuss the possible molecular pathogenesis and the role of genetics in disease classification and treatment. PMID:25386256

An alternative didactic, functional and topographic systematization of the spinal muscles.

PubMed

de Araújo Baptista, Vivianne Izabelle; Mayer, William Paganini; Eustáquio da Silva, Ricardo; de Vasconcellos Fontes, Ricardo Bragança; da Silva Baptista, Josemberg

2017-09-01

Back muscles are commonly described in a topographically-oriented manner without necessarily following morphological criteria. In this manner, non-standard terms may be employed which convey incorrect morphological concepts and demanding more time from both faculty and students to transmit knowledge. We propose a classification system for spinal muscles incorporating morphological concepts with the goal of facilitating knowledge transfer and suggest the term "spinal muscles". Those muscles were systematically divided and classified in seven strata from anterior to posterior: vertebro-appendicular (VA), transversarium (Tr), deep post-transversarium (DPT), middle post-transversarium (MPT), superficial post-transversarium (SPT), deep spino-appendicular (DSA) and superficial spino-appendicular (SSA). Besides topography and function, this system incorporates innervation and embryological origins of each muscle. The extrinsic (VA, DSA, SSA) or intrinsic (Tr, DPT, MPT, SPT) nature of these muscles in relation to the spine and also the topographic relationship to the transverse process is represented in this system. Specific areas of functional, nervous and developmental transition exist on Tr and DPT strata due to being adjacent to extrinsic strata. We believe this system represents a more modern and concise teaching strategy for back muscles which may be employed partially or fully within any program. We envision its full version may be particularly useful in postgraduate medical training for specialties dealing with the spinal column such as neurosurgery, orthopedic surgery and physical medicine and rehabilitation. Copyright © 2017 Elsevier GmbH. All rights reserved.

Molecular Phylogeny, Recent Radiation and Evolution of Gross Morphology of the Rhubarb genus Rheum (Polygonaceae) Inferred from Chloroplast DNA trnL-F Sequences

PubMed Central

WANG, AILAN; YANG, MEIHUA; LIU, JIANQUAN

2005-01-01

• Background and Aims Rheum, a highly diversified genus with about 60 species, is mainly confined to the mountainous and desert regions of the Qinghai–Tibetan plateau and adjacent areas. This genus represents a good example of the extensive diversification of the temperate genera in the Qinghai–Tibetan plateau, in which the forces to drive diversification remain unknown. To date, the infrageneric classification of Rheum has been mainly based on morphological characters. However, it may have been subject to convergent evolution under habitat pressure, and the systematic position of some sections are unclear, especially Sect. Globulosa, which has globular inflorescences, and Sect. Nobilia, which has semi-translucent bracts. Recent palynological research has found substantial contradictions between exine patterns and the current classification of Rheum. Two specific objectives of this research were (1) to evaluate possible relationships of some ambiguous sections with a unique morphology, and (2) to examine possible occurrence of the radiative speciation with low genetic divergence across the total genus and the correlation between the extensive diversification time of Rheum and past geographical events, especially the recent large-scale uplifts of the Qinghai–Tibetan Plateau. • Methods The chloroplast DNA trnL-F region of 29 individuals representing 26 species of Rheum, belonging to seven out of eight sections, was sequenced and compared. The phylogenetic relationships were further constructed based on the sequences obtained. • Key Results Despite the highly diversified morphology, the genetic variation in this DNA fragment is relatively low. The molecular phylogeny is highly inconsistent with gross morphology, pollen exine patterns and traditional classifications, except for identifying all samples of Sect. Palmata, three species of Sect. Spiciformia and a few species of Sect. Rheum as corresponding monophyletic groups. The monotypic Sect. Globulosa showed a tentative position within the clade comprising five species of Sect. Rheum. All of the analyses revealed the paraphyly of R. nobile and R. alexandrae, the only two species of Sect. Nobilia circumscribed by the possession of large bracts. The crude calibration of lineages based on trnL-F sequence differentiation implied an extensive diversification of Rheum within approx. 7 million years. • Conclusions Based on these results, it is suggested that the rich geological and ecological diversity caused by the recent large-scale uplifts of the Qinghai–Tibetan Plateau since the late Tertiary, coupled with the oscillating climate of the Quaternary stage, might have promoted rapid speciation in small and isolated populations, as well as allowing the fixation of unique or rare morphological characters in Rheum. Such a rapid radiation, combined with introgressive hybridization and reticulate evolution, may have caused the transfer of cpDNA haplotypes between morphologically dissimilar species, and might account for the inconsistency between morphological classification and molecular phylogeny reported here. PMID:15994840

Vietnamese Document Representation and Classification

NASA Astrophysics Data System (ADS)

Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

Genera of the human lineage

PubMed Central

Cela-Conde, Camilo J.; Ayala, Francisco J.

2003-01-01

Human fossils dated between 3.5 and nearly 7 million years old discovered during the last 8 years have been assigned to as many as four new genera of the family Hominidae: Ardipithecus, Orrorin, Kenyanthropus, and Sahelanthropus. These specimens are described as having morphological traits that justify placing them in the family Hominidae while creating a new genus for the classification of each. The discovery of these fossils pushed backward by >2 million years the date of the oldest hominids known. Only two or three hominid genera, Australopithecus, Paranthropus, and Homo, had been previously accepted, with Paranthropus considered a subgenus of Australopithecus by some authors. Two questions arise from the classification of the newly discovered fossils: (i) Should each one of these specimens be placed in the family Hominidae? (ii) Are these specimens sufficiently distinct to justify the creation of four new genera? The answers depend, in turn, on the concepts of what is a hominid and how the genus category is defined. These specimens seem to possess a sufficient number of morphological traits to be placed in the Hominidae. However, the nature of the morphological evidence and the adaptation-rooted concept of what a genus is do not justify the establishment of four new genera. We propose a classification that includes four well defined genera: Praeanthropus, Ardipithecus, Australopithecus, and Homo, plus one tentative incertae sedis genus: Sahelanthropus. PMID:12794185

Sexing adult black-legged kittiwakes by DNA, behavior, and morphology

USGS Publications Warehouse

Jodice, P.G.R.; Lanctot, Richard B.; Gill, V.A.; Roby, D.D.; Hatch, Shyla A.

2000-01-01

We sexed adult Black-legged Kittiwakes (Rissa tridactyla) using DNA-based genetic techniques, behavior and morphology and compared results from these techniques. Genetic and morphology data were collected on 605 breeding kittiwakes and sex-specific behaviors were recorded for a sub-sample of 285 of these individuals. We compared sex classification based on both genetic and behavioral techniques for this sub-sample to assess the accuracy of the genetic technique. DNA-based techniques correctly sexed 97.2% and sex-specific behaviors, 96.5% of this sub-sample. We used the corrected genetic classifications from this sub-sample and the genetic classifications for the remaining birds, under the assumption they were correct, to develop predictive morphometric discriminant function models for all 605 birds. These models accurately predicted the sex of 73-96% of individuals examined, depending on the sample of birds used and the characters included. The most accurate single measurement for determining sex was length of head plus bill, which correctly classified 88% of individuals tested. When both members of a pair were measured, classification levels improved and approached the accuracy of both behavioral observations and genetic analyses. Morphometric techniques were only slightly less accurate than genetic techniques but were easier to implement in the field and less costly. Behavioral observations, while highly accurate, required that birds be easily observable during the breeding season and that birds be identifiable. As such, sex-specific behaviors may best be applied as a confirmation of sex for previously marked birds. All three techniques thus have the potential to be highly accurate, and the selection of one or more will depend on the circumstances of any particular field study.

Mining the Galaxy Zoo Database: Machine Learning Applications

NASA Astrophysics Data System (ADS)

Borne, Kirk D.; Wallin, J.; Vedachalam, A.; Baehr, S.; Lintott, C.; Darg, D.; Smith, A.; Fortson, L.

2010-01-01

The new Zooniverse initiative is addressing the data flood in the sciences through a transformative partnership between professional scientists, volunteer citizen scientists, and machines. As part of this project, we are exploring the application of machine learning techniques to data mining problems associated with the large and growing database of volunteer science results gathered by the Galaxy Zoo citizen science project. We will describe the basic challenge, some machine learning approaches, and early results. One of the motivators for this study is the acquisition (through the Galaxy Zoo results database) of approximately 100 million classification labels for roughly one million galaxies, yielding a tremendously large and rich set of training examples for improving automated galaxy morphological classification algorithms. In our first case study, the goal is to learn which morphological and photometric features in the Sloan Digital Sky Survey (SDSS) database correlate most strongly with user-selected galaxy morphological class. As a corollary to this study, we are also aiming to identify which galaxy parameters in the SDSS database correspond to galaxies that have been the most difficult to classify (based upon large dispersion in their volunter-provided classifications). Our second case study will focus on similar data mining analyses and machine leaning algorithms applied to the Galaxy Zoo catalog of merging and interacting galaxies. The outcomes of this project will have applications in future large sky surveys, such as the LSST (Large Synoptic Survey Telescope) project, which will generate a catalog of 20 billion galaxies and will produce an additional astronomical alert database of approximately 100 thousand events each night for 10 years -- the capabilities and algorithms that we are exploring will assist in the rapid characterization and classification of such massive data streams. This research has been supported in part through NSF award #0941610.

Functional traits and root morphology of alpine plants

PubMed Central

Pohl, Mandy; Stroude, Raphaël; Buttler, Alexandre; Rixen, Christian

2011-01-01

Background and Aims Vegetation has long been recognized to protect the soil from erosion. Understanding species differences in root morphology and functional traits is an important step to assess which species and species mixtures may provide erosion control. Furthermore, extending classification of plant functional types towards root traits may be a useful procedure in understanding important root functions. Methods In this study, pioneer data on traits of alpine plant species, i.e. plant height and shoot biomass, root depth, horizontal root spreading, root length, diameter, tensile strength, plant age and root biomass, from a disturbed site in the Swiss Alps are presented. The applicability of three classifications of plant functional types (PFTs), i.e. life form, growth form and root type, was examined for above- and below-ground plant traits. Key Results Plant traits differed considerably among species even of the same life form, e.g. in the case of total root length by more than two orders of magnitude. Within the same root diameter, species differed significantly in tensile strength: some species (Geum reptans and Luzula spicata) had roots more than twice as strong as those of other species. Species of different life forms provided different root functions (e.g. root depth and horizontal root spreading) that may be important for soil physical processes. All classifications of PFTs were helpful to categorize plant traits; however, the PFTs according to root type explained total root length far better than the other PFTs. Conclusions The results of the study illustrate the remarkable differences between root traits of alpine plants, some of which cannot be assessed from simple morphological inspection, e.g. tensile strength. PFT classification based on root traits seems useful to categorize plant traits, even though some patterns are better explained at the individual species level. PMID:21795278

Chemometric classification of morphologically similar Umbelliferae medicinal herbs by DART-TOF-MS fingerprint.

PubMed

Lee, Sang Min; Kim, Hye-Jin; Jang, Young Pyo

2012-01-01

It needs many years of special training to gain expertise on the organoleptic classification of botanical raw materials and, even for those experts, discrimination among Umbelliferae medicinal herbs remains an intricate challenge due to their morphological similarity. To develop a new chemometric classification method using a direct analysis in real time-time of flight-mass spectrometry (DART-TOF-MS) fingerprinting for Umbelliferae medicinal herbs and to provide a platform for its application to the discrimination of other herbal medicines. Angelica tenuissima, Angelica gigas, Angelica dahurica and Cnidium officinale were chosen for this study and ten samples of each species were purchased from various Korean markets. DART-TOF-MS was employed on powdered raw materials to obtain a chemical fingerprint of each sample and the orthogonal partial-least squares method in discriminant analysis (OPLS-DA) was used for multivariate analysis. All samples of collected species were successfully discriminated from each other according to their characteristic DART-TOF-MS fingerprint. Decursin (or decursinol angelate) and byakangelicol were identified as marker molecules for Angelica gigas and A. dahurica, respectively. Using the OPLS method for discriminant analysis, Angelica tenuissima and Cnidium officinale were clearly separated into two groups. Angelica tenuissima was characterised by the presence of ligustilide and unidentified molecular ions of m/z 239 and 283, while senkyunolide A together with signals with m/z 387 and 389 were the marker compounds for Cnidium officinale. Elaborating with chemoinformatics, DART-TOF-MS fingerprinting with chemoinformatic tools results in a powerful method for the classification of morphologically similar Umbelliferae medicinal herbs and quality control of medicinal herbal products, including the extracts of these crude drugs. Copyright © 2012 John Wiley & Sons, Ltd.

Accurate diagnosis of thyroid follicular lesions from nuclear morphology using supervised learning.

PubMed

Ozolek, John A; Tosun, Akif Burak; Wang, Wei; Chen, Cheng; Kolouri, Soheil; Basu, Saurav; Huang, Hu; Rohde, Gustavo K

2014-07-01

Follicular lesions of the thyroid remain significant diagnostic challenges in surgical pathology and cytology. The diagnosis often requires considerable resources and ancillary tests including immunohistochemistry, molecular studies, and expert consultation. Visual analyses of nuclear morphological features, generally speaking, have not been helpful in distinguishing this group of lesions. Here we describe a method for distinguishing between follicular lesions of the thyroid based on nuclear morphology. The method utilizes an optimal transport-based linear embedding for segmented nuclei, together with an adaptation of existing classification methods. We show the method outputs assignments (classification results) which are near perfectly correlated with the clinical diagnosis of several lesion types' lesions utilizing a database of 94 patients in total. Experimental comparisons also show the new method can significantly outperform standard numerical feature-type methods in terms of agreement with the clinical diagnosis gold standard. In addition, the new method could potentially be used to derive insights into biologically meaningful nuclear morphology differences in these lesions. Our methods could be incorporated into a tool for pathologists to aid in distinguishing between follicular lesions of the thyroid. In addition, these results could potentially provide nuclear morphological correlates of biological behavior and reduce health care costs by decreasing histotechnician and pathologist time and obviating the need for ancillary testing. Copyright © 2014 Elsevier B.V. All rights reserved.

Galaxy Zoo: morphological classifications for 120 000 galaxies in HST legacy imaging

NASA Astrophysics Data System (ADS)

Willett, Kyle W.; Galloway, Melanie A.; Bamford, Steven P.; Lintott, Chris J.; Masters, Karen L.; Scarlata, Claudia; Simmons, B. D.; Beck, Melanie; Cardamone, Carolin N.; Cheung, Edmond; Edmondson, Edward M.; Fortson, Lucy F.; Griffith, Roger L.; Häußler, Boris; Han, Anna; Hart, Ross; Melvin, Thomas; Parrish, Michael; Schawinski, Kevin; Smethurst, R. J.; Smith, Arfon M.

2017-02-01

We present the data release paper for the Galaxy Zoo: Hubble (GZH) project. This is the third phase in a large effort to measure reliable, detailed morphologies of galaxies by using crowdsourced visual classifications of colour-composite images. Images in GZH were selected from various publicly released Hubble Space Telescope legacy programmes conducted with the Advanced Camera for Surveys, with filters that probe the rest-frame optical emission from galaxies out to z ˜ 1. The bulk of the sample is selected to have mI814W < 23.5, but goes as faint as mI814W < 26.8 for deep images combined over five epochs. The median redshift of the combined samples is = 0.9 ± 0.6, with a tail extending out to z ≃ 4. The GZH morphological data include measurements of both bulge- and disc-dominated galaxies, details on spiral disc structure that relate to the Hubble type, bar identification, and numerous measurements of clump identification and geometry. This paper also describes a new method for calibrating morphologies for galaxies of different luminosities and at different redshifts by using artificially redshifted galaxy images as a baseline. The GZH catalogue contains both raw and calibrated morphological vote fractions for 119 849 galaxies, providing the largest data set to date suitable for large-scale studies of galaxy evolution out to z ˜ 1.

Flow Classification and Cave Discharge Characteristics in Unsaturated Karst Formation

NASA Astrophysics Data System (ADS)

Mariethoz, G.; Mahmud, K.; Baker, A.; Treble, P. C.

2015-12-01

In this study we utilize the spatial array of automated cave drip monitoring in two large chambers of the Golgotha Cave, SW Australia, developed in Quaternary aeolianite (dune limestone), with the aim of understanding infiltration water movement via the relationships between infiltration, stalactite morphology and groundwater recharge. Mahmud et al. (2015) used the Terrestrial LiDAR measurements to analyze stalactite morphology and to characterize possible flow locations in this cave. Here we identify the stalactites feeding the drip loggers and classify each as matrix (soda straw or icicle), fracture or combined-flow. These morphology-based classifications are compared with flow characteristics from the drip logger time series and the discharge from each stalactite is calculated. The total estimated discharge from each area is compared with infiltration estimates to better understand flow from the surface to the cave ceilings of the studied areas. The drip discharge data agrees with the morphology-based flow classification in terms of flow and geometrical characteristics of cave ceiling stalactites. No significant relationships were observed between the drip logger discharge, skewness and coefficient of variation with overburden thickness, due to the possibility of potential vadose-zone storage volume and increasing complexity of the karst architecture. However, these properties can be used to characterize different flow categories. A correlation matrix demonstrates that similar flow categories are positively correlated, implying significant influence of spatial distribution. The infiltration water comes from a larger surface area, suggesting that infiltration is being focused to the studied ceiling areas of each chamber. Most of the ceiling in the cave site is dry, suggesting the possibility of capillary effects with water moving around the cave rather than passing through it. Reference:Mahmud et al. (2015), Terrestrial Lidar Survey and Morphological Analysis to Identify Infiltration Properties in the Tamala Limestone, Western Australia, IEEE JSTARS, DOI: 10.1109/JSTARS.2015.2451088, in Press.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

Phylogeny and systematics of deep-sea precious corals (Anthozoa: Octocorallia: Coralliidae).

PubMed

Tu, Tzu-Hsuan; Dai, Chang-Feng; Jeng, Ming-Shiou

2015-03-01

The phylogeny of Coralliidae is being increasingly studied to elucidate their evolutionary history and species delimitation due to global concerns about their conservation. Previous studies on phylogenetic relationships within Coralliidae have pointed out that the two currently recognized genera are not monophyletic and the Coralliidae should be divided into three genera. In order to provide a comprehensive revision of the taxonomy of Coralliidae, we documented 110 specimens using eight mitochondrial and one nuclear loci to reconstruct their phylogeny. The morphological features of 27 type specimens were also examined. Phylogenetic relationships based on both mitochondrial and nuclear markers revealed two reciprocally monophyletic clades of Coralliidae. One of the clades was further split into two subclades with respect to sequence variation and observable morphological features. Based on the results of genealogical analyses and distinctive morphological features, the three genera classification of Coralliidae proposed by Gray (1867) was redefined. In this revised taxonomic system, Corallium, Hemicorallium, and Pleurocorallium consist of 7, 16 and 14 species, respectively. Our results also showed that the cosmopolitan Hemicorallium laauense is a species complex containing a cryptic species. Copyright © 2015 Elsevier Inc. All rights reserved.

Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine.

PubMed

Kovacs, Gabor G

2016-02-02

Neurodegenerative diseases (NDDs) are characterized by selective dysfunction and loss of neurons associated with pathologically altered proteins that deposit in the human brain but also in peripheral organs. These proteins and their biochemical modifications can be potentially targeted for therapy or used as biomarkers. Despite a plethora of modifications demonstrated for different neurodegeneration-related proteins, such as amyloid-β, prion protein, tau, α-synuclein, TAR DNA-binding protein 43 (TDP-43), or fused in sarcoma protein (FUS), molecular classification of NDDs relies on detailed morphological evaluation of protein deposits, their distribution in the brain, and their correlation to clinical symptoms together with specific genetic alterations. A further facet of the neuropathology-based classification is the fact that many protein deposits show a hierarchical involvement of brain regions. This has been shown for Alzheimer and Parkinson disease and some forms of tauopathies and TDP-43 proteinopathies. The present paper aims to summarize current molecular classification of NDDs, focusing on the most relevant biochemical and morphological aspects. Since the combination of proteinopathies is frequent, definition of novel clusters of patients with NDDs needs to be considered in the era of precision medicine. Optimally, neuropathological categorizing of NDDs should be translated into in vivo detectable biomarkers to support better prediction of prognosis and stratification of patients for therapy trials.

Classification of microscopic images of breast tissue

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Franzen, Lennart

2004-05-01

Breast cancer is the most common form of cancer among women. The diagnosis is usually performed by the pathologist, that subjectively evaluates tissue samples. The aim of our research is to develop techniques for the automatic classification of cancerous tissue, by analyzing histological samples of intact tissue taken with a biopsy. In our study, we considered 200 images presenting four different conditions: normal tissue, fibroadenosis, ductal cancer and lobular cancer. Methods to extract features have been investigated and described. One method is based on granulometries, which are size-shape descriptors widely used in mathematical morphology. Applications of granulometries lead to distribution functions whose moments are used as features. A second method is based on fractal geometry, that seems very suitable to quantify biological structures. The fractal dimension of binary images has been computed using the euclidean distance mapping. Image classification has then been performed using the extracted features as input of a back-propagation neural network. A new method that combines genetic algorithms and morphological filters has been also investigated. In this case, the classification is based on a correlation measure. Very encouraging results have been obtained with pilot experiments using a small subset of images as training set. Experimental results indicate the effectiveness of the proposed methods. Cancerous tissue was correctly classified in 92.5% of the cases.

Morphology of Mesiobuccal Root Canals of Maxillary First Molars: a comparison of CBCT scanning and Cross-sectioning.

PubMed

Lyra, Carina Maria; Delai, Débora; Pereira, Keila Cristina Rausch; Pereira, Guy Martins; Pasternak Júnior, Bráulio; Oliveira, César Augusto Pereira

2015-10-01

The aim of this study was to evaluate the mesiobuccal root of maxillary first molars, according to the root canal configuration, prevalence and location of isthmuses at 3 and 6 mm from the apex, comparing cone-beam computed tomography (CBCT) analysis and cross sectioning of roots by thirds. Images of the mesiobuccal root of 100 maxillary first molars were acquired by CBCT and then roots were cross-sectioned into two parts, starting at 3 mm from the apex. Data were recorded and analyzed according to Weine's classification for root canal configuration, and Hsu and Kim's classification for isthmuses. In the analysis of CBCT images, 8 root canals were classified as type I, 57 as type II, 35 as type III. In the cross-sectioning technique, 19 root canals were classified as type I, 60 as type II, 20 as type III and 1 as type IV. The classification of isthmuses was predominantly type I in both CBCT and cross-sectioning evaluations for sections at 3 mm from the apex, while for sections at 6 mm from the apex, the classification of isthmuses was predominantly types V and II in CBCT and cross-sectioning evaluations, respectively. The cross-sectioning technique showed better results in detection of the internal morphology of root canals than CBCT scanning.

Molecular Pathological Classification of Neurodegenerative Diseases: Turning towards Precision Medicine

PubMed Central

Kovacs, Gabor G.

2016-01-01

Neurodegenerative diseases (NDDs) are characterized by selective dysfunction and loss of neurons associated with pathologically altered proteins that deposit in the human brain but also in peripheral organs. These proteins and their biochemical modifications can be potentially targeted for therapy or used as biomarkers. Despite a plethora of modifications demonstrated for different neurodegeneration-related proteins, such as amyloid-β, prion protein, tau, α-synuclein, TAR DNA-binding protein 43 (TDP-43), or fused in sarcoma protein (FUS), molecular classification of NDDs relies on detailed morphological evaluation of protein deposits, their distribution in the brain, and their correlation to clinical symptoms together with specific genetic alterations. A further facet of the neuropathology-based classification is the fact that many protein deposits show a hierarchical involvement of brain regions. This has been shown for Alzheimer and Parkinson disease and some forms of tauopathies and TDP-43 proteinopathies. The present paper aims to summarize current molecular classification of NDDs, focusing on the most relevant biochemical and morphological aspects. Since the combination of proteinopathies is frequent, definition of novel clusters of patients with NDDs needs to be considered in the era of precision medicine. Optimally, neuropathological categorizing of NDDs should be translated into in vivo detectable biomarkers to support better prediction of prognosis and stratification of patients for therapy trials. PMID:26848654

Biological attachment devices: exploring nature's diversity for biomimetics.

PubMed

Gorb, Stanislav N

2008-05-13

Many species of animals and plants are supplied with diverse attachment devices, in which morphology depends on the species biology and the particular function in which the attachment device is involved. Many functional solutions have evolved independently in different lineages of animals and plants. Since the diversity of such biological structures is huge, there is a need for their classification. This paper, based on the original and literature data, proposes ordering of biological attachment systems according to several principles: (i) fundamental physical mechanism, according to which the system operates, (ii) biological function of the attachment device, and (iii) duration of the contact. Finally, we show a biomimetic potential of studies on biological attachment devices.

Microaneurysm detection with radon transform-based classification on retina images.

PubMed

Giancardo, L; Meriaudeau, F; Karnowski, T P; Li, Y; Tobin, K W; Chaum, E

2011-01-01

The creation of an automatic diabetic retinopathy screening system using retina cameras is currently receiving considerable interest in the medical imaging community. The detection of microaneurysms is a key element in this effort. In this work, we propose a new microaneurysms segmentation technique based on a novel application of the radon transform, which is able to identify these lesions without any previous knowledge of the retina morphological features and with minimal image preprocessing. The algorithm has been evaluated on the Retinopathy Online Challenge public dataset, and its performance compares with the best current techniques. The performance is particularly good at low false positive ratios, which makes it an ideal candidate for diabetic retinopathy screening systems.

Refractory anemia with ringed sideroblasts and chronic myelomonocytic leukemia: myelodysplastic/myeloproliferative disease.

PubMed

D'Angelo, Guido

2005-01-01

Here is reported the case of an elderly woman that, after surgical intervention, showed an important anemia, leucocytosis and thrombocytopenia. The leucocytosis was accompanied with clean increase of the monocytes. The morphological appearances, both peripheral blood and bone marrow, showed an evident overlapping of myelodysplastic and myeloproliferative picture, characterized from the presence of refractory anemia with ringed sideroblasts (RARS) and chronic myelomonocytic leukemia (CMML). The case has been reported because it is not frequent, besides, the CMML, until from the beginning of French-American-British (FAB) classification application, has raised problems of classification. Currently, the World Health Organization (WHO) has given an arrangement to the hematological picture with myelodysplastic and myeloproliferative morphological appearances, including this pathology in a new category: myelodysplastic/myeloproliferative diseases (MDS/MPD).

[Classification of prosthetic loosening and determination of wear particles].

PubMed

Otto, M

2008-11-01

Nowaday, loosening of orthopaedic implants implies important medical and socioeconomic problems. Implant loosening is caused by implant infections as well as aseptic loosening, due to particle disease and mechanical alterations. Clinically we divide the implant infection into early and late infections. Morphologically it is possible to reliably detect the infection by quantification of neutrophil granulocytes. Additionally molecular methods are suitable to detect micro-organisms which are responsible for the prosthetic joint infection including their resistance to antibiotics. Particle disease may be reproducibly classified by the detection of different types of wear particles, particularly polyethylene, metal, ceramic and cement. The aetiology of the indeterminate type of the periprosthetic membrane is obscure, but may be associated with osteopathies. This classification of the periprosthetic membrane morphology provides clinically significant information concerning clinical management of implant loosening.

Integrating a Numerical Taxonomic Method and Molecular Phylogeny for Species Delimitation of Melampsora Species (Melampsoraceae, Pucciniales) on Willows in China

PubMed Central

Zhao, Peng; Wang, Qing-Hong; Tian, Cheng-Ming; Kakishima, Makoto

2015-01-01

The species in genus Melampsora are the causal agents of leaf rust diseases on willows in natural habitats and plantations. However, the classification and recognition of species diversity are challenging because morphological characteristics are scant and morphological variation in Melampsora on willows has not been thoroughly evaluated. Thus, the taxonomy of Melampsora species on willows remains confused, especially in China where 31 species were reported based on either European or Japanese taxonomic systems. To clarify the species boundaries of Melampsora species on willows in China, we tested two approaches for species delimitation inferred from morphological and molecular variations. Morphological species boundaries were determined based on numerical taxonomic analyses of morphological characteristics in the uredinial and telial stages by cluster analysis and one-way analysis of variance. Phylogenetic species boundaries were delineated based on the generalized mixed Yule-coalescent (GMYC) model analysis of the sequences of the internal transcribed spacer (ITS1 and ITS2) regions including the 5.8S and D1/D2 regions of the large nuclear subunit of the ribosomal RNA gene. Numerical taxonomic analyses of 14 morphological characteristics recognized in the uredinial-telial stages revealed 22 morphological species, whereas the GMYC results recovered 29 phylogenetic species. In total, 17 morphological species were in concordance with the phylogenetic species and 5 morphological species were in concordance with 12 phylogenetic species. Both the morphological and molecular data supported 14 morphological characteristics, including 5 newly recognized characteristics and 9 traditionally emphasized characteristics, as effective for the differentiation of Melampsora species on willows in China. Based on the concordance and discordance of the two species delimitation approaches, we concluded that integrative taxonomy by using both morphological and molecular variations was an effective approach for delimitating Melampsora species on willows in China. PMID:26680416

Molecular approaches for classifying endometrial carcinoma.

PubMed

Piulats, Josep M; Guerra, Esther; Gil-Martín, Marta; Roman-Canal, Berta; Gatius, Sonia; Sanz-Pamplona, Rebeca; Velasco, Ana; Vidal, August; Matias-Guiu, Xavier

2017-04-01

Endometrial carcinoma is the most common cancer of the female genital tract. This review article discusses the usefulness of molecular techniques to classify endometrial carcinoma. Any proposal for molecular classification of neoplasms should integrate morphological features of the tumors. For that reason, we start with the current histological classification of endometrial carcinoma, by discussing the correlation between genotype and phenotype, and the most significant recent improvements. Then, we comment on some of the possible flaws of this classification, by discussing also the value of molecular pathology in improving them, including interobserver variation in pathologic interpretation of high grade tumors. Third, we discuss the importance of applying TCGA molecular approach to clinical practice. We also comment on the impact of intratumor heterogeneity in classification, and finally, we will discuss briefly, the usefulness of TCGA classification in tailoring immunotherapy in endometrial cancer patients. We suggest combining pathologic classification and the surrogate TCGA molecular classification for high-grade endometrial carcinomas, as an option to improve assessment of prognosis. Copyright © 2016 Elsevier Inc. All rights reserved.

The use of morphological knowledge in spelling derived forms by learning-disabled and normal students.

PubMed

Carlisle, J F

1987-01-01

Currently popular systems for classification of spelling words or errors emphasize the learning of phoneme-grapheme correspondences and memorization of irregular words, but do not take into account the morphophonemic nature of the English language. This study is based on the premise that knowledge of the morphological rules of derivational morphology is acquired developmentally and is related to the spelling abilities of both normal and learning-disabled (LD) students. It addresses three issues: 1) how the learning of derivational morphology and the spelling of derived words by LD students compares to that of normal students; 2) whether LD students learn derived forms rulefully; and 3) the extent to which LD and normal students use knowledge of relationships between base and derived forms to spell derived words (e.g. "magic" and "magician"). The results showed that LD ninth graders' knowledge of derivational morphology was equivalent to that of normal sixth graders, following similar patterns of mastery of orthographic and phonological rules, but that their spelling of derived forms was equivalent to that of the fourth graders. Thus, they know more about derivational morphology than they use in spelling. In addition, they were significantly more apt to spell derived words as whole words, without regard for morphemic structure, than even the fourth graders. Nonetheless, most of the LD spelling errors were phonetically acceptable, suggesting that their misspellings cannot be attributed primarily to poor knowledge of phoneme-grapheme correspondences.

Classification in Astronomy: Past and Present

NASA Astrophysics Data System (ADS)

Feigelson, Eric

2012-03-01

Astronomers have always classified celestial objects. The ancient Greeks distinguished between asteros, the fixed stars, and planetos, the roving stars. The latter were associated with the Gods and, starting with Plato in his dialog Timaeus, provided the first mathematical models of celestial phenomena. Giovanni Hodierna classified nebulous objects, seen with a Galilean refractor telescope in the mid-seventeenth century into three classes: "Luminosae," "Nebulosae," and "Occultae." A century later, Charles Messier compiled a larger list of nebulae, star clusters and galaxies, but did not attempt a classification. Classification of comets was a significant enterprise in the 19th century: Alexander (1850) considered two groups based on orbit sizes, Lardner (1853) proposed three groups of orbits, and Barnard (1891) divided them into two classes based on morphology. Aside from the segmentation of the bright stars into constellations, most stellar classifications were based on colors and spectral properties. During the 1860s, the pioneering spectroscopist Angelo Secchi classified stars into five classes: white, yellow, orange, carbon stars, and emission line stars. After many debates, the stellar spectral sequence was refined by the group at Harvard into the familiar OBAFGKM spectral types, later found to be a sequence on surface temperature (Cannon 1926). The spectral classification is still being extended with recent additions of O2 hot stars (Walborn et al. 2002) and L and T brown dwarfs (Kirkpatrick 2005). Townley (1913) reviews 30 years of variable star classification, emerging with six classes with five subclasses. The modern classification of variable stars has about 80 (sub)classes, and is still under debate (Samus 2009). Shortly after his confirmation that some nebulae are external galaxies, Edwin Hubble (1926) proposed his famous bifurcated classification of galaxy morphologies with three classes: ellipticals, spirals, and irregulars. These classes are still used today with many refinements by Gerard de Vaucouleurs and others. Supernovae, nearly all of which are found in external galaxies, have a complicated classification scheme:Type I with subtypes Ia, Ib, Ic, Ib/c pec and Type II with subtypes IIb, IIL, IIP, and IIn (Turatto 2003). The classification is based on elemental abundances in optical spectra and on optical light curve shapes. Tadhunter (2009) presents a three-dimensional classification of active galactic nuclei involving radio power, emission line width, and nuclear luminosity. These taxonomies have played enormously important roles in the development of astronomy, yet all were developed using heuristic methods. Many are based on qualitative and subjective assessments of spatial, temporal, or spectral properties. A qualitative, morphological approach to astronomical studies was explicitly promoted by Zwicky (1957). Other classifications are based on quantitative criteria, but these criteria were developed by subjective examination of training datasets. For example, starburst galaxies are discriminated from narrow-line Seyfert galaxies by a curved line in a diagramof the ratios of four emission lines (Veilleux and Osterbrock 1987). Class II young stellar objects have been defined by a rectangular region in a mid-infrared color-color diagram (Allen et al. 2004). Short and hard gamma-ray bursts are discriminated by a dip in the distribution of burst durations (Kouveliotou et al. 2000). In no case was a statistical or algorithmic procedure used to define the classes.

Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

2017-05-01

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

Phylogeny of Comatulidae (Echinodermata: Crinoidea: Comatulida): a new classification and an assessment of morphological characters for crinoid taxonomy.

PubMed

Summers, Mindi M; Messing, Charles G; Rouse, Greg W

2014-11-01

Comatulidae Fleming, 1828 (previously, and incorrectly, Comasteridae A.H. Clark, 1908a), is a group of feather star crinoids currently divided into four accepted subfamilies, 21 genera and approximately 95 nominal species. Comatulidae is the most commonly-encountered and species-rich crinoid group on shallow tropical coral reefs, particularly in the Indo-western Pacific region (IWP). We conducted a molecular phylogenetic analysis of the group with concatenated data from up to seven genes for 43 nominal species spanning 17 genera and all subfamilies. Basal nodes returned low support, but maximum likelihood, maximum parsimony, and Bayesian analyses were largely congruent, permitting an evaluation of current taxonomy and analysis of morphological character transformations. Two of the four current subfamilies were paraphyletic, whereas 15 of the 17 included genera returned as monophyletic. We provide a new classification with two subfamilies, Comatulinae and Comatellinae n. subfamily Summers, Messing, & Rouse, the former containing five tribes. We revised membership of analyzed genera to make them all clades and erected Anneissia n. gen. Summers, Messing, & Rouse. Transformation analyses for morphological features generally used in feather star classification (e.g., ray branching patterns, articulations) and those specifically for Comatulidae (e.g., comb pinnule form, mouth placement) were labile with considerable homoplasy. These traditional characters, in combination, allow for generic diagnoses, but in most cases we did not recover apomorphies for subfamilies, tribes, and genera. New morphological characters that will be informative for crinoid taxonomy and identification are still needed. DNA sequence data currently provides the most reliable method of identification to the species-level for many taxa of Comatulidae. Copyright © 2014 Elsevier Inc. All rights reserved.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae).

PubMed

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks's λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant ( p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species.

Phylogenetic relationships among species of Lutzomyia, subgenus Lutzomyia (Diptera: Psychodidae).

PubMed

Pinto, Israel S; Filho, José D Andrade; Santos, Claudiney B; Falqueto, Aloísio; Leite, Yuri L R

2010-01-01

Lutzomyia França is the largest and most diverse sand fly genus in the New World and contains all the species involved in the transmission of American visceral leishmaniasis (AVL). Morphological characters were used to test the monophyly and to infer phylogenetic relationships among members of the Lutzomyia subgenus. Fifty-two morphological characters from male and female adult specimens belonging to 18 species of Lu. (Lutzomyia) were scored and analyzed. The resulting phylogeny confirms the monophyly of this subgenus and reveals four main internal clades. These four clades, however, do not support the classification of the subgenus in two series, longipalpis and cavernicola, because neither is necessarily monophyletic. Knowledge on phylogenetic relationships among these relevant vectors of AVL should be used as a tool for monitoring target taxa and a first step for establishing an early warning system for disease control.

Morphological analysis of dendrites and spines by hybridization of ridge detection with twin support vector machine.

PubMed

Wang, Shuihua; Chen, Mengmeng; Li, Yang; Shao, Ying; Zhang, Yudong; Du, Sidan; Wu, Jane

2016-01-01

Dendritic spines are described as neuronal protrusions. The morphology of dendritic spines and dendrites has a strong relationship to its function, as well as playing an important role in understanding brain function. Quantitative analysis of dendrites and dendritic spines is essential to an understanding of the formation and function of the nervous system. However, highly efficient tools for the quantitative analysis of dendrites and dendritic spines are currently undeveloped. In this paper we propose a novel three-step cascaded algorithm-RTSVM- which is composed of ridge detection as the curvature structure identifier for backbone extraction, boundary location based on differences in density, the Hu moment as features and Twin Support Vector Machine (TSVM) classifiers for spine classification. Our data demonstrates that this newly developed algorithm has performed better than other available techniques used to detect accuracy and false alarm rates. This algorithm will be used effectively in neuroscience research.

Potential impacts of robust surface roughness indexes on DTM-based segmentation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2017-04-01

In this study, we explore the impact of robust surface texture indexes based on MAD (median absolute differences), implemented by Trevisani and Rocca (2015), in the unsupervised morphological segmentation of an alpine basin. The area was already object of a geomorphometric analysis, consisting in the roughness-based segmentation of the landscape (Trevisani et al. 2012); the roughness indexes were calculated on a high resolution DTM derived by means of airborne Lidar using the variogram as estimator. The calculated roughness indexes have been then used for the fuzzy clustering (Odeh et al., 1992; Burrough et al., 2000) of the basin, revealing the high informative geomorphometric content of the roughness-based indexes. However, the fuzzy clustering revealed a high fuzziness and a high degree of mixing between textural classes; this was ascribed both to the morphological complexity of the basin and to the high sensitivity of variogram to non-stationarity and signal-noise. Accordingly, we explore how the new implemented roughness indexes based on MAD affect the morphological segmentation of the studied basin. References Burrough, P.A., Van Gaans, P.F.M., MacMillan, R.A., 2000. High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52. Odeh, I.O.A., McBratney, A.B., Chittleborough, D.J., 1992. Soil pattern recognition with fuzzy-c-means: application to classification and soil-landform interrelationships. Soil Sciences Society of America Journal 56, 505-516. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S. & Rocca, M. 2015, "MAD: Robust image texture analysis for applications in high resolution geomorphometry", Computers and Geosciences, vol. 81, pp. 78-92.

Meeting the Cool Neighbors. XII. An Optically Anchored Analysis of the Near-infrared Spectra of L Dwarfs

NASA Astrophysics Data System (ADS)

Cruz, Kelle L.; Núñez, Alejandro; Burgasser, Adam J.; Abrahams, Ellianna; Rice, Emily L.; Reid, I. Neill; Looper, Dagny

2018-01-01

Discrepancies between competing optical and near-infrared (NIR) spectral typing systems for L dwarfs have motivated us to search for a classification scheme that ties the optical and NIR schemes together, and addresses complexities in the spectral morphology. We use new and extant optical and NIR spectra to compile a sample of 171 L dwarfs, including 27 low-gravity β and γ objects, with spectral coverage from 0.6–2.4 μm. We present 155 new low-resolution NIR spectra and 19 new optical spectra. We utilize a method for analyzing NIR spectra that partially removes the broad-band spectral slope and reveals similarities in the absorption features between objects of the same optical spectral type. Using the optical spectra as an anchor, we generate near-infrared spectral average templates for L0–L8, L0–L4γ, and L0–L1β type dwarfs. These templates reveal that NIR spectral morphologies are correlated with the optical types. They also show the range of spectral morphologies spanned by each spectral type. We compare low-gravity and field-gravity templates to provide recommendations on the minimum required observations for credibly classifying low-gravity spectra using low-resolution NIR data. We use the templates to evaluate the existing NIR spectral standards and propose new ones where appropriate. Finally, we build on the work of Kirkpatrick et al. to provide a spectral typing method that is tied to the optical and can be used when only H or K band data are available. The methods we present here provide resolutions to several long-standing issues with classifying L dwarf spectra and could also be the foundation for a spectral classification scheme for cloudy exoplanets.

SkICAT: A cataloging and analysis tool for wide field imaging surveys

NASA Technical Reports Server (NTRS)

Weir, N.; Fayyad, U. M.; Djorgovski, S. G.; Roden, J.

1992-01-01

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Texture classification using non-Euclidean Minkowski dilation

NASA Astrophysics Data System (ADS)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

Comparison of the ESHRE–ESGE and ASRM classifications of Müllerian duct anomalies in everyday practice

PubMed Central

Ludwin, A.; Ludwin, I.

2015-01-01

STUDY QUESTION Does the European Society of Human Reproduction and Embryology–European Society for Gynaecological Endoscopy (ESHRE–ESGE) classification of female genital tract malformations significantly increase the frequency of septate uterus diagnosis relative to the American Society for Reproductive Medicine (ASRM) classification? SUMMARY ANSWER Use of the ESHRE–ESGE classification, compared with the ASRM classification, significantly increased the frequency of septate uterus recognition. WHAT IS KNOWN ALREADY The ESHRE–ESGE criteria were supposed to eliminate the subjective diagnoses of septate uterus by the ASRM criteria and replace the complementary absolute morphometric criteria. However, the clinical value of the ESHRE–ESGE classification in daily practice is difficult to appreciate. The application of the ESHRE–ESGE criteria has resulted in a significantly increased recognition of residual septum after hysteroscopic metroplasty, with a possible risk of overdiagnosis of septate uterus and problems for its management. STUDY DESIGN, SIZE, AND DURATION A prospective observational study was performed with 261 women consecutively enrolled between June and September 2013. PARTICIPANTS/MATERIALS, SETTING, AND METHODS Non-pregnant women of reproductive age presented for evaluation to a private medical center. A gynecological examination and 3D ultrasonography were performed to assess the anatomy of the uterus, cervix and vagina. Congenital anomalies were diagnosed using the ASRM classification with additional morphometric criteria as well as with the ESHRE–ESGE classification. We compared the frequency and concordance of diagnoses of septate uterus and all congenital malformations of the uterus according to both classifications. The morphological characteristics of septate uterus recognized by both criteria were compared. MAIN RESULTS AND ROLE OF CHANCE Of the 261 patients enrolled in this study, septate uterus was diagnosed in 44 (16.9%) and 16 (6.1%) patients using the ESGE–ESHRE and ASRM criteria, respectively [relative risk (RR)ESHRE–ESGE:ASRM 2.74; 95% confidence interval (CI), 1.6–4.72; P < 0.01]. At least one congenital anomaly were diagnosed in 58 (22.2%) and 43 (16.5%) patients using the ESHRE–ESGE and ASRM classifications (RRESHRE–ESGE:ASRM, 1.35; 95% CI, 0.95–1.92, P = 0.1), respectively. The two criteria had moderate strength of agreement in the diagnosis of septate uterus (κ = 0.45, P < 0.01). There was good agreement in differentiation between anomaly and norm between the two assessment criteria (κ = 0.79, P < 0.01). The percentages of all congenital malformations and results of the differentiation between the anomaly and norm were obtained after excluding the confounding original ESHRE–ESGE criterion of dysmorphic uterus (internal indentation <50% uterine wall thickness). The morphology of septa identified by the ESHRE–ESGE [length of internal fundal indentation (mm): median 10.7; lower–upper quartile, 8.1–20] significantly differed (P < 0.01) from that identified by the ASRM criteria [length of internal fundal indentation (mm): median, 21.1; lower–upper quartile, 18.8–33.1]. Internal fundal indentation in 16 out of 44 (36.4%) cases was <1 cm in the septate uterus by ESHRE–ESGE and met the criteria for normal uterus by ASRM. LIMITATIONS AND REASONS FOR CAUTION The study participants were women who visited a diagnostic and treatment center specialized in uterine congenital malformations for a medical assessment, not from the general public. WIDER IMPLICATIONS OF THE FINDINGS Septate uterus diagnosis by ESHRE–ESGE was quantitatively dominated by morphological states corresponding to arcuate uterus or cases that were not diagnosed as congenital malformations by ASRM. Relative overdiagnosis of septate uterus by ESHRE–ESGE in these cases may lead to unnecessary overtreatment without the expected benefits. The ESHRE–ESGE classification criteria should be redefined due to confusions in the methodology. Until the criteria are revised, septate uterus should not be diagnosed using this classification system and it should not be used as an eligibility criterion for hysteroscopic metroplasty. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by Jagiellonian University (grant no. K/ZDS/003821). The authors have no competing interests to declare. PMID:25534461

Hip ontogenesis: how evolution, genes, and load history shape hip morphotype and cartilotype.

PubMed

Hogervorst, Tom; Eilander, Wouter; Fikkers, Joost T; Meulenbelt, Ingrid

2012-12-01

Developmental hip disorders (DHDs), eg, developmental dysplasia of the hip, slipped capitis femoris epiphysis, and femoroacetabular impingement, can be considered morphology variants of the normal hip. The femoroacetabular morphology of DHD is believed to induce osteoarthritis (OA) through local cumulative mechanical overload acting on genetically controlled patterning systems and subsequent damage of joint structures. However, it is unclear why hip morphology differs between individuals with seemingly comparable load histories and why certain hips with DHD progress to symptomatic OA whereas others do not. We asked (1) which mechanical factors influence growth and development of the proximal femur; and (2) which genes or genetic mechanisms are associated with hip ontogenesis. We performed a systematic literature review of mechanical and genetic factors of hip ontogeny. We focused on three fields that in recent years have advanced our knowledge of adult hip morphology: imaging, evolution, and genetics. WHERE ARE WE NOW?: Mechanical factors can be understood in view of human evolutionary peculiarities and may summate to load histories conducive to DHD. Genetic factors most likely act through multiple genes, each with modest effect sizes. Single genes that explain a DHD are therefore unlikely to be found. Apparently, the interplay between genes and load history not only determines hip morphotype, but also joint cartilage robustness ("cartilotype") and resistance to symptomatic OA. WHERE DO WE NEED TO GO?: We need therapies that can improve both morphotype and cartilotype. HOW DO WE GET THERE?: Better phenotyping, improving classification systems of hip morphology, and comparative population studies can be done with existing methods. Quantifying load histories likely requires new tools, but proof of principle of modifying morphotype in treatment of DDH and of cartilotype with exercise is available.

Application of morphological associative memories and Fourier descriptors for classification of noisy subsurface signatures

NASA Astrophysics Data System (ADS)

Ortiz, Jorge L.; Parsiani, Hamed; Tolstoy, Leonid

2004-02-01

This paper presents a method for recognition of Noisy Subsurface Images using Morphological Associative Memories (MAM). MAM are type of associative memories that use a new kind of neural networks based in the algebra system known as semi-ring. The operations performed in this algebraic system are highly nonlinear providing additional strength when compared to other transformations. Morphological associative memories are a new kind of neural networks that provide a robust performance with noisy inputs. Two representations of morphological associative memories are used called M and W matrices. M associative memory provides a robust association with input patterns corrupted by dilative random noise, while the W associative matrix performs a robust recognition in patterns corrupted with erosive random noise. The robust performance of MAM is used in combination of the Fourier descriptors for the recognition of underground objects in Ground Penetrating Radar (GPR) images. Multiple 2-D GPR images of a site are made available by NASA-SSC center. The buried objects in these images appear in the form of hyperbolas which are the results of radar backscatter from the artifacts or objects. The Fourier descriptors of the prototype hyperbola-like and shapes from non-hyperbola shapes in the sub-surface images are used to make these shapes scale-, shift-, and rotation-invariant. Typical hyperbola-like and non-hyperbola shapes are used to calculate the morphological associative memories. The trained MAMs are used to process other noisy images to detect the presence of these underground objects. The outputs from the MAM using the noisy patterns may be equal to the training prototypes, providing a positive identification of the artifacts. The results are images with recognized hyperbolas which indicate the presence of buried artifacts. A model using MATLAB has been developed and results are presented.

Melanocytoma-like melanoma may be the missing link between benign and malignant uveal melanocytic lesions in humans and dogs: a comparative study.

PubMed

Zoroquiain, Pablo; Mayo-Goldberg, Erin; Alghamdi, Sarah; Alhumaid, Sulaiman; Perlmann, Eduardo; Barros, Paulo; Mayo, Nancy; Burnier, Miguel N

2016-12-01

The cutoff presented in the current classification of canine melanocytic lesions by Wilcock and Pfeiffer is based on the clinical outcome rather than morphological concepts. Classification of tumors based on morphology or molecular signatures is the key to identifying new therapies or prognostic factors. Therefore, the aim of this study was to analyze morphological findings in canine melanocytic lesions based on classic malignant morphologic principles of neoplasia and to compare these features with human uveal melanoma (HUM) samples. In total, 64 canine and 111 human morphologically malignant melanocytic lesions were classified into two groups (melanocytoma-like or classic melanoma) based on the presence or absence of M cells, respectively. Histopathological characteristics were compared between the two groups using the χ-test, t-test, and multivariate discriminant analysis. Among the 64 canine tumors, 28 (43.7%) were classic and 36 (56.3%) were melanocytoma-like melanomas. Smaller tumor size, a higher degree of pigmentation, and lower mitotic activity distinguished melanocytoma-like from classic tumors with an accuracy of 100% for melanocytoma-like lesions. From the human series, only one case showed melanocytoma-like features and had a low risk for metastasis characteristics. Canine uveal melanoma showed a morphological spectrum with features similar to the HUM counterpart (classic melanoma) and overlapped features between uveal melanoma and melanocytoma (melanocytoma-like melanoma). Recognition that the subgroup of melanocytoma-like melanoma may represent the missing link between benign and malignant lesions could help explain the progression of uveal melanoma in dogs; these findings can potentially be translated to HUM.

Effects of atmospheric stability and urban morphology on daytime intra-urban temperature variability for Glasgow, UK.

PubMed

Drach, Patricia; Krüger, Eduardo L; Emmanuel, Rohinton

2018-06-15

This study investigates the joint effect of atmospheric conditions and urban morphology, expressed as the Sky View Factor (SVF), on intra-urban variability. The study has been carried out in Glasgow, UK, a shrinking city with a maritime temperate climate type, and findings could guide future climate adaptation plans in terms of morphology and services provided by the municipality to overcome thermal discomfort in outdoor settings. In this case, SVF has been used as an indicator of urban morphology. The modified Pasquill-Gifford-Turner (PGT) classification system was adopted for classifying the temperature monitoring periods according to atmospheric stability conditions. Thirty two locations were selected on the basis of SVF with a wide variety of urban shapes (narrow streets, neighbourhood green spaces, urban parks, street canyons and public squares) and compared to a reference weather station during a total of twenty three transects during late spring and summer in 2013. Maximum daytime intra-urban temperature differences were found to be strongly correlated with atmospheric stability classes. Furthermore, differences in air temperature are noticeable in urban canyons, with a direct correlation to the site's SVF (or sky openness) and with an inverse trend under open-air conditions. Copyright © 2018 Elsevier B.V. All rights reserved.

Rapid evolution in lekking grouse: Implications for taxonomic definitions

USGS Publications Warehouse

Oyler-McCance, Sara J.; St. John, Judy; Quinn, Thomas W.

2010-01-01

Species and subspecies delineations were traditionally defined by morphological and behavioral traits, as well as by plumage characteristics. Molecular genetic data have more recently been used to assess these classifications and, in many cases, to redefine them. The recent practice of utilizing molecular genetic data to examine taxonomic questions has led some to suggest that molecular genetic methods are more appropriate than traditional methods for addressing taxonomic uncertainty and management units. We compared the North American Tetraoninae—which have been defined using plumage, morphology, and behavior—and considered the effects of redefinition using only neutral molecular genetic data (mitochondrial control region and cytochrome oxidase subunit 1). Using the criterion of reciprocal monophyly, we failed to recognize the five species whose mating system is highly polygynous, with males displaying on leks. In lek-breeding species, sexual selection can act to influence morphological and behavioral traits at a rate much faster than can be tracked genetically. Thus, we suggest that at least for lek-breeding species, it is important to recognize the possibility that morphological and behavioral changes may occur at an accelerated rate compared with the processes that led to reciprocal monophyly of putatively neutral genetic markers. Therefore, it is particularly important to consider the possible disconnect between such lines of evidence when making taxonomic revisions and definitions of management units.

Flat colon polyps: what should radiologists know?

PubMed

Ignjatovic, A; Burling, D; Ilangovan, R; Clark, S K; Taylor, S A; East, J E; Saunders, B P

2010-12-01

With the recent publication of international computed tomography (CT) colonography standards, which aim to improve quality of examinations, this review informs radiologists about the significance of flat polyps (adenomas and hyperplastic polyps) in colorectal cancer pathways. We describe flat polyp classification systems and propose how flat polyps should be reported to ensure patient management strategies are based on polyp morphology as well as size. Indeed, consistency when describing flat polyps is of increasing importance given the strengthening links between CT colonography and endoscopy. Copyright © 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

PubMed

Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

2016-09-01

Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.

Congenital basis of posterior fossa anomalies

PubMed Central

Cotes, Claudia; Bonfante, Eliana; Lazor, Jillian; Jadhav, Siddharth; Caldas, Maria; Swischuk, Leonard

2015-01-01

The classification of posterior fossa congenital anomalies has been a controversial topic. Advances in genetics and imaging have allowed a better understanding of the embryologic development of these abnormalities. A new classification schema correlates the embryologic, morphologic, and genetic bases of these anomalies in order to better distinguish and describe them. Although they provide a better understanding of the clinical aspects and genetics of these disorders, it is crucial for the radiologist to be able to diagnose the congenital posterior fossa anomalies based on their morphology, since neuroimaging is usually the initial step when these disorders are suspected. We divide the most common posterior fossa congenital anomalies into two groups: 1) hindbrain malformations, including diseases with cerebellar or vermian agenesis, aplasia or hypoplasia and cystic posterior fossa anomalies; and 2) cranial vault malformations. In addition, we will review the embryologic development of the posterior fossa and, from the perspective of embryonic development, will describe the imaging appearance of congenital posterior fossa anomalies. Knowledge of the developmental bases of these malformations facilitates detection of the morphological changes identified on imaging, allowing accurate differentiation and diagnosis of congenital posterior fossa anomalies. PMID:26246090

CNN-SVM for Microvascular Morphological Type Recognition with Data Augmentation.

PubMed

Xue, Di-Xiu; Zhang, Rong; Feng, Hui; Wang, Ya-Lei

2016-01-01

This paper focuses on the problem of feature extraction and the classification of microvascular morphological types to aid esophageal cancer detection. We present a patch-based system with a hybrid SVM model with data augmentation for intraepithelial papillary capillary loop recognition. A greedy patch-generating algorithm and a specialized CNN named NBI-Net are designed to extract hierarchical features from patches. We investigate a series of data augmentation techniques to progressively improve the prediction invariance of image scaling and rotation. For classifier boosting, SVM is used as an alternative to softmax to enhance generalization ability. The effectiveness of CNN feature representation ability is discussed for a set of widely used CNN models, including AlexNet, VGG-16, and GoogLeNet. Experiments are conducted on the NBI-ME dataset. The recognition rate is up to 92.74% on the patch level with data augmentation and classifier boosting. The results show that the combined CNN-SVM model beats models of traditional features with SVM as well as the original CNN with softmax. The synthesis results indicate that our system is able to assist clinical diagnosis to a certain extent.

Improving Geologic Mapping of Mid-ocean Ridges by Integrating sonar and Visual Observations through Seafloor Classification by Machine-learning Systems

NASA Astrophysics Data System (ADS)

White, S. M.; McClinton, J. T.

2011-12-01

Beyond the ability of modern near-bottom sonar systems to deliver air-photo-like images of the seafloor to help guide fieldwork, there is a tremendous amount of information hidden within sonar data that is rarely exploited for geologic mapping. Seafloor texture, backscatter amplitude, seafloor slope and roughness data can provide clues about seafloor geology but not straightforward to interpret. We present techniques for seafloor classification in volcanic terrains that integrate the capability of high-resolution, near-bottom sonar instruments to cover extensive areas of seafloor with the ability of visual mapping to discriminate differences in volcanic terrain. These techniques are adapted from the standard practices of terrestrial remote-sensing for use in the deep seafloor volcanic environment. A combination of sonar backscatter and bathymetry is used to supplement the direct seafloor visual observations by geologists to make quasi-geologic thematic maps that are consistent, objective, and most importantly spatially complete. We have taken two approaches to producing thematic maps of the seafloor for the accurate mapping of fine-scale lava morphology (e.g. pillow, lobate and sheet lava) and for the differentiation of distinct seafloor terrain types on a larger scale (e.g. hummocky or smooth). Mapping lava morphology is most accurate using fuzzy logic capable of making inferences between similar morphotypes (e.g. pillow and lobate) and where high-resolution side-scan and bathymetry data coexist. We present examples of lava morphology maps from the Galápagos Spreading Center that show the results from several analyses using different types of input data. Lava morphology is an important source of information on volcanic emplacement and eruptive dynamics. Terrain modeling can be accomplished at any resolution level, depending on the desired use of the model. For volcanic processes, input data needs to be at the appropriate scale to resolve individual volcanic features on the seafloor (e.g. small haystacks and lava channels). We present examples from the East Pacific Rise, which shows that the number of volcanic terrains differs from the tectonic provinces defined by following the spreading axis. Our terrain modeling suggests that differences in ocean crust construction and evolution can be meaningfully identified and explored without a priori assumptions about the geologic processes in a given region.

Characterization of limes (Citrus aurantifolia) grown in Bhutan and Indonesia using high-throughput sequencing

PubMed Central

Penjor, Tshering; Mimura, Takashi; Matsumoto, Ryoji; Yamamoto, Masashi; Nagano, Yukio

2014-01-01

Lime [Citrus aurantifolia (Cristm.) Swingle] is a Citrus species that is a popular ingredient in many cuisines. Some citrus plants are known to originate in the area ranging from northeastern India to southwestern China. In the current study, we characterized and compared limes grown in Bhutan (n = 5 accessions) and Indonesia (n = 3 accessions). The limes were separated into two groups based on their morphology. Restriction site-associated DNA sequencing (RAD-seq) separated the eight accessions into two clusters. One cluster contained four accessions from Bhutan, whereas the other cluster contained one accession from Bhutan and the three accessions from Indonesia. This genetic classification supported the morphological classification of limes. The analysis suggests that the properties associated with asexual reproduction, and somatic homologous recombination, have contributed to the genetic diversification of limes. PMID:24781859

A multi-gene phylogeny of Chlorophyllum (Agaricaceae, Basidiomycota): new species, new combination and infrageneric classification

PubMed Central

Ge, Zai-Wei; Jacobs, Adriaana; Vellinga, Else C.; Sysouphanthong, Phongeun; van der Walt, Retha; Lavorato, Carmine; An, Yi-Feng; Yang, Zhu L.

2018-01-01

Abstract Taxonomic and phylogenetic studies of Chlorophyllum were carried out on the basis of morphological differences and molecular phylogenetic analyses. Based on the phylogeny inferred from the internal transcribed spacer (ITS), the partial large subunit nuclear ribosomal DNA (nrLSU), the second largest subunit of RNA polymerase II (rpb2) and translation elongation factor 1-α (tef1) sequences, six well-supported clades and 17 phylogenetic species are recognised. Within this phylogenetic framework and considering the diagnostic morphological characters, two new species, C. africanum and C. palaeotropicum, are described. In addition, a new infrageneric classification of Chlorophyllum is proposed, in which the genus is divided into six sections. One new combination is also made. This study provides a robust basis for a more detailed investigation of diversity and biogeography of Chlorophyllum. PMID:29681738

[The establishment, development and application of classification approach of freshwater phytoplankton based on the functional group: a review].

PubMed

Yang, Wen; Zhu, Jin-Yong; Lu, Kai-Hong; Wan, Li; Mao, Xiao-Hua

2014-06-01

Appropriate schemes for classification of freshwater phytoplankton are prerequisites and important tools for revealing phytoplanktonic succession and studying freshwater ecosystems. An alternative approach, functional group of freshwater phytoplankton, has been proposed and developed due to the deficiencies of Linnaean and molecular identification in ecological applications. The functional group of phytoplankton is a classification scheme based on autoecology. In this study, the theoretical basis and classification criterion of functional group (FG), morpho-functional group (MFG) and morphology-based functional group (MBFG) were summarized, as well as their merits and demerits. FG was considered as the optimal classification approach for the aquatic ecology research and aquatic environment evaluation. The application status of FG was introduced, with the evaluation standards and problems of two approaches to assess water quality on the basis of FG, index methods of Q and QR, being briefly discussed.

Pathological and Molecular Evaluation of Pancreatic Neoplasms

PubMed Central

Rishi, Arvind; Goggins, Michael; Wood, Laura D.; Hruban, Ralph H.

2015-01-01

Pancreatic neoplasms are morphologically and genetically heterogeneous and include wide variety of neoplasms ranging from benign to malignant with an extremely poor clinical outcome. Our understanding of these pancreatic neoplasms has improved significantly with recent advances in cancer sequencing. Awareness of molecular pathogenesis brings in new opportunities for early detection, improved prognostication, and personalized gene-specific therapies. Here we review the pathological classification of pancreatic neoplasms from their molecular and genetic perspective. All of the major tumor types that arise in the pancreas have been sequenced, and a new classification that incorporates molecular findings together with pathological findings is now possible (Table 1). This classification has significant implications for our understanding of why tumors aggregate in some families, for the development of early detection tests, and for the development of personalized therapies for patients with established cancers. Here we describe this new classification using the framework of the standard histological classification. PMID:25726050

Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

NASA Astrophysics Data System (ADS)

Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

2017-10-01

The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Immunological classification of high grade non-Hodgkin's lymphomas (NHL) in children.

PubMed

Pituch-Noworolska, A; Miezyński, W

1994-01-01

The immunological classification of 28 high grade non-Hodgkin's lymphomas (NHL) in children was shown. The morphological classification was based on Working Formulation, the immunological classification--on acute lymphoblastic leukemia subtypes. The phenotypes were assayed cytofluorometrically with monoclonal antibodies and compared to ontogenic stages in B and T cell development. Small non-cleaved cell lymphoma (Burkitt's type) was seen in 13 patients, lymphoblastic lymphoma in 12 patients, low differentiated in 3 patients. Immunological classification showed B-lymphocyte origin of blast cells in 15 patients including 11 small non-cleaved Burkitt's lymphoma (mature B and cALL phenotype), 3 undifferentiated cases (pro-B and mature B cell) and 1 case of lymphoblastic lymphoma (cALL type). T-cell origin of blast cells was demonstrated in 13 patients. The immunological classification used routinely was helpful in selection of patients with unfavourable prognosis. The more precise description of blast cells was valuable for better adjustment of therapy and better prognosis.

Investigation of multimodal forward scatter phenotyping from bacterial colonies

NASA Astrophysics Data System (ADS)

Kim, Huisung

A rapid, label-free, and elastic light scattering (ELS) based bacterial colony phenotyping technology, bacterial rapid detection using optical scattering technology (BARDOT) provides a successful classification of several bacterial genus and species. For a thorough understanding of the phenomena and overcoming the limitations of the previous design, five additional modalities from a bacterial colony: 3D morphology, spatial optical density (OD) distribution, spectral forward scattering pattern, spectral OD, and surface backward reflection pattern are proposed to enhance the classification/identification ratio, and the feasibilities of each modality are verified. For the verification, three different instruments: integrated colony morphology analyzer (ICMA), multi-spectral BARDOT (MS-BARDOT) , and multi-modal BARDOT (MM-BARDOT) are proposed and developed. The ICMA can measure 3D morphology and spatial OD distribution of the colony simultaneously. A commercialized confocal displacement meter is used to measure the profiles of the bacterial colonies, together with a custom built optical density measurement unit to interrogate the biophysics behind the collective behavior of a bacterial colony. The system delivers essential information related to the quantitative growth dynamics (height, diameter, aspect ratio, optical density) of the bacterial colony, as well as, a relationship in between the morphological characteristics of the bacterial colony and its forward scattering pattern. Two different genera: Escherichia coli O157:H7 EDL933, and Staphylococcus aureus ATCC 25923 are selected for the analysis of the spatially resolved growth dynamics, while, Bacillus spp. such as B. subtilis ATCC 6633, B. cereus ATCC 14579, B. thuringiensis DUP6044, B. polymyxa B719W, and B. megaterium DSP 81319, are interrogated since some of the Bacillus spp. provides strikingly different characteristics of ELS patterns, and the origin of the speckle patterns are successfully correlated with the 2-D spatial density map from the ICMA. The MS-BARDOT can measure multispectral elastic-light-scatter patterns of the bacterial colony and its spectral OD to overcome the inherent limits of the single-wavelength BARDOT. A theoretical model for spectral forward scatter patterns from a bacterial colony based on elastic light scatter is presented. The spectral forward scatter patterns are computed by scalar diffraction theory, and compared with experimental results of three discrete wavelengths (405 nm, 635 nm, and 904 nm). Both model and experiment results show an excellent agreement; a longer wavelength induces a wider ring width, a wider ring gap, a smaller pattern size, and smaller numbers of rings. Further analysis using spatial fast Fourier transform (SFFT) shows a good agreement; the spatial frequencies are increasing towards the inward direction, and the slope is inversely proportional to the incoming wavelength. Four major pathogenic bacterial genera (Escherichia coli O157:H7 EDL933, Listeria monocytogenes F4244, Salmonella enterica serovar Enteritidis PT21, and Staphylococcus aureus ATCC 25923) and the seven major Escherichia coli serovar (O26, O45, O103, O111, O121, O145, and O157) with 3-4 strains each are measured and analyzed with the proposed instrument and algorithm. The MM-BARDOT can measure six different modalities: 1) light microscopy, 2) 3D morphology map from confocal microscopy, 3) 3D optical density map, 4) spectral forward scattering pattern, 5) spectral OD, 6) surface backward reflection pattern, and 7) fluorescence of a bacterial colony without moving the specimen. A custom-built confocal microscope with a controller which can be easily attached to an infinity-corrected commercial microscope is designed and built. Since the current BARDOT needs additional information from a bacterial colony to enhance the identification/classification ratio for a lower hierarchy of bacterial taxonomy such as serovar or strain level, the approach can offer a series of coordinates matched and correlated bio-optical characteristics of a colony and enhance the classification accuracy of the previously introduced BARDOT system. Four major pathogenic bacterial genera: Escherichia coli O157:H7 EDL933, Listeria monocytogenes F4244, Salmonella enterica serovar Enteritidis PT21, and Staphylococcus aureus ATCC 25923 are measured and analyzed with the proposed instrument and algorithm. Also, a feasibility test for a smaller colony (up to 500 mum) classification utilizing a surface backward reflection pattern from the measurement is done, and shows a potential as an additional modality for the bacterial phenotyping.

Association Between Peri-implant Bone Morphology and Marginal Bone Loss: A Retrospective Study on Implant-Supported Mandibular Overdentures.

PubMed

Ding, Qian; Zhang, Lei; Geraets, Wil; Wu, Wuqing; Zhou, Yongsheng; Wismeijer, Daniel; Xie, Qiufei

The present study aimed to explore the association between marginal bone loss and type of peri-implant bony defect determined using a new peri-implant bony defect classification system. A total of 110 patients with implant-supported mandibular overdentures were involved. Clinical information was collected, including gender, age, smoking habit, and the overdenture attachment system used. Peri-implant bony defect types and marginal distances (ie, distance between the marginal bone level and the top of the implant shoulder) of all sites were identified on panoramic radiographs by a single experienced observer. The associations between marginal distance and peri-implant bony defect type, gender, age, smoking habit, attachment system, and time after implantation were investigated using marginal generalized linear models and regression analysis. A total of 83 participants were included in the final sample with a total of 224 implants involving 3,124 implant sites. The mean observation time was 10.7 years. All peri-implant bony defect types except Type 5 (slit-like) were significantly related to marginal distance in all models (P < .01). Smoking and time after implantation were significantly related to marginal distance while gender, age, and the overdenture attachment system used were not. The peri-implant bony defect type, determined using the new classification system, is associated with the extent of marginal bone loss.

A GPU-based computer-assisted microscopy system for assessing the importance of different families of histological characteristics in cancer diagnosis

NASA Astrophysics Data System (ADS)

Glotsos, Dimitris; Kostopoulos, Spiros; Sidiropoulos, Konstantinos; Ravazoula, Panagiota; Kalatzis, Ioannis; Asvestas, Pantelis; Cavouras, Dionisis

2014-01-01

In this study a Computer-Aided Microscopy (CAM) system is proposed for investigating the importance of the histological criteria involved in diagnosing of cancers in microscopy in order to suggest the more informative features for discriminating low from high-grade brain tumours. Four families of criteria have been examined, involving the greylevel variations (i.e. texture), the morphology (i.e. roundness), the architecture (i.e. cellularity) and the overall tumour qualities (expert's ordinal scale). The proposed CAM system was constructed using a modified Seeded Region Growing algorithm for image segmentation, and the Probabilistic Neural Network classifier for image classification. The implementation was designed on a commercial Graphics Processing Unit card using parallel programming. The system's performance using textural, morphological, architectural and ordinal information was 90.8%, 87.0%, 81.2% and 88.9% respectively. Results indicate that nuclei texture is the most important family of features regarding the degree of malignancy, and, thus, may guide more accurate predictions for discriminating low from high grade gliomas. Considering that nuclei texture is almost impractical to be encoded by visual observation, the need to incorporate computer-aided diagnostic tools as second opinion in daily clinical practice of diagnosing rare brain tumours may be justified.

Classification of Suncus murinus species complex (Soricidae: Crocidurinae) in Peninsular Malaysia using image analysis and machine learning approaches.

PubMed

Abu, Arpah; Leow, Lee Kien; Ramli, Rosli; Omar, Hasmahzaiti

2016-12-22

Taxonomists frequently identify specimen from various populations based on the morphological characteristics and molecular data. This study looks into another invasive process in identification of house shrew (Suncus murinus) using image analysis and machine learning approaches. Thus, an automated identification system is developed to assist and simplify this task. In this study, seven descriptors namely area, convex area, major axis length, minor axis length, perimeter, equivalent diameter and extent which are based on the shape are used as features to represent digital image of skull that consists of dorsal, lateral and jaw views for each specimen. An Artificial Neural Network (ANN) is used as classifier to classify the skulls of S. murinus based on region (northern and southern populations of Peninsular Malaysia) and sex (adult male and female). Thus, specimen classification using Training data set and identification using Testing data set were performed through two stages of ANNs. At present, the classifier used has achieved an accuracy of 100% based on skulls' views. Classification and identification to regions and sexes have also attained 72.5%, 87.5% and 80.0% of accuracy for dorsal, lateral, and jaw views, respectively. This results show that the shape characteristic features used are substantial because they can differentiate the specimens based on regions and sexes up to the accuracy of 80% and above. Finally, an application was developed and can be used for the scientific community. This automated system demonstrates the practicability of using computer-assisted systems in providing interesting alternative approach for quick and easy identification of unknown species.

River network and watershed morphology analysis with potential implications towards basin classification

NASA Astrophysics Data System (ADS)

Bugaets, Andrey; Gartsman, Boris; Bugaets, Nadezhda

2013-04-01

Generally, the investigation of river network composition and watersheds morphology (fluvial geomorphology), constituting one of the key patterns of land surface, is a fundamental question of Earth Sciences. Recent ideas in this research field are the equilibrium and optimal, in the sense of minimum energy expenditure, river network evolution under constant or slowly varying conditions (Rodriguez-Iturbe, Rinaldo, 1997). It follows to such network behavior as self-similarity, self-affinity and self-organization. That is to say, under relatively stable conditions the river systems tend to some "good composed" form and vice-versa. Lately appearing global free available detailed DEM covers involve new possibilities in this research field. We develop new methodology and program package for river network structure and watershed morphology detailed analysis on the base of ArcMap tools. Different characteristics of river network (e.g. ordering, coefficients of Horton's laws, Shannon entropy, fractal dimension) and basin morphology (e.g. diagrams of average elevation, slope, width and energy index against distance to outlet along streams) could be calculated to find a good indicators of intensity and non-equilibrium of watershed evolution. Watersheds are non-conservative systems in which energy is dissipated by transporting water and sediment in geomorphic adjustment of the slopes and channels. The problem of estimating the amount of energy expenditure associated with overcoming surface and system resistance is extremely complicated to solve. A simplification on a river network scale is to consider energy expenditure to be primarily associated with friction of the fluid. We propose a new technique to analyze the catchment landforms based on so-called "energy function" that is a distribution of total energy index against distance from outlet. As potential energy of water on the hillslopes is transformed into kinetic energy of the flowing fluid-sediment mixture in the runoff process, the energy is dissipated from the system. The rate of energy dissipation is defined as the work that a fluid element needs to perform to overcome friction at the unit area. Appling the product of local slope and watershed area, i.e. calculating the total energy index at the different distance from outlet, one gets the watershed "energy function" E(x). Application results indicate that the proposed method could be used for watersheds classification, regionalization and paleoreconstructions. NASA-SRTM DEM of 3" resolution has been employed to analyze the 24 watersheds within Amur River Basin with area 20-70 thousand km2 (7-8 order). The study was carried out, in particular, to assess the limitation of SRTM DEM data, especially in flat terrains. The study also revealed that some of regularities investigated are described satisfactorily by well-known simplest model of drainage networks, so-called Peano's basin.

A partial list of southern clusters of galaxies

NASA Technical Reports Server (NTRS)

Quintana, H.; White, R. A.

1990-01-01

An inspection of 34 SRC/ESO J southern sky fields is the basis of the present list of clusters of galaxies and their approximate classifications in terms of cluster concentration, defined independently of richness and shape-symmetry. Where possible, an estimate of the cluster morphological population is provided. The Bautz-Morgan classification was applied using a strict comparison with clusters on the Palomar Sky Survey. Magnitudes were estimated on the basis of galaxies with photoelectric or photographic magnitudes.

[Analysis of morphologic classifications of testicular lesions in male sterility].

PubMed

Lysenko, A I; Kirpatovskiĭ, I D

1991-01-01

An analysis of the authors' own data based on the examination of 697 testis biopsies is given. The material is subdivided into two groups depending on the presence or absence of germ cells: 1) hypospermatogenesis and 2) aspermatogenesis. Hypospermatogenesis is related to any tubule changes resulting in the under-production of spermatozoa. Criteria of tubule changes and a method for determination of the hypospermatogenesis degree are given. Insolvency of some existing histologic classifications is shown.

Characterization and classification of patients with different levels of cardiac death risk by using Poincaré plot analysis.

PubMed

Rodriguez, Javier; Voss, Andreas; Caminal, Pere; Bayes-Genis, Antoni; Giraldo, Beatriz F

2017-07-01

Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed. Left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF > 35%, 16 patients), and high risk (HR: LVEF ≤ 35%, 30 patients) of heart attack. RR, SBP and T Tot time series were extracted from the ECG, blood pressure and respiratory flow signals, respectively. Parameters that describe the scatterplott of Poincaré method, related to short- and long-term variabilities, acceleration and deceleration of the dynamic system, and the complex correlation index were extracted. The linear discriminant analysis (LDA) and the support vector machines (SVM) classification methods were used to analyze the results of the extracted parameters. The results showed that cardiac parameters were the best to discriminate between HR and LR groups, especially the complex correlation index (p = 0.009). Analising the interaction, the best result was obtained with the relation between the difference of the standard deviation of the cardiac and respiratory system (p = 0.003). When comparing HR vs LR groups, the best classification was obtained applying SVM method, using an ANOVA kernel, with an accuracy of 98.12%. An accuracy of 97.01% was obtained by comparing patients versus healthy, with a SVM classifier and Laplacian kernel. The morphology of Poincaré plot introduces parameters that allow the characterization of the cardiorespiratory system dynamics.

Beach morphodynamics and types of foredune erosion generated by storms along the Emilia-Romagna coastline, Italy

NASA Astrophysics Data System (ADS)

Armaroli, Clara; Grottoli, Edoardo; Harley, Mitchell D.; Ciavola, Paolo

2013-10-01

The objectives of this study are to examine the response of a dune and beach system on the Adriatic coastline in northern Italy to the arrival of storms, compare it with seasonal (months) and medium-term (3-year) morphodynamic change, and evaluate results predicted by the numerical model XBeach. The studied coastline stretches 4 km from the Bevano River mouth to the north of the site to the township of Lido di Classe to the south, where the beach is protected by coastal structures. Fieldwork consisted of topographic profile surveys using RTK-DGPS technology (7 times over an approx. 3-year period). 103 samples of surface sediment were collected along 20 of the cross-shore profiles at 6 distinct cross-shore positions, selected on the basis of morphological beach characteristics. Data analyses of dune and beach slopes enabled the study area to be divided into 6 separate morphological zones using the spatial (longshore and cross-shore) variation of morphologies located on the backshore and intertidal beach observed in a preliminary survey of the area. Other criteria were a spatial consistency in beach slopes and/or presence/absence of intertidal morphologies identified in the aerial photographs and Lidar data. The swash zone slope did not show any significant variability for the entire area. A weak seasonal trend in the variability of the mean foredune slope was observed, with steeper slopes typically during winter and flatter slopes during summer. Analysis of grain size revealed that the beach sediment is well-sorted fine sand tending to medium, with a decreasing trend in size from the Bevano River mouth southwards towards Lido di Classe. According to the Masselink and Short (1993) classification, the natural part of the study site has an Intermediate Barred Beach (IBB) and following the Short (1999) classification, results in a modally LBT (longshore bar-trough) or LTT (low tide terrace) with a small section being TBR (transverse bar and rip). Storms are considered the main factor controlling changes in the beach and dune slope. The most significant storm was recorded in March 2010 with a peak significant wave height of 3.91 m. Contrary to the seasonal dune trend, several foredune slopes were observed to flatten following this event, which can be attributed to the action of dune slumping from the already weakened dune state. Modelling of foredune erosion, using a process-based model (XBeach), reproduced the erosion of the upper beach and dune toe reasonably well, but is currently limited by the acceptable slope value for dune stability, which does not account for biotic factors (e.g. plant roots). The comparison between the storm impact categories of Sallenger (2000) and the DSF (Dune Stability Factor) of Armaroli et al. (2012) shows a very good correspondence between the effects of the winter 2008-2009 storms and the vulnerability of the dune system predicted using both classifications.

Application of a new genetic classification and semi-automated geomorphic mapping approach in the Perth submarine canyon, Australia

NASA Astrophysics Data System (ADS)

Picard, K.; Nanson, R.; Huang, Z.; Nichol, S.; McCulloch, M.

2017-12-01

The acquisition of high resolution marine geophysical data has intensified in recent years (e.g. multibeam echo-sounding, sub-bottom profiling). This progress provides the opportunity to classify and map the seafloor in greater detail, using new methods that preserve the links between processes and morphology. Geoscience Australia has developed a new genetic classification approach, nested within the Harris et al (2014) global seafloor mapping framework. The approach divides parent units into sub-features based on established classification schemes and feature descriptors defined by Bradwell et al. (2016: http://nora.nerc.ac.uk/), the International Hydrographic Organization (https://www.iho.int) and the Coastal Marine and Ecological Classification Standard (https://www.cmecscatalog.org). Owing to the ecological significance of submarine canyon systems in particular, much recent attention has focused on defining their variation in form and process, whereby they can be classified using a range of topographic metrics, fluvial dis/connection and shelf-incising status. The Perth Canyon is incised into the continental slope and shelf of southwest Australia, covering an area of >1500 km2 and extending from 4700 m water depth to the shelf break in 170 m. The canyon sits within a Marine Protected Area, incorporating a Marine National Park and Habitat Protection Zone in recognition of its benthic and pelagic biodiversity values. However, detailed information of the spatial patterns of the seabed habitats that influence this biodiversity is lacking. Here we use 20 m resolution bathymetry and acoustic backscatter data acquired in 2015 by the Schmidt Ocean Institute plus sub-bottom datasets and sediment samples collected Geoscience Australia in 2005 to apply the new geomorphic classification system to the Perth Canyon. This presentation will show the results of the geomorphic feature mapping of the canyon and its application to better defining potential benthic habitats.

Focal liver lesions segmentation and classification in nonenhanced T2-weighted MRI.

PubMed

Gatos, Ilias; Tsantis, Stavros; Karamesini, Maria; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Hazle, John D; Kagadis, George C

2017-07-01

To automatically segment and classify focal liver lesions (FLLs) on nonenhanced T2-weighted magnetic resonance imaging (MRI) scans using a computer-aided diagnosis (CAD) algorithm. 71 FLLs (30 benign lesions, 19 hepatocellular carcinomas, and 22 metastases) on T2-weighted MRI scans were delineated by the proposed CAD scheme. The FLL segmentation procedure involved wavelet multiscale analysis to extract accurate edge information and mean intensity values for consecutive edges computed using horizontal and vertical analysis that were fed into the subsequent fuzzy C-means algorithm for final FLL border extraction. Texture information for each extracted lesion was derived using 42 first- and second-order textural features from grayscale value histogram, co-occurrence, and run-length matrices. Twelve morphological features were also extracted to capture any shape differentiation between classes. Feature selection was performed with stepwise multilinear regression analysis that led to a reduced feature subset. A multiclass Probabilistic Neural Network (PNN) classifier was then designed and used for lesion classification. PNN model evaluation was performed using the leave-one-out (LOO) method and receiver operating characteristic (ROC) curve analysis. The mean overlap between the automatically segmented FLLs and the manual segmentations performed by radiologists was 0.91 ± 0.12. The highest classification accuracies in the PNN model for the benign, hepatocellular carcinoma, and metastatic FLLs were 94.1%, 91.4%, and 94.1%, respectively, with sensitivity/specificity values of 90%/97.3%, 89.5%/92.2%, and 90.9%/95.6% respectively. The overall classification accuracy for the proposed system was 90.1%. Our diagnostic system using sophisticated FLL segmentation and classification algorithms is a powerful tool for routine clinical MRI-based liver evaluation and can be a supplement to contrast-enhanced MRI to prevent unnecessary invasive procedures. © 2017 American Association of Physicists in Medicine.

Prostate cancer detection using machine learning techniques by employing combination of features extracting strategies.

PubMed

Hussain, Lal; Ahmed, Adeel; Saeed, Sharjil; Rathore, Saima; Awan, Imtiaz Ahmed; Shah, Saeed Arif; Majid, Abdul; Idris, Adnan; Awan, Anees Ahmed

2018-02-06

Prostate is a second leading causes of cancer deaths among men. Early detection of cancer can effectively reduce the rate of mortality caused by Prostate cancer. Due to high and multiresolution of MRIs from prostate cancer require a proper diagnostic systems and tools. In the past researchers developed Computer aided diagnosis (CAD) systems that help the radiologist to detect the abnormalities. In this research paper, we have employed novel Machine learning techniques such as Bayesian approach, Support vector machine (SVM) kernels: polynomial, radial base function (RBF) and Gaussian and Decision Tree for detecting prostate cancer. Moreover, different features extracting strategies are proposed to improve the detection performance. The features extracting strategies are based on texture, morphological, scale invariant feature transform (SIFT), and elliptic Fourier descriptors (EFDs) features. The performance was evaluated based on single as well as combination of features using Machine Learning Classification techniques. The Cross validation (Jack-knife k-fold) was performed and performance was evaluated in term of receiver operating curve (ROC) and specificity, sensitivity, Positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR). Based on single features extracting strategies, SVM Gaussian Kernel gives the highest accuracy of 98.34% with AUC of 0.999. While, using combination of features extracting strategies, SVM Gaussian kernel with texture + morphological, and EFDs + morphological features give the highest accuracy of 99.71% and AUC of 1.00.

Diagnostic reproducibility of hydatidiform moles: ancillary techniques (p57 immunohistochemistry and molecular genotyping) improve morphologic diagnosis for both recently trained and experienced gynecologic pathologists.

PubMed

Gupta, Mamta; Vang, Russell; Yemelyanova, Anna V; Kurman, Robert J; Li, Fanghong Rose; Maambo, Emily C; Murphy, Kathleen M; DeScipio, Cheryl; Thompson, Carol B; Ronnett, Brigitte M

2012-12-01

Distinction of hydatidiform moles from nonmolar specimens (NMs) and subclassification of hydatidiform moles as complete hydatidiform mole (CHM) and partial hydatidiform mole (PHM) are important for clinical practice and investigational studies; however, diagnosis based solely on morphology is affected by interobserver variability. Molecular genotyping can distinguish these entities by discerning androgenetic diploidy, diandric triploidy, and biparental diploidy to diagnose CHMs, PHMs, and NMs, respectively. Eighty genotyped cases (27 CHMs, 27 PHMs, 26 NMs) were selected from a series of 200 potentially molar specimens previously diagnosed using p57 immunohistochemistry and genotyping. Cases were classified by 6 pathologists (3 faculty level gynecologic pathologists and 3 fellows) on the basis of morphology, masked to p57 immunostaining and genotyping results, into 1 of 3 categories (CHM, PHM, or NM) during 2 diagnostic rounds; a third round incorporating p57 immunostaining results was also conducted. Consensus diagnoses (those rendered by 2 of 3 pathologists in each group) were also determined. Performance of experienced gynecologic pathologists versus fellow pathologists was compared, using genotyping results as the gold standard. Correct classification of CHMs ranged from 59% to 100%; there were no statistically significant differences in performance of faculty versus fellows in any round (P-values of 0.13, 0.67, and 0.54 for rounds 1 to 3, respectively). Correct classification of PHMs ranged from 26% to 93%, with statistically significantly better performance of faculty versus fellows in each round (P-values of 0.04, <0.01, and <0.01 for rounds 1 to 3, respectively). Correct classification of NMs ranged from 31% to 92%, with statistically significantly better performance of faculty only in round 2 (P-values of 1.0, <0.01, and 0.61 for rounds 1 to 3, respectively). Correct classification of all cases combined ranged from 51% to 75% by morphology and 70% to 80% with p57, with statistically significantly better performance of faculty only in round 2 (P-values of 0.69, <0.01, and 0.15 for rounds 1 to 3, respectively). p57 immunostaining significantly improved recognition of CHMs (P<0.01) and had high reproducibility (κ=0.93 to 0.96) but had no impact on distinction of PHMs and NMs. Genotyping provides a definitive diagnosis for the ∼25% to 50% of cases that are misclassified by morphology, especially those that are also unresolved by p57 immunostaining.

An Automated Classification Technique for Detecting Defects in Battery Cells

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2006-01-01

Battery cell defect classification is primarily done manually by a human conducting a visual inspection to determine if the battery cell is acceptable for a particular use or device. Human visual inspection is a time consuming task when compared to an inspection process conducted by a machine vision system. Human inspection is also subject to human error and fatigue over time. We present a machine vision technique that can be used to automatically identify defective sections of battery cells via a morphological feature-based classifier using an adaptive two-dimensional fast Fourier transformation technique. The initial area of interest is automatically classified as either an anode or cathode cell view as well as classified as an acceptable or a defective battery cell. Each battery cell is labeled and cataloged for comparison and analysis. The result is the implementation of an automated machine vision technique that provides a highly repeatable and reproducible method of identifying and quantifying defects in battery cells.

Inference of RhoGAP/GTPase regulation using single-cell morphological data from a combinatorial RNAi screen.

PubMed

Nir, Oaz; Bakal, Chris; Perrimon, Norbert; Berger, Bonnie

2010-03-01

Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae)

PubMed Central

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Abstract Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks’s λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant (p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species. PMID:29134012

Soils and the soil cover of the Valley of Geysers

NASA Astrophysics Data System (ADS)

Kostyuk, D. N.; Gennadiev, A. N.

2014-06-01

The results of field studies of the soil cover within the tourist part of the Valley of Geysers in Kamchatka performed in 2010 and 2011 are discussed. The morphology of soils, their genesis, and their dependence on the degree of hydrothermal impact are characterized; the soil cover patterns developing in the valley are analyzed. On the basis of the materials provided by the Kronotskii Biospheric Reserve and original field data, the soil map of the valley has been developed. The maps of vegetation conditions, soil temperature at the depth of 15 cm, and slopes of the surface have been used for this purpose together with satellite imagery and field descriptions of reference soil profiles. The legend to the soil map includes nine soil units and seven units of parent materials and their textures. Soil names are given according to the classification developed by I.L. Goldfarb (2005) for the soils of hydrothermal fields. The designation of soil horizons follows the new Classification and Diagnostic System of Russian Soils (2004). It is suggested that a new horizon—a thermometamorphic horizon TRM—can be introduced into this system by analogy with other metamorphic (transformed in situ) horizons distinguished in this system. This horizon is typical of the soils partly or completely transformed by hydrothermal impacts.

Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides.

PubMed

Torrens, Francisco; Castellano, Gloria

2014-06-05

Pesticide residues in wine were analyzed by liquid chromatography-tandem mass spectrometry. Retentions are modelled by structure-property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy-morphological determination-natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

Leucocyte classification for leukaemia detection using image processing techniques.

PubMed

Putzu, Lorenzo; Caocci, Giovanni; Di Ruberto, Cecilia

2014-11-01

The counting and classification of blood cells allow for the evaluation and diagnosis of a vast number of diseases. The analysis of white blood cells (WBCs) allows for the detection of acute lymphoblastic leukaemia (ALL), a blood cancer that can be fatal if left untreated. Currently, the morphological analysis of blood cells is performed manually by skilled operators. However, this method has numerous drawbacks, such as slow analysis, non-standard accuracy, and dependences on the operator's skill. Few examples of automated systems that can analyse and classify blood cells have been reported in the literature, and most of these systems are only partially developed. This paper presents a complete and fully automated method for WBC identification and classification using microscopic images. In contrast to other approaches that identify the nuclei first, which are more prominent than other components, the proposed approach isolates the whole leucocyte and then separates the nucleus and cytoplasm. This approach is necessary to analyse each cell component in detail. From each cell component, different features, such as shape, colour and texture, are extracted using a new approach for background pixel removal. This feature set was used to train different classification models in order to determine which one is most suitable for the detection of leukaemia. Using our method, 245 of 267 total leucocytes were properly identified (92% accuracy) from 33 images taken with the same camera and under the same lighting conditions. Performing this evaluation using different classification models allowed us to establish that the support vector machine with a Gaussian radial basis kernel is the most suitable model for the identification of ALL, with an accuracy of 93% and a sensitivity of 98%. Furthermore, we evaluated the goodness of our new feature set, which displayed better performance with each evaluated classification model. The proposed method permits the analysis of blood cells automatically via image processing techniques, and it represents a medical tool to avoid the numerous drawbacks associated with manual observation. This process could also be used for counting, as it provides excellent performance and allows for early diagnostic suspicion, which can then be confirmed by a haematologist through specialised techniques. Copyright © 2014 Elsevier B.V. All rights reserved.

The Soil Series in Soil Classifications of the United States

NASA Astrophysics Data System (ADS)

Indorante, Samuel; Beaudette, Dylan; Brevik, Eric C.

2014-05-01

Organized national soil survey began in the United States in 1899, with soil types as the units being mapped. The soil series concept was introduced into the U.S. soil survey in 1903 as a way to relate soils being mapped in one area to the soils of other areas. The original concept of a soil series was all soil types formed in the same parent materials that were of the same geologic age. However, within about 15 years soil series became the primary units being mapped in U.S. soil survey. Soil types became subdivisions of soil series, with the subdivisions based on changes in texture. As the soil series became the primary mapping unit the concept of what a soil series was also changed. Instead of being based on parent materials and geologic age, the soil series of the 1920s was based on the morphology and composition of the soil profile. Another major change in the concept of soil series occurred when U.S. Soil Taxonomy was released in 1975. Under Soil Taxonomy, the soil series subdivisions were based on the uses the soils might be put to, particularly their agricultural uses (Simonson, 1997). While the concept of the soil series has changed over the years, the term soil series has been the longest-lived term in U.S. soil classification. It has appeared in every official classification system used by the U.S. soil survey (Brevik and Hartemink, 2013). The first classification system was put together by Milton Whitney in 1909 and had soil series at its second lowest level, with soil type at the lowest level. The second classification system used by the U.S. soil survey was developed by C.F. Marbut, H.H. Bennett, J.E. Lapham, and M.H. Lapham in 1913. It had soil series at the second highest level, with soil classes and soil types at more detailed levels. This was followed by another system in 1938 developed by M. Baldwin, C.E. Kellogg, and J. Thorp. In this system soil series were again at the second lowest level with soil types at the lowest level. The soil type concept was dropped and replaced by the soil phase in the 1950s in a modification of the 1938 Baldwin et al. classification (Simonson, 1997). When Soil Taxonomy was released in 1975, soil series became the most detailed (lowest) level of the classification system, and the only term maintained throughout all U.S. classifications to date. While the number of recognized soil series have increased steadily throughout the history of U.S. soil survey, there was a rapid increase in the recognition of new soil series following the introduction of Soil Taxonomy (Brevik and Hartemink, 2013). References Brevik, E.C., and A.E. Hartemink. 2013. Soil maps of the United States of America. Soil Science Society of America Journal 77:1117-1132. doi:10.2136/sssaj2012.0390. Simonson, R.W. 1997. Evolution of soil series and type concepts in the United States. Advances in Geoecology 29:79-108.

Texture analysis applied to second harmonic generation image data for ovarian cancer classification

NASA Astrophysics Data System (ADS)

Wen, Bruce L.; Brewer, Molly A.; Nadiarnykh, Oleg; Hocker, James; Singh, Vikas; Mackie, Thomas R.; Campagnola, Paul J.

2014-09-01

Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"-frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations-is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.

[Magnetic resonance semiotics of prostate cancer according to the PI-RADS classification. The clinical diagnostic algorithm of a study].

PubMed

Korobkin, A S; Shariya, M A; Chaban, A S; Voskanvan, G A; Vinarov, A Z

2015-01-01

to elaborate the magnetic resonance imaging (MRI) signs of prostate cancer (PC) in accordance with the PI-RADS classification during multiparametric MRI (mpMRI). A total of 89 men aged 20 to 82 years were examined. A control group consisted of 8 (9%) healthy volunteers younger than 30 years of age with no urological history to obtain control images and MRI plots and 20 (22.5%) men aged 26-76 years, whose morphological changes were inflammatory and hyperplastic. The second age-matched group included 61 (68.5%) patients diagnosed with prostate cancer at morphological examination. A set of studies included digital rectal examination, serum prostate-specific antigen, and transrectal ultrasound-guided prostate biopsy. All the patients underwent prostate mpMRI applying a 3.0 T Achieva MRI scanner (Philips, the Netherlands). The patients have been found to have mpMRI signs that were typical of PC; its MRI semiotics according to the PI-RADS classification is presented. Each mpMRI procedure has been determined to be of importance and informative value in detecting PC. The comprehensive mpMRI approach to diagnosing PC improves the quality and diagnostic value of prostate MRI.

Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks.

PubMed

Abedi, Behzad; Abbasi, Ataollah; Goshvarpour, Atefeh

2017-05-01

In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women. Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music. For each ECG signal, 20 morphological and wavelet-based features were selected. Artificial neural network (ANN) and probabilistic neural network (PNN) classifiers were used for the classification of ECG signals during and before listening to music. Collected data were separated into two data sets: train and test. Classification accuracies of 88% and 97% were achieved in train data sets using ANN and PNN, respectively. In addition, the test data set was employed for evaluating the classifiers, and classification rates of 84% and 93% were obtained using ANN and PNN, respectively. The present study investigated the effect of music on ECG signals based on wavelet transform and morphological features. The results obtained here can provide a good understanding on the effects of music on ECG signals to researchers.

State dynamics of a double sandbar system

NASA Astrophysics Data System (ADS)

Price, T. D.; Ruessink, B. G.

2011-04-01

A 9.3-year dataset of low-tide time-exposure images from Surfers Paradise, Northern Gold Coast, Australia was used to characterise the state dynamics of a double sandbar system. The morphology of the nearshore sandbars was described by means of the sequential bar state classification scheme of Wright and Short [1984. Morphodynamic variability of surf zones and beaches: a synthesis. Marine Geology 56, 93-118]. Besides the two end members (the dissipative (D) and the reflective (R) states) and the four intermediate states (longshore bar and trough (LBT), rhythmic bar and beach (RBB), transverse bar and rip (TBR) and low tide terrace (LTT)), we identified two additional intermediate bar states. The erosive transverse bar and rip (eTBR) state related to the dominant oblique angle of wave incidence at the study site and the rhythmic low tide terrace (rLTT) related to the multiple bar setting. Using the alongshore barline variability and alongshore trough continuity as morphological indicators enabled the objective classification of the inner and outer bar states from the images. The outer bar was mostly in the TBR state and generally advanced sequentially through the states LBT-RBB-TBR-eTBR-LBT, with occasional transitions to the D state. Wave events led to abrupt state transitions of the outer bar, but, in contrast to expectations, did not necessarily correspond to upstate transitions. Instead, upstate (downstate) transitions coincided with angles of wave incidence θ larger (smaller) than 30°. The upstate TBR-eTBR-LBT sequence during high-angle events highlights the role of alongshore currents in bar straightening. The outer bar was found to govern the state of the inner bar to a large extent. Two types of inner bar behaviour were distinguished, based on the outer bar state. For intermediate outer bar states, the alongshore variability of the dominant inner rLTT state (52% in time) mainly related to that of the outer bar, implying some sort of morphological coupling. For dissipative outer bar states, however, the more upstate inner bar frequently separated from the shoreline and persistently developed rip channels as TBR became the most frequent state (60% in time).

Automated image processing method for the diagnosis and classification of malaria on thin blood smears.

PubMed

Ross, Nicholas E; Pritchard, Charles J; Rubin, David M; Dusé, Adriano G

2006-05-01

Malaria is a serious global health problem, and rapid, accurate diagnosis is required to control the disease. An image processing algorithm to automate the diagnosis of malaria on thin blood smears is developed. The image classification system is designed to positively identify malaria parasites present in thin blood smears, and differentiate the species of malaria. Images are acquired using a charge-coupled device camera connected to a light microscope. Morphological and novel threshold selection techniques are used to identify erythrocytes (red blood cells) and possible parasites present on microscopic slides. Image features based on colour, texture and the geometry of the cells and parasites are generated, as well as features that make use of a priori knowledge of the classification problem and mimic features used by human technicians. A two-stage tree classifier using backpropogation feedforward neural networks distinguishes between true and false positives, and then diagnoses the species (Plasmodium falciparum, P. vivax, P. ovale or P. malariae) of the infection. Malaria samples obtained from the Department of Clinical Microbiology and Infectious Diseases at the University of the Witwatersrand Medical School are used for training and testing of the system. Infected erythrocytes are positively identified with a sensitivity of 85% and a positive predictive value (PPV) of 81%, which makes the method highly sensitive at diagnosing a complete sample provided many views are analysed. Species were correctly determined for 11 out of 15 samples.

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Matrices of carbonaceous chondrite meteorites

NASA Technical Reports Server (NTRS)

Buseck, Peter R.; Hua, Xin

1993-01-01

The morphology, classification, and chemistry of the matrices of carbonaceous chondrite (CC) meteorites is reviewed based on recent research results. The various kinds of CCs are examined in terms of their matrix mineralogy. Alteration processes in CCs are discussed.

Medical Parasitology Taxonomy Update: January 2012 to December 2015.

PubMed

Simner, P J

2017-01-01

Parasites of medical importance have long been classified taxonomically by morphological characteristics. However, molecular-based techniques have been increasingly used and relied on to determine evolutionary distances for the basis of rational hierarchal classifications. This has resulted in several different classification schemes for parasites and changes in parasite taxonomy. The purpose of this Minireview is to provide a single reference for diagnostic laboratories that summarizes new and revised clinically relevant parasite taxonomy from January 2012 through December 2015. Copyright © 2016 American Society for Microbiology.

Rock flows

NASA Technical Reports Server (NTRS)

Matveyev, S. N.

1986-01-01

Rock flows are defined as forms of spontaneous mass movements, commonly found in mountainous countries, which have been studied very little. The article considers formations known as rock rivers, rock flows, boulder flows, boulder stria, gravel flows, rock seas, and rubble seas. It describes their genesis as seen from their morphological characteristics and presents a classification of these forms. This classification is based on the difference in the genesis of the rubbly matter and characterizes these forms of mass movement according to their source, drainage, and deposit areas.

[Variants of choice of surgical treatment of chronic pancreatitis in consideration of morphological changes in the pancreas].

PubMed

Priadko, A S; Maĭstrenko, N A; Romashchenko, P N

2014-01-01

The results of examination and treatment of 445 patients with chronic pancreatitis were analyzed. It was established, that 298 (67%) patients had indications for treatment in the conditions of surgical hospital. The patients were divided into three groups according to the modified pancreatitis classification of Marseilles-Rome 1988. There were the calcifying form (n = 78), obstructive form (n = 81), inflammatory form (n = 139). The application of modern methods of diagnostics and treatment of chronic pancreatitis allowed modifying the classification by selection of subgroups for each form of the disease. It was stated, that the substantiation of variants of surgical treatment of chronic pancreatitis in consideration of morphological changes in the pancreas could improve the possibilities of medical care plan for patients with minimal complications and good quality of life in long-term period of time.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

PubMed

Held, Michael; Schmitz, Michael H A; Fischer, Bernd; Walter, Thomas; Neumann, Beate; Olma, Michael H; Peter, Matthias; Ellenberg, Jan; Gerlich, Daniel W

2010-09-01

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

Computer-assisted quantification of the skull deformity for craniosynostosis from 3D head CT images using morphological descriptor and hierarchical classification

NASA Astrophysics Data System (ADS)

Lee, Min Jin; Hong, Helen; Shim, Kyu Won; Kim, Yong Oock

2017-03-01

This paper proposes morphological descriptors representing the degree of skull deformity for craniosynostosis in head CT images and a hierarchical classifier model distinguishing among normal and different types of craniosynostosis. First, to compare deformity surface model with mean normal surface model, mean normal surface models are generated for each age range and the mean normal surface model is deformed to the deformity surface model via multi-level threestage registration. Second, four shape features including local distance and area ratio indices are extracted in each five cranial bone. Finally, hierarchical SVM classifier is proposed to distinguish between the normal and deformity. As a result, the proposed method showed improved classification results compared to traditional cranial index. Our method can be used for the early diagnosis, surgical planning and postsurgical assessment of craniosynostosis as well as quantitative analysis of skull deformity.

Synopsis of Phyllosticta in China

PubMed Central

Zhang, Ke; Shivas, Roger G.; Cai, Lei

2015-01-01

The generic concept of Phyllosticta has undergone substantial changes since its establishment in 1818. The existence of conidia with a mucilaginous sheath and an apical appendage is synapomorphic for Phyllosticta species, which has been shown in recent molecular phylogenetic studies. Thus a natural classification of Phyllosticta species should emphasize above morphological characters. Many names in Phyllosticta, both published in the scientific literatures and in publically accessible databases, need updating. In China, more than 200 species names in Phyllosticta have been recorded, of which, 158 species names are reviewed here based on their morphological descriptions and molecular data. Only 20 species of Phyllosticta are accepted from China. Other records of Phyllosticta refer to Phoma (89 records), Asteromella (14 records), Boeremia (9 records), Phomopsis (7 records) and Microsphaeropsis (1 record), with 19 names of uncertain generic classification. This work demonstrates an urgent need for the re-assessment of records of Phyllosticta worldwide. PMID:26000199

Comparative morphometry of facial surface models obtained from a stereo vision system in a healthy population

NASA Astrophysics Data System (ADS)

López, Leticia; Gastélum, Alfonso; Chan, Yuk Hin; Delmas, Patrice; Escorcia, Lilia; Márquez, Jorge

2014-11-01

Our goal is to obtain three-dimensional measurements of craniofacial morphology in a healthy population, using standard landmarks established by a physical-anthropology specialist and picked from computer reconstructions of the face of each subject. To do this, we designed a multi-stereo vision system that will be used to create a data base of human faces surfaces from a healthy population, for eventual applications in medicine, forensic sciences and anthropology. The acquisition process consists of obtaining the depth map information from three points of views, each depth map is obtained from a calibrated pair of cameras. The depth maps are used to build a complete, frontal, triangular-surface representation of the subject face. The triangular surface is used to locate the landmarks and the measurements are analyzed with a MATLAB script. The classification of the subjects was done with the aid of a specialist anthropologist that defines specific subject indices, according to the lengths, areas, ratios, etc., of the different structures and the relationships among facial features. We studied a healthy population and the indices from this population will be used to obtain representative averages that later help with the study and classification of possible pathologies.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Phylogenetic Inferences Reveal a Large Extent of Novel Biodiversity in Chemically Rich Tropical Marine Cyanobacteria

PubMed Central

Gunasekera, Sarath P.; Gerwick, William H.

2013-01-01

Benthic marine cyanobacteria are known for their prolific biosynthetic capacities to produce structurally diverse secondary metabolites with biomedical application and their ability to form cyanobacterial harmful algal blooms. In an effort to provide taxonomic clarity to better guide future natural product drug discovery investigations and harmful algal bloom monitoring, this study investigated the taxonomy of tropical and subtropical natural product-producing marine cyanobacteria on the basis of their evolutionary relatedness. Our phylogenetic inferences of marine cyanobacterial strains responsible for over 100 bioactive secondary metabolites revealed an uneven taxonomic distribution, with a few groups being responsible for the vast majority of these molecules. Our data also suggest a high degree of novel biodiversity among natural product-producing strains that was previously overlooked by traditional morphology-based taxonomic approaches. This unrecognized biodiversity is primarily due to a lack of proper classification systems since the taxonomy of tropical and subtropical, benthic marine cyanobacteria has only recently been analyzed by phylogenetic methods. This evolutionary study provides a framework for a more robust classification system to better understand the taxonomy of tropical and subtropical marine cyanobacteria and the distribution of natural products in marine cyanobacteria. PMID:23315747

Ecological Design of Fernery based on Bioregion Classification System in Ecopark Cibinong Science Center Botanic Gardens, Indonesia

NASA Astrophysics Data System (ADS)

Nafar, S.; Gunawan, A.

2017-10-01

Indonesia as mega biodiversity country has a wide variety of ferns. However, the natural habitats of ferns are currently degrading, particularly in lowlands due to the increasing level of urban-sprawl and industrial zones development. Therefore, Ecology Park (Ecopark) Cibinong Science Center-Botanic Gardens as an ex-situ conservation area is expected to be the best location to conserve the lowland ferns. The purpose of this study is to design a fernery through an ecological landscape design process. The main concept is The Journey of Fern, this concept aiming on providing users experiences in fernery by associating conservational, educational, and recreational aspects. Ecological landscape design as general is applied by the principal of reduce, reuse, and recycle (3R). Bioregion classification system is applied by grouping the plants based on the characteristics of light, water, soil, air, and temperature. The design concept is inspired by the morphology of fern and its growth patterns which is transformed into organic and geometric forms. The result of this study is a design of fernery which consist of welcome area, recreation area, service area, and conservation education area as the main area that providing 66 species of ferns.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, S I; Liparas, Dimitris; Tsolaki, Magda N

2018-05-15

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. Based on preprocessed MRI images from the organizers of a neuroimaging challenge, 3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel pathomorphologic classification of capsulo-articular lesions of the pubic symphysis in athletes to predict treatment and outcome.

PubMed

Hopp, Sascha; Ojodu, Ishaq; Jain, Atul; Fritz, Tobias; Pohlemann, Tim; Kelm, Jens

2018-05-01

Radiographic abnormalities of the symphysis as well as the formation of accessory clefts, indicating injury at the rectus-adductor aponeurosis, reportedly relate to longstanding groin pain in athletes. However, yet, no systematic classification for clinical and scientific purposes exists. We aimed to (1) create a radiographic classification based on symphysography; (2) test intra- and interobserver reliability; (3) characterise clinical significance of the morphologic patterns by evaluating success of injection therapy. We retrospectively reviewed symphysography, AP radiographs, and MRI of the pelvis from 70 consecutive competitive athletes, with chronic groin pain. Symphysographs were evaluated for intra- and interobserver variance using cohen's kappa statistics. Morphologic studies of the different contrast distribution patterns and their clinical and radiological correlation with symptom relief were investigated. All patients were followed up to evaluate immediate and long-term response to the initial therapeutic injection with steroid. Four reproducible symphysographic patterns were identified: type 0, no changes; type 1, symphyseal disk degeneration; types 2a with unilateral clefts, bilateral clefts (2b), suprapubic clefts (2c); and type 3, with expanded or multidirectional clefts. Analysis revealed excellent intra (0.94)-and interobserver (0.90) reliability. Our findings showed that 78.6% of our patients had significant short-term improvement enabling early resumption of physiotherapy, only in types 1 and 2 (p = 0.001), while type 0 and 3 did not respond. At follow-up, only 21.8% had permanent pain relief. Regarding the detection of pathologic clefts with symphysography, sensitivity (88%) and specifity (77%) were superior to that of MRI. A reproducible symphysography-based classification of distinct morphologic patterns is proposed. It serves as a predictive tool for response to injection therapy in a select group of pathologic lesions. Complete recovery after injection can only be expected in a lesser percentage, as this might indicate surgical treatment for long-term non-responders.

Hidden among Sea Anemones: The First Comprehensive Phylogenetic Reconstruction of the Order Actiniaria (Cnidaria, Anthozoa, Hexacorallia) Reveals a Novel Group of Hexacorals

PubMed Central

Rodríguez, Estefanía; Barbeitos, Marcos S.; Brugler, Mercer R.; Crowley, Louise M.; Grajales, Alejandro; Gusmão, Luciana; Häussermann, Verena; Reft, Abigail; Daly, Marymegan

2014-01-01

Sea anemones (order Actiniaria) are among the most diverse and successful members of the anthozoan subclass Hexacorallia, occupying benthic marine habitats across all depths and latitudes. Actiniaria comprises approximately 1,200 species of solitary and skeleton-less polyps and lacks any anatomical synapomorphy. Although monophyly is anticipated based on higher-level molecular phylogenies of Cnidaria, to date, monophyly has not been explicitly tested and at least some hypotheses on the diversification of Hexacorallia have suggested that actiniarians are para- or poly-phyletic. Published phylogenies have demonstrated the inadequacy of existing morphological-based classifications within Actiniaria. Superfamilial groups and most families and genera that have been rigorously studied are not monophyletic, indicating conflict with the current hierarchical classification. We test the monophyly of Actiniaria using two nuclear and three mitochondrial genes with multiple analytical methods. These analyses are the first to include representatives of all three currently-recognized suborders within Actiniaria. We do not recover Actiniaria as a monophyletic clade: the deep-sea anemone Boloceroides daphneae, previously included within the infraorder Boloceroidaria, is resolved outside of Actiniaria in several of the analyses. We erect a new genus and family for B. daphneae, and rank this taxon incerti ordinis. Based on our comprehensive phylogeny, we propose a new formal higher-level classification for Actiniaria composed of only two suborders, Anenthemonae and Enthemonae. Suborder Anenthemonae includes actiniarians with a unique arrangement of mesenteries (members of Edwardsiidae and former suborder Endocoelantheae). Suborder Enthemonae includes actiniarians with the typical arrangement of mesenteries for actiniarians (members of former suborders Protantheae, Ptychodacteae, and Nynantheae and subgroups therein). We also erect subgroups within these two newly-erected suborders. Although some relationships among these newly-defined groups are still ambiguous, morphological and molecular results are consistent enough to proceed with a new higher-level classification and to discuss the putative functional and evolutionary significance of several morphological attributes within Actiniaria. PMID:24806477

HPV- and non-HPV-related subtypes of penile squamous cell carcinoma (SCC): Morphological features and differential diagnosis according to the new WHO classification (2015).

PubMed

Sanchez, Diego F; Cañete, Sofía; Fernández-Nestosa, María José; Lezcano, Cecilia; Rodríguez, Ingrid; Barreto, José; Alvarado-Cabrero, Isabel; Cubilla, Antonio L

2015-05-01

The majority of penile carcinomas are squamous cell carcinomas originating in the squamous mucosa covering the glans, coronal sulcus, or inner surface of the foreskin, the 3 latter sites comprising the penile anatomical compartments. There is a variegated spectrum of subtypes of penile squamous cell carcinomas according to recent classification schemes. Currently, because of etiological and prognostic considerations, 2 morphologically and molecularly distinctive groups of subtypes of penile SCCs based on the presence of HPV were delineated. The predominant cell composition of tumors associated with HPV is the basaloid cell, which is the hallmark and best tissue marker for the virus. Tumors negative for the virus, however, are preferentially of lower grade and keratinizing maturing neoplasms with the exception of sarcomatoid carcinoma. HPV is detected in research studies by PCR or in situ hybridization (ISH) technologies, but p16 immunohistochemical stain is an adequate and less-expensive surrogate that is useful in the routine practice of pathology. The aim of this review is to demonstrate the variable morphological phenotypic expression of penile tumors separating non-HPV- and HPV-related neoplasms and to add morphological information that will justify subclassifying squamous cell carcinomas in a number of special subtypes. A brief discussion of the differential diagnosis in each category is also provided. Copyright © 2015 Elsevier Inc. All rights reserved.

Ancestral State Reconstruction Reveals Rampant Homoplasy of Diagnostic Morphological Characters in Urticaceae, Conflicting with Current Classification Schemes

PubMed Central

Wu, Zeng-Yuan; Milne, Richard I.; Chen, Chia-Jui; Liu, Jie; Wang, Hong; Li, De-Zhu

2015-01-01

Urticaceae is a family with more than 2000 species, which contains remarkable morphological diversity. It has undergone many taxonomic reorganizations, and is currently the subject of further systematic studies. To gain more resolution in systematic studies and to better understand the general patterns of character evolution in Urticaceae, based on our previous phylogeny including 169 accessions comprising 122 species across 47 Urticaceae genera, we examined 19 diagnostic characters, and analysed these employing both maximum-parsimony and maximum-likelihood approaches. Our results revealed that 16 characters exhibited multiple state changes within the family, with ten exhibiting >eight changes and three exhibiting between 28 and 40. Morphological synapomorphies were identified for many clades, but the diagnostic value of these was often limited due to reversals within the clade and/or homoplasies elsewhere. Recognition of the four clades comprising the family at subfamily level can be supported by a small number carefully chosen defining traits for each. Several non-monophyletic genera appear to be defined only by characters that are plesiomorphic within their clades, and more detailed work would be valuable to find defining traits for monophyletic clades within these. Some character evolution may be attributed to adaptive evolution in Urticaceae due to shifts in habitat or vegetation type. This study demonstrated the value of using phylogeny to trace character evolution, and determine the relative importance of morphological traits for classification. PMID:26529598

Robust Phylogeny of Tetrastigma (Vitaceae) Based on Ten Plastid DNA Regions: Implications for Infrageneric Classification and Seed Character Evolution

PubMed Central

Habib, Sadaf; Dang, Viet-Cuong; Ickert-Bond, Stefanie M.; Zhang, Jin-Long; Lu, Li-Min; Wen, Jun; Chen, Zhi-Duan

2017-01-01

Tetrastigma (Miq.) Planch. is one of the most species-rich genera of the economically and agronomically important grape family Vitaceae. It includes ca. 95 species widely distributed in the tropics and subtropics of Asia and Australia. Species of Tetrastigma exhibit great diversity in both vegetative and reproductive characters. Here we inferred a well-supported phylogeny of Tetrastigma based on ten chloroplast DNA regions with an expanded taxon sampling of 72 species and two varieties. Our molecular results support six major clades within Tetrastigma and the relationships among these clades were well-resolved. We also documented seed morphology of 44 species covering the six major clades of the genus. Ancestral states of eight characters (seed shape, seed surface rumination pattern, chalaza length/width ratio, chalaza position, ventral infold position, ventral infold divergence, ventral infold depth in cross section, and endosperm shape) were reconstructed in Mesquite and R with four models. Character optimizations suggest that all character states have evolved multiple times except that the irregular-shaped surface rumination has derived only once in Tetrastigma. We evaluated the taxonomic importance of seed morphology and identified potential morphological evidence to support each major clade. Our comprehensive analyses of Tetrastigma shed insights into the infrageneric classification of this morphologically diverse and ecologically important genus in tropical and subtropical Asia. PMID:28491066

The morphology of faint galaxies in Medium Deep Survey images using WFPC2

NASA Technical Reports Server (NTRS)

Griffiths, R. E.; Casertano, S.; Ratnatunga, K. U.; Neuschaefer, L. W.; Ellis, R. S.; Gilmore, G. F.; Glazebrook, K.; Santiago, B.; Huchra, J. P.; Windhorst, R. A.

1994-01-01

First results from Hubble Space Telescope (HST) Medium Deep Survey images taken with Wide Field/Planetary Camera-2 (WFPC2) demonstrate that galaxy classifications can be reliably performed to magnitudes I814 approximately less than 22.0 in the F815W band. Published spectroscopic surveys to this depth indicate a mean redshift of bar-z approximately 0.5. We have classified over 200 galaxies in nine WFPC2 fields according to a basic morphological scheme. The majority of these faint galaxies appear to be similar to regular Hubble-sequence examples observed at low redshift. To the precision of our classification scheme, the relative proportion of spheroidal and disk systems of normal appearance is as expected from nearby samples, indicating that the bulk of the local galaxy population was in place at half the Hubble time. However, the most intriguing result is the relatively high proportion (approximately 40%) of objects which are in some way anomalous, and which may be of relevance in understanding the origin of the familiar excess population of faint galaxies established by others. These diverse objects include apparently interacting pairs whose multiple structure is only revealed with HST's angular resolution, galaxies with superluminous star-forming regions, diffuse low surface brightness galaxies of various forms, and compact galaxies. These anomalous galaxies contribute a substantial fraction of the excess counts at our limiting magnitude, and may provide insights into the 'faint blue galaxy' problem.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruvindy, Rendy; White III, Richard Allen; Neilan, Brett Anthony

Modern microbial mats are potential analogues of some of Earth’s earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic nextgeneration sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marinemore » mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats.« less

Radio Galaxy Zoo: compact and extended radio source classification with deep learning

NASA Astrophysics Data System (ADS)

Lukic, V.; Brüggen, M.; Banfield, J. K.; Wong, O. I.; Rudnick, L.; Norris, R. P.; Simmons, B.

2018-05-01

Machine learning techniques have been increasingly useful in astronomical applications over the last few years, for example in the morphological classification of galaxies. Convolutional neural networks have proven to be highly effective in classifying objects in image data. In the context of radio-interferometric imaging in astronomy, we looked for ways to identify multiple components of individual sources. To this effect, we design a convolutional neural network to differentiate between different morphology classes using sources from the Radio Galaxy Zoo (RGZ) citizen science project. In this first step, we focus on exploring the factors that affect the performance of such neural networks, such as the amount of training data, number and nature of layers, and the hyperparameters. We begin with a simple experiment in which we only differentiate between two extreme morphologies, using compact and multiple-component extended sources. We found that a three-convolutional layer architecture yielded very good results, achieving a classification accuracy of 97.4 per cent on a test data set. The same architecture was then tested on a four-class problem where we let the network classify sources into compact and three classes of extended sources, achieving a test accuracy of 93.5 per cent. The best-performing convolutional neural network set-up has been verified against RGZ Data Release 1 where a final test accuracy of 94.8 per cent was obtained, using both original and augmented images. The use of sigma clipping does not offer a significant benefit overall, except in cases with a small number of training images.

A morphometric assessment and classification of coral reef spur and groove morphology

NASA Astrophysics Data System (ADS)

Duce, S.; Vila-Concejo, A.; Hamylton, S. M.; Webster, J. M.; Bruce, E.; Beaman, R. J.

2016-07-01

Spurs and grooves (SaGs) are a common and important feature of coral reef fore slopes worldwide. However, they are difficult to access and hence their morphodynamics and formation are poorly understood. We use remote sensing, with extensive ground truthing, to measure SaG morphometrics and environmental factors at 11,430 grooves across 17 reefs in the southern Great Barrier Reef, Australia. We revealed strong positive correlations between groove length, orientation and wave exposure with longer, more closely-spaced grooves oriented easterly reflecting the dominant swell regime. Wave exposure was found to be the most important factor controlling SaG distribution and morphology. Gradient of the upper reef slope was also an important limiting factor, with SaGs less likely to develop in steeply sloping (> 5°) areas. We used a subset of the morphometric data (11 reefs) to statistically define four classes of SaG. This classification scheme was tested on the remaining six reefs. SaGs in the four classes differ in morphology, groove substrate and coral cover. These differences provide insights into SaG formation mechanisms with implications to reef platform growth and evolution. We hypothesize SaG formation is dominated by coral growth processes at two classes and erosion processes at one class. A fourth class may represent relic features formed earlier in the Holocene transgression. The classes are comparable with SaGs elsewhere, suggesting the classification could be applied globally with the addition of new classes if necessary. While further research is required, we show remotely sensed SaG morphometrics can provide useful insights into reef platform evolution.

Classification and phylogeny of the cyanobiont Anabaena azollae Strasburger: an answered question?

PubMed

Pereira, Ana L; Vasconcelos, Vitor

2014-06-01

The symbiosis Azolla-Anabaena azollae, with a worldwide distribution in pantropical and temperate regions, is one of the most studied, because of its potential application as a biofertilizer, especially in rice fields, but also as an animal food and in phytoremediation. The cyanobiont is a filamentous, heterocystic cyanobacterium that inhabits the foliar cavities of the pteridophyte and the indusium on the megasporocarp (female reproductive structure). The classification and phylogeny of the cyanobiont is very controversial: from its morphology, it has been named Nostoc azollae, Anabaena azollae, Anabaena variabilis status azollae and recently Trichormus azollae, but, from its 16S rRNA gene sequence, it has been assigned to Nostoc and/or Anabaena, and from its phycocyanin gene sequence, it has been assigned as non-Nostoc and non-Anabaena. The literature also points to a possible co-evolution between the cyanobiont and the Azolla host, since dendrograms and phylogenetic trees of fatty acids, short tandemly repeated repetitive (STRR) analysis and restriction fragment length polymorphism (RFLP) analysis of nif genes and the 16S rRNA gene give a two-cluster association that matches the two-section ranking of the host (Azolla). Another controversy surrounds the possible existence of more than one genus or more than one species strain. The use of freshly isolated or cultured cyanobionts is an additional problem, since their morphology and protein profiles are different. This review gives an overview of how morphological, chemical and genetic analyses influence the classification and phylogeny of the cyanobiont and future research. © 2014 IUMS.

The distribution of early- and late-type galaxies in the Coma cluster

NASA Technical Reports Server (NTRS)

Doi, M.; Fukugita, M.; Okamura, S.; Turner, E. L.

1995-01-01

The spatial distribution and the morohology-density relation of Coma cluster galaxies are studied using a new homogeneous photmetric sample of 450 galaxies down to B = 16.0 mag with quantitative morphology classification. The sample covers a wide area (10 deg X 10 deg), extending well beyond the Coma cluster. Morphological classifications into early- (E+SO) and late-(S) type galaxies are made by an automated algorithm using simple photometric parameters, with which the misclassification rate is expected to be approximately 10% with respect to early and late types given in the Third Reference Catalogue of Bright Galaxies. The flattened distribution of Coma cluster galaxies, as noted in previous studies, is most conspicuously seen if the early-type galaxies are selected. Early-type galaxies are distributed in a thick filament extended from the NE to the WSW direction that delineates a part of large-scale structure. Spiral galaxies show a distribution with a modest density gradient toward the cluster center; at least bright spiral galaxies are present close to the center of the Coma cluster. We also examine the morphology-density relation for the Coma cluster including its surrounding regions.

Retinal ganglion cells in the eastern newt Notophthalmus viridescens: topography, morphology, and diversity.

PubMed

Pushchin, Igor I; Karetin, Yuriy A

2009-10-20

The topography and morphology of retinal ganglion cells (RGCs) in the eastern newt were studied. Cells were retrogradely labeled with tetramethylrhodamine-conjugated dextran amines or horseradish peroxidase and examined in retinal wholemounts. Their total number was 18,025 +/- 3,602 (mean +/- SEM). The spatial density of RGCs varied from 2,100 cells/mm(2) in the retinal periphery to 4,500 cells/mm(2) in the dorsotemporal retina. No prominent retinal specializations were found. The spatial resolution estimated from the spatial density of RGCs varied from 1.4 cycles per degree in the periphery to 1.95 cycles per degree in the region of the peak RGC density. A sample of 68 cells was camera lucida drawn and subjected to quantitative analysis. A total of 21 parameters related to RGC morphology and stratification in the retina were estimated. Partitionings obtained by using different clustering algorithms combined with automatic variable weighting and dimensionality reduction techniques were compared, and an effective solution was found by using silhouette analysis. A total of seven clusters were identified and associated with potential cell types. Kruskal-Wallis ANOVA-on-Ranks with post hoc Mann-Whitney U tests showed significant pairwise between-cluster differences in one or more of the clustering variables. The average silhouette values of the clusters were reasonably high, ranging from 0.52 to 0.79. Cells assigned to the same cluster displayed similar morphology and stratification in the retina. The advantages and limitations of the methodology adopted are discussed. The present classification is compared with known morphological and physiological RGC classifications in other salamanders.

Morphological evaluation of clefts of the lip, palate, or both in dogs.

PubMed

Peralta, Santiago; Fiani, Nadine; Kan-Rohrer, Kimi H; Verstraete, Frank J M

2017-08-01

OBJECTIVE To systematically characterize the morphology of cleft lip, cleft palate, and cleft lip and palate in dogs. ANIMALS 32 client-owned dogs with clefts of the lip (n = 5), palate (23), or both (4) that had undergone a CT or cone-beam CT scan of the head prior to any surgical procedures involving the oral cavity or face. PROCEDURES Dog signalment and skull type were recorded. The anatomic form of each defect was characterized by use of a widely used human oral-cleft classification system on the basis of CT findings and clinical images. Other defect morphological features, including shape, relative size, facial symmetry, and vomer involvement, were also recorded. RESULTS 9 anatomic forms of cleft were identified. Two anatomic forms were identified in the 23 dogs with cleft palate, in which differences in defect shape and size as well as vomer abnormalities were also evident. Seven anatomic forms were observed in 9 dogs with cleft lip or cleft lip and palate, and most of these dogs had incisive bone abnormalities and facial asymmetry. CONCLUSIONS AND CLINICAL RELEVANCE The morphological features of congenitally acquired cleft lip, cleft palate, and cleft lip and palate were complex and varied among dogs. The features identified here may be useful for surgical planning, developing of clinical coding schemes, or informing genetic, embryological, or clinical research into birth defects in dogs and other species.

Automated method for the identification and analysis of vascular tree structures in retinal vessel network

NASA Astrophysics Data System (ADS)

Joshi, Vinayak S.; Garvin, Mona K.; Reinhardt, Joseph M.; Abramoff, Michael D.

2011-03-01

Structural analysis of retinal vessel network has so far served in the diagnosis of retinopathies and systemic diseases. The retinopathies are known to affect the morphologic properties of retinal vessels such as course, shape, caliber, and tortuosity. Whether the arteries and the veins respond to these changes together or in tandem has always been a topic of discussion. However the diseases such as diabetic retinopathy and retinopathy of prematurity have been diagnosed with the morphologic changes specific either to arteries or to veins. Thus a method describing the separation of retinal vessel trees imaged in a two dimensional color fundus image may assist in artery-vein classification and quantitative assessment of morphologic changes particular to arteries or veins. We propose a method based on mathematical morphology and graph search to identify and label the retinal vessel trees, which provides a structural mapping of vessel network in terms of each individual primary vessel, its branches and spatial positions of branching and cross-over points. The method was evaluated on a dataset of 15 fundus images resulting into an accuracy of 92.87 % correctly assigned vessel pixels when compared with the manual labeling of separated vessel trees. Accordingly, the structural mapping method performs well and we are currently investigating its potential in evaluating the characteristic properties specific to arteries or veins.

Application of 2D and 3D image technologies to characterise morphological attributes of grapevine clusters.

PubMed

Tello, Javier; Cubero, Sergio; Blasco, José; Tardaguila, Javier; Aleixos, Nuria; Ibáñez, Javier

2016-10-01

Grapevine cluster morphology influences the quality and commercial value of wine and table grapes. It is routinely evaluated by subjective and inaccurate methods that do not meet the requirements set by the food industry. Novel two-dimensional (2D) and three-dimensional (3D) machine vision technologies emerge as promising tools for its automatic and fast evaluation. The automatic evaluation of cluster length, width and elongation was successfully achieved by the analysis of 2D images, significant and strong correlations with the manual methods being found (r = 0.959, 0.861 and 0.852, respectively). The classification of clusters according to their shape can be achieved by evaluating their conicity in different sections of the cluster. The geometric reconstruction of the morphological volume of the cluster from 2D features worked better than the direct 3D laser scanning system, showing a high correlation (r = 0.956) with the manual approach (water displacement method). In addition, we constructed and validated a simple linear regression model for cluster compactness estimation. It showed a high predictive capacity for both the training and validation subsets of clusters (R(2)  = 84.5 and 71.1%, respectively). The methodologies proposed in this work provide continuous and accurate data for the fast and objective characterisation of cluster morphology. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Management of thoracolumbar spine trauma: An overview

PubMed Central

Rajasekaran, S; Kanna, Rishi Mugesh; Shetty, Ajoy Prasad

2015-01-01

Thoracolumbar spine fractures are common injuries that can result in significant disability, deformity and neurological deficit. Controversies exist regarding the appropriate radiological investigations, the indications for surgical management and the timing, approach and type of surgery. This review provides an overview of the epidemiology, biomechanical principles, radiological and clinical evaluation, classification and management principles. Literature review of all relevant articles published in PubMed covering thoracolumbar spine fractures with or without neurologic deficit was performed. The search terms used were thoracolumbar, thoracic, lumbar, fracture, trauma and management. All relevant articles and abstracts covering thoracolumbar spine fractures with and without neurologic deficit were reviewed. Biomechanically the thoracolumbar spine is predisposed to a higher incidence of spinal injuries. Computed tomography provides adequate bony detail for assessing spinal stability while magnetic resonance imaging shows injuries to soft tissues (posterior ligamentous complex [PLC]) and neurological structures. Different classification systems exist and the most recent is the AO spine knowledge forum classification of thoracolumbar trauma. Treatment includes both nonoperative and operative methods and selected based on the degree of bony injury, neurological involvement, presence of associated injuries and the integrity of the PLC. Significant advances in imaging have helped in the better understanding of thoracolumbar fractures, including information on canal morphology and injury to soft tissue structures. The ideal classification that is simple, comprehensive and guides management is still elusive. Involvement of three columns, progressive neurological deficit, significant kyphosis and canal compromise with neurological deficit are accepted indications for surgical stabilization through anterior, posterior or combined approaches. PMID:25593358

DeepPap: Deep Convolutional Networks for Cervical Cell Classification.

PubMed

Zhang, Ling; Le Lu; Nogues, Isabella; Summers, Ronald M; Liu, Shaoxiong; Yao, Jianhua

2017-11-01

Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most traditional classification methods relies on the presence of accurate cell segmentations. Despite sixty years of research in this field, accurate segmentation remains a challenge in the presence of cell clusters and pathologies. Moreover, previous classification methods are only built upon the extraction of hand-crafted features, such as morphology and texture. This paper addresses these limitations by proposing a method to directly classify cervical cells-without prior segmentation-based on deep features, using convolutional neural networks (ConvNets). First, the ConvNet is pretrained on a natural image dataset. It is subsequently fine-tuned on a cervical cell dataset consisting of adaptively resampled image patches coarsely centered on the nuclei. In the testing phase, aggregation is used to average the prediction scores of a similar set of image patches. The proposed method is evaluated on both Pap smear and LBC datasets. Results show that our method outperforms previous algorithms in classification accuracy (98.3%), area under the curve (0.99) values, and especially specificity (98.3%), when applied to the Herlev benchmark Pap smear dataset and evaluated using five-fold cross validation. Similar superior performances are also achieved on the HEMLBC (H&E stained manual LBC) dataset. Our method is promising for the development of automation-assisted reading systems in primary cervical screening.

Object-based delineation and classification of alluvial fans by application of mean-shift segmentation and support vector machines

NASA Astrophysics Data System (ADS)

Pipaud, Isabel; Lehmkuhl, Frank

2017-09-01

In the field of geomorphology, automated extraction and classification of landforms is one of the most active research areas. Until the late 2000s, this task has primarily been tackled using pixel-based approaches. As these methods consider pixels and pixel neighborhoods as the sole basic entities for analysis, they cannot account for the irregular boundaries of real-world objects. Object-based analysis frameworks emerging from the field of remote sensing have been proposed as an alternative approach, and were successfully applied in case studies falling in the domains of both general and specific geomorphology. In this context, the a-priori selection of scale parameters or bandwidths is crucial for the segmentation result, because inappropriate parametrization will either result in over-segmentation or insufficient segmentation. In this study, we describe a novel supervised method for delineation and classification of alluvial fans, and assess its applicability using a SRTM 1‧‧ DEM scene depicting a section of the north-eastern Mongolian Altai, located in northwest Mongolia. The approach is premised on the application of mean-shift segmentation and the use of a one-class support vector machine (SVM) for classification. To consider variability in terms of alluvial fan dimension and shape, segmentation is performed repeatedly for different weightings of the incorporated morphometric parameters as well as different segmentation bandwidths. The final classification layer is obtained by selecting, for each real-world object, the most appropriate segmentation result according to fuzzy membership values derived from the SVM classification. Our results show that mean-shift segmentation and SVM-based classification provide an effective framework for delineation and classification of a particular landform. Variable bandwidths and terrain parameter weightings were identified as being crucial for consideration of intra-class variability, and, in turn, for a constantly high segmentation quality. Our analysis further reveals that incorporation of morphometric parameters quantifying specific morphological aspects of a landform is indispensable for developing an accurate classification scheme. Alluvial fans exhibiting accentuated composite morphologies were identified as a major challenge for automatic delineation, as they cannot be fully captured by a single segmentation run. There is, however, a high probability that this shortcoming can be overcome by enhancing the presented approach with a routine merging fan sub-entities based on their spatial relationships.

Inter-observer variance with the diagnosis of myelodysplastic syndromes (MDS) following the 2008 WHO classification.

PubMed

Font, P; Loscertales, J; Benavente, C; Bermejo, A; Callejas, M; Garcia-Alonso, L; Garcia-Marcilla, A; Gil, S; Lopez-Rubio, M; Martin, E; Muñoz, C; Ricard, P; Soto, C; Balsalobre, P; Villegas, A

2013-01-01

Morphology is the basis of the diagnosis of myelodysplastic syndromes (MDS). The WHO classification offers prognostic information and helps with the treatment decisions. However, morphological changes are subject to potential inter-observer variance. The aim of our study was to explore the reliability of the 2008 WHO classification of MDS, reviewing 100 samples previously diagnosed with MDS using the 2001 WHO criteria. Specimens were collected from 10 hospitals and were evaluated by 10 morphologists, working in five pairs. Each observer evaluated 20 samples, and each sample was analyzed independently by two morphologists. The second observer was blinded to the clinical and laboratory data, except for the peripheral blood (PB) counts. Nineteen cases were considered as unclassified MDS (MDS-U) by the 2001 WHO classification, but only three remained as MDS-U by the 2008 WHO proposal. Discordance was observed in 26 of the 95 samples considered suitable (27 %). Although there were a high number of observers taking part, the rate of discordance was quite similar among the five pairs. The inter-observer concordance was very good regarding refractory anemia with excess blasts type 1 (RAEB-1) (10 of 12 cases, 84 %), RAEB-2 (nine of 10 cases, 90 %), and also good regarding refractory cytopenia with multilineage dysplasia (37 of 50 cases, 74 %). However, the categories with unilineage dysplasia were not reproducible in most of the cases. The rate of concordance with refractory cytopenia with unilineage dysplasia was 40 % (two of five cases) and 25 % with RA with ring sideroblasts (two of eight). Our results show that the 2008 WHO classification gives a more accurate stratification of MDS but also illustrates the difficulty in diagnosing MDS with unilineage dysplasia.

Vasculitic wheel - an algorithmic approach to cutaneous vasculitides.

PubMed

Ratzinger, Gudrun; Zelger, Bettina Gudrun; Carlson, J Andrew; Burgdorf, Walter; Zelger, Bernhard

2015-11-01

Previous classifications of vasculitides suffer from several defects. First, classifications may follow different principles including clinicopathologic findings, etiology, pathogenesis, prognosis, or therapeutic options. Second, authors fail to distinguish between vasculitis and coagulopathy. Third, vasculitides are systemic diseases. Organ-specific variations make morphologic findings difficult to compare. Fourth, subtle changes are recognized in the skin, but may be asymptomatic in other organs. Our aim was to use the skin and subcutis as a model and the clinicopathologic correlation as the basic process for classification. We use an algorithmic approach with pattern analysis, which allows for consistent reporting of microscopic findings. We first differentiate between small and medium vessel vasculitis. In the second step, we differentiate the subtypes of small (capillaries versus postcapillary venules) and medium-sized (arterioles/arteries versus veins) vessels. In the final step, we differentiate, according to the predominant cell type, into leukocytoclastic and/or granulomatous vasculitis. Starting from leukocytoclastic vasculitis as a central reaction pattern of cutaneous small/medium vessel vasculitides, its relations or variations may be arranged around it like spokes of a wheel around the hub. This may help establish some basic order in this rather complex realm of cutaneous vasculitides, leading to a better understanding in a complicated field. © 2015 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

Review of the genera of Conoderinae (Coleoptera, Curculionidae) from North America, Central America, and the Caribbean

PubMed Central

Anzaldo, Salvatore S.

2017-01-01

Abstract The thirty-nine extant genera of Conoderinae known to occur in North America, Central America, and the Caribbean are reviewed based on external morphology. An identification key is provided along with diagnoses, distributions, species counts, and natural history information, when known, for each genus. Morphological character systems of importance for weevil classification are surveyed, potential relationships among the tribes and genera are discussed, and groups most in need of taxonomic and phylogenetic attention are identified. The following genera are transferred to new tribes: Acoptus LeConte, 1876 from the Lechriopini to the Othippiini (new placement) and the South American genus Hedycera Pascoe, 1870 from the Lechriopini to the Piazurini (new placement). Philides Champion, 1906 and Philinna Champion, 1906 are transferred from the Lechriopini to Conoderinae incertae sedis (new placement) although their placement as conoderines is uncertain. The species Copturomimus cinereus Heller, 1895 is designated as the type species of the genus Copturomimus Heller, 1895. PMID:28769729

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera).

PubMed

De Souza, Daiana A; Wang, Ying; Kaftanoglu, Osman; De Jong, David; Amdam, Gro V; Gonçalves, Lionel S; Francoy, Tiago M

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera)

PubMed Central

A. De Souza, Daiana; Wang, Ying; Kaftanoglu, Osman; De Jong, David; V. Amdam, Gro; S. Gonçalves, Lionel; M. Francoy, Tiago

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates. PMID:25894528

Predicted singers' vocal fold lengths and voice classification-a study of x-ray morphological measures.

PubMed

Roers, Friederike; Mürbe, Dirk; Sundberg, Johan

2009-07-01

Students admitted to the solo singing education at the University of Music Dresden, Germany have been submitted to a detailed physical examination of a variety of factors with relevance to voice function since 1959. In the years 1959-1991, this scheme of examinations included X-ray profiles of the singers' vocal tracts. This material of 132 X-rays of voice professionals was used to investigate different laryngeal morphological measures and their relation to vocal fold length. Further, the study aimed to investigate if there are consistent anatomical differences between singers of different voice classifications. The study design used was a retrospective analysis. Vocal fold length could be measured in 29 of these singer subjects directly. These data showed a strong correlation with the anterior-posterior diameter of the subglottis and the trachea as well as with the distance from the anterior contour of the thyroid cartilage to the anterior contour of the spine. These relations were used in an attempt to predict the 132 singers' vocal fold lengths. The results revealed a clear covariation between predicted vocal fold length and voice classification. Anterior-posterior subglottic-tracheal diameter yielded mean vocal fold lengths of 14.9, 16.0, 16.6, 18.4, 19.5, and 20.9mm for sopranos, mezzo-sopranos, altos, tenors, baritones, and basses, respectively. The data support the assumption that there are consistent anatomical laryngeal differences between singers of different voice classifications, which are of relevance to pitch range and timbre of the voice.

Classification of radiolarian images with hand-crafted and deep features

NASA Astrophysics Data System (ADS)

Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

2017-12-01

Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

Ultrasonographic characteristics and BI-RADS-US classification of BRCA1 mutation-associated breast cancer in Guangxi, China.

PubMed

Li, Cheng; Liu, Junjie; Wang, Sida; Chen, Yuanyuan; Yuan, Zhigang; Zeng, Jian; Li, Zhixian

2015-01-01

To retrospectively analyze and compare the ultrasonographic characteristics and BI-RADS-US classification between patients with BRCA1 mutation-associated breast cancer and those without BRCA1 gene mutation in Guangxi, China. The study was performed in 36 lesions from 34 BRCA1 mutation-associated breast cancer patients. A total of 422 lesions from 422 breast cancer patients without BRCA1 mutations served as control group. The comparison of the ultrasonographic features and BI-RADS-US classification between two the groups were reviewed. More complex inner echo was disclosed in BRCA1 mutation-associated breast cancer patients (x(2) = 4.741, P = 0.029). The BI-RADS classification of BRCA1 mutation-associated breast cancer was lower (U = 6094.0, P = 0.022). BRCA1 mutation-associated breast cancer frequently displays as microlobulated margin and complex echo. It also shows more benign characteristics in morphology, and the BI-RADS classification is prone to be underestimated.

Toward extending terrestrial laser scanning applications in forestry: a case study of broad- and needle-leaf tree classification

NASA Astrophysics Data System (ADS)

Lin, Yi; Jiang, Miao

2017-01-01

Tree species information is essential for forest research and management purposes, which in turn require approaches for accurate and precise classification of tree species. One such remote sensing technology, terrestrial laser scanning (TLS), has proved to be capable of characterizing detailed tree structures, such as tree stem geometry. Can TLS further differentiate between broad- and needle-leaves? If the answer is positive, TLS data can be used for classification of taxonomic tree groups by directly examining their differences in leaf morphology. An analysis was proposed to assess TLS-represented broad- and needle-leaf structures, followed by a Bayes classifier to perform the classification. Tests indicated that the proposed method can basically implement the task, with an overall accuracy of 77.78%. This study indicates a way of implementing the classification of the two major broad- and needle-leaf taxonomies measured by TLS in accordance to their literal definitions, and manifests the potential of extending TLS applications in forestry.

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

Ongoing data reduction, theoretical studies and supporting research in magnetospheric physics

NASA Technical Reports Server (NTRS)

Scarf, F. L.; Greenstadt, E. W.

1984-01-01

Data from ISEE-3, Pioneer Venus Orbiter, and Voyager 1 and 2 were analyzed. The predictability of local shock macrostructure at ISEE-1, at the Earth's bow shock, from solar wind measurements made up-stream by ISEE-3, was conducted using computer graphic format. Morphology of quasi-parallel shock was reviewed. The review attempted to interrelate various measurements and computations involving the q-parallel structure and foreshock elements connected to it. A new classification for q-parallel morphology was suggested.

Aquatic Plant Control Research Program: Effects of Salinity and Irradiance Conditions on the Growth, Morphology and Chemical Composition of Submersed Aquatic Macrophytes

DTIC Science & Technology

1990-07-01

L , AQUATIC PLANT CONTROL RESEARCH PROGRAM * * TECHNICAL REPORT A-90-5 EFFECTS OF SALINITY AND IRRADIANCE CONDITIONS ON THE GROWTH, MORPHOLOGY AND...UNIT ELEMENT NO. NO. NO. ACCESSION NO. 11. TITLE (Indude Security Classification) Effects of Salinity and Irradiance Conditions on the Growth...Dr. Robert W. Whalin. This report should be cited as follows: Twilley, Robert R., and Barko, John W. 1990. " Effects of Salinity and Irradiance

SHAPING POINT- AND MIRROR-SYMMETRIC PROTOPLANETARY NEBULAE BY THE ORBITAL MOTION OF THE CENTRAL BINARY SYSTEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haro-Corzo, Sinhue A. R.; Velazquez, Pablo F.; Raga, Alejandro C.

We present three-dimensional hydrodynamical simulations of a jet launched from the secondary star of a binary system inside a protoplanetary nebula. The secondary star moves around the primary in a close eccentric orbit. From the gasdynamic simulations we compute synthetic [N II] lambda 6583 emission maps. Different jet axis inclinations with respect to the orbital plane, as well as different orientations of the flow with respect to the observer, are considered. For some parameter combinations, we obtain structures that show point- or mirror-symmetric morphologies depending on the orientation of the flow with respect to the observer. Furthermore, our models canmore » explain some of the emission distribution asymmetries that are summarized in the classification given by Soker and Hadar.« less

The Development of Combined Raman Spectroscopy-Optical Coherence Tomography and Application for Skin Cancer Diagnosis

NASA Astrophysics Data System (ADS)

Patil, Chetan

2009-11-01

Optical spectroscopy and imaging have shown promise for performing rapid, non-invasive disease detection and diagnosis in vivo. Independently, Raman Spectroscopy (RS) has demonstrated the ability to perform diagnosis of epithelial cancers such the cervix with excellent overall classification accuracy due to the inherent biochemical specificity of the technique, however relating features of tissue morphology with techniques such as Raman mapping is clinically impractical due to the weak nature of the scattering phenomena resulting in prohibitively long acquisition times. Optical Coherence Tomography (OCT), on the other hand, has demonstrated the ability to perform real-time, high-resolution, cross-sectional imaging of the microstructural characteristics of disease, but typically lacks molecularly specific information that can assist in classifying pathological lesions. We present the development of a combined Raman Spectroscopy-OCT (RS-OCT) instrument capable of compensating for the limitations of each technique individually and performing both biochemical and microstructural evaluation of tissues. We will include the design and development of benchtop RS-OCT implementations based on independent 785 nm Raman and 1310 nm time-domain OCT system backbones, as well as with a 785nm Raman / 850nm spectral-domain OCT setup employing an integrated detection arm. These systems motivated the ultimate design of a clinical RS-OCT system for application in dermatology. In order to aid in the development of our Raman spectral processing and classification methods, we conducted a simultaneous pilot study in which RS alone was used to measure basal and squamous cell carcinomas. We will present the initial results from our clinical experiences with the combined RS-OCT device, and include a discussion of spectral classification and the ultimate potential of combined RS-OCT for skin cancer diagnosis.

The 2016 revision of the WHO Classification of Central Nervous System Tumours: retrospective application to a cohort of diffuse gliomas.

PubMed

Rogers, Te Whiti; Toor, Gurvinder; Drummond, Katharine; Love, Craig; Field, Kathryn; Asher, Rebecca; Tsui, Alpha; Buckland, Michael; Gonzales, Michael

2018-03-01

The classification of central nervous system tumours has more recently been shaped by a focus on molecular pathology rather than histopathology. We re-classified 82 glial tumours according to the molecular-genetic criteria of the 2016 revision of the World Health Organization (WHO) Classification of Tumours of the Central Nervous System. Initial diagnoses and grading were based on the morphological criteria of the 2007 WHO scheme. Because of the impression of an oligodendroglial component on initial histological assessment, each tumour was tested for co-deletion of chromosomes 1p and 19q and mutations of isocitrate dehydrogenase (IDH-1 and 2) genes. Additionally, expression of proteins encoded by alpha-thalassemia X-linked mental retardation (ATRX) and TP53 genes was assessed by immunohistochemistry. We found that all but two tumours could be assigned to a specific category in the 2016 revision. The most common change in diagnosis was from oligoastrocytoma to specifically astrocytoma or oligodendroglioma. Analysis of progression free survival (PFS) for WHO grade II and III tumours showed that the objective criteria of the 2016 revision separated diffuse gliomas into three distinct molecular categories: chromosome 1p/19q co-deleted/IDH mutant, intact 1p/19q/IDH mutant and IDH wild type. No significant difference in PFS was found when comparing IDH mutant grade II and III tumours suggesting that IDH status is more informative than tumour grade. The segregation into distinct molecular sub-types that is achieved by the 2016 revision provides an objective evidence base for managing patients with grade II and III diffuse gliomas based on prognosis.

Digital microbiology: detection and classification of unknown bacterial pathogens using a label-free laser light scatter-sensing system

NASA Astrophysics Data System (ADS)

Rajwa, Bartek; Dundar, M. Murat; Akova, Ferit; Patsekin, Valery; Bae, Euiwon; Tang, Yanjie; Dietz, J. Eric; Hirleman, E. Daniel; Robinson, J. Paul; Bhunia, Arun K.

2011-06-01

The majority of tools for pathogen sensing and recognition are based on physiological or genetic properties of microorganisms. However, there is enormous interest in devising label-free and reagentless biosensors that would operate utilizing the biophysical signatures of samples without the need for labeling and reporting biochemistry. Optical biosensors are closest to realizing this goal and vibrational spectroscopies are examples of well-established optical label-free biosensing techniques. A recently introduced forward-scatter phenotyping (FSP) also belongs to the broad class of optical sensors. However, in contrast to spectroscopies, the remarkable specificity of FSP derives from the morphological information that bacterial material encodes on a coherent optical wavefront passing through the colony. The system collects elastically scattered light patterns that, given a constant environment, are unique to each bacterial species and/or serovar. Both FSP technology and spectroscopies rely on statistical machine learning to perform recognition and classification. However, the commonly used methods utilize either simplistic unsupervised learning or traditional supervised techniques that assume completeness of training libraries. This restrictive assumption is known to be false for real-life conditions, resulting in unsatisfactory levels of accuracy, and consequently limited overall performance for biodetection and classification tasks. The presented work demonstrates preliminary studies on the use of FSP system to classify selected serotypes of non-O157 Shiga toxin-producing E. coli in a nonexhaustive framework, that is, without full knowledge about all the possible classes that can be encountered. Our study uses a Bayesian approach to learning with a nonexhaustive training dataset to allow for the automated and distributed detection of unknown bacterial classes.

Quantitative cervical vertebral maturation assessment in adolescents with normal occlusion: a mixed longitudinal study.

PubMed

Chen, Li-Li; Xu, Tian-Min; Jiang, Jiu-Hui; Zhang, Xing-Zhong; Lin, Jiu-Xiang

2008-12-01

The purpose of this study was to establish a quantitative cervical vertebral maturation (CVM) system for adolescents with normal occlusion. Mixed longitudinal data were used. The subjects included 87 children and adolescents from 8 to 18 years old with normal occlusion (32 boys, 55 girls) selected from 901 candidates. Sequential lateral cephalograms and hand-wrist films were taken once a year for 6 years. The lateral cephalograms of all subjects were divided into 11 maturation groups according to the Fishman skeletal maturity indicators. The morphologic characteristics of the second, third, and fourth cervical vertebrae at 11 developmental stages were measured and analyzed. Three characteristic parameters (H4/W4, AH3/PH3, @2) were selected to determine the classification of CVM. With 3 morphologic variables, the quantitative CVM system including 4 maturational stages was established. An equation that can accurately estimate the maturation of the cervical vertebrae was established: CVM stage=-4.13+3.57xH4/W4+4.07xAH3/PH3+0.03x@2. The quantitative CVM method is an efficient, objective, and relatively simple approach to assess the level of skeletal maturation during adolescence.

Hitting rock bottom: morphological responses of bedrock-confined streams to a catastrophic flood

NASA Astrophysics Data System (ADS)

Baggs Sargood, M.; Cohen, T. J.; Thompson, C. J.; Croke, J.

2015-06-01

The role of extreme events in shaping the Earth's surface is one that has held the interests of Earth scientists for centuries. A catastrophic flood in a tectonically quiescent setting in eastern Australia in 2011 provides valuable insight into how semi-alluvial channels respond to such events. Field survey data (3 reaches) and desktop analyses (10 reaches) with catchment areas ranging from 0.5 to 168 km2 show that the predicted discharge for the 2011 event ranged from 415 to 933 m3 s-1, with unit stream power estimates of up to 1077 W m-2. Estimated entrainment relationships predict the mobility of the entire grain-size population, and field data suggest the localised mobility of boulders up to 4.8 m in diameter. Analysis of repeat lidar data demonstrates that all reaches (field and desktop) were areas of net degradation via extensive scouring of coarse-grained alluvium with a strong positive relationship between catchment area and normalised erosion (R2 = 0.72-0.74). The extensive scouring in the 2011 flood decreased thalweg variance significantly removing previous step pools and other coarse-grained in-channel units, forming lengths of plane-bed (cobble) reach morphology. This was also accompanied by the exposure of planar bedrock surfaces, marginal bedrock straths and bedrock steps. Post-flood field data indicate a slight increase in thalweg variance as a result of the smaller 2013 flood rebuilding the alluvial overprint with pool-riffle formation. However, the current form and distribution of channel morphological units does not conform to previous classifications of bedrock or headwater river systems. This variation in post-flood form indicates that in semi-alluvial systems extreme events are significant for re-setting the morphology of in-channel units and for exposing the underlying lithology to ongoing erosion.

B-cell posttransplant lymphoproliferative disorder isolated to the central nervous system is Epstein-Barr virus positive and lacks p53 and Myc expression by immunohistochemistry.

PubMed

Sundin, Andrew; Grzywacz, Bartosz J; Yohe, Sophia; Linden, Michael A; Courville, Elizabeth L

2017-03-01

In this retrospective study from one institution, we performed a clinicopathological study of a cohort of patients with posttransplant lymphoproliferative disorder (PTLD) confined to the central nervous system. We also identified a comparison cohort of patients with de novo primary diffuse large B-cell lymphoma of the central nervous system. We performed a detailed morphologic review, evaluated Epstein-Barr virus (EBV) by in situ hybridization, and interpreted a panel of immunohistochemical stains in a subset of cases including Hans classification markers (CD10, BCL6, MUM1), p53, CD30, Myc, and BCL2. All 17 of the posttransplant and none of 11 de novo cases were EBV positive (P < .005). Morphologic patterns identified in the PTLD cases were monomorphic diffuse large B-cell lymphoma pattern (10 patients) and "T-cell-rich" pattern (7 patients). The monomorphic posttransplant cases were more likely to be Myc negative (P = .015) and CD30 positive (P < .005) than the de novo cases, and showed a similarly low rate of p53 positivity by immunohistochemistry. No prognostic factors for overall survival were identified. Central nervous system PTLD is EBV positive, typically lacks p53 and Myc expression by immunohistochemistry, and can present with numerous background T lymphocytes. Copyright © 2016 Elsevier Inc. All rights reserved.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Disease scoring systems for oral lichen planus; a critical appraisal

PubMed Central

Wang, Jing

2015-01-01

The aim of the present study has been to critically review 22 disease scoring systems (DSSs) on oral lichen planus (OLP) that have been reported in the literature during the past decades. Although the presently available DSSs may all have some merit, particularly for research purposes, the diversity of both the objective and subjective parameters used in these systems and the lack of acceptance of one of these systems for uniform use, there is a need for an international, authorized consensus meeting on this subject. Because of the natural course of OLP characterized by remissions and exacerbations and also due to the varying distribution pattern and the varying clinical types, e.g. reticular and erosive, the relevance of a DSS based on morphologic parameters is somewhat questionable. Instead, one may consider to only look for a quality of life scoring system adapted for use in OLP patients. Key words:Oral lichen planus, disease scoring system, classification. PMID:25681372

Combining High Spatial Resolution Optical and LIDAR Data for Object-Based Image Classification

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, T.; Geng, R.; Wang, L.

2018-04-01

In order to classify high spatial resolution images more accurately, in this research, a hierarchical rule-based object-based classification framework was developed based on a high-resolution image with airborne Light Detection and Ranging (LiDAR) data. The eCognition software is employed to conduct the whole process. In detail, firstly, the FBSP optimizer (Fuzzy-based Segmentation Parameter) is used to obtain the optimal scale parameters for different land cover types. Then, using the segmented regions as basic units, the classification rules for various land cover types are established according to the spectral, morphological and texture features extracted from the optical images, and the height feature from LiDAR respectively. Thirdly, the object classification results are evaluated by using the confusion matrix, overall accuracy and Kappa coefficients. As a result, a method using the combination of an aerial image and the airborne Lidar data shows higher accuracy.

New low-resolution spectrometer spectra for IRAS sources

NASA Astrophysics Data System (ADS)

Volk, Kevin; Kwok, Sun; Stencel, R. E.; Brugel, E.

1991-12-01

Low-resolution spectra of 486 IRAS point sources with Fnu(12 microns) in the range 20-40 Jy are presented. This is part of an effort to extract and classify spectra that were not included in the Atlas of Low-Resolution Spectra and represents an extension of the earlier work by Volk and Cohen which covers sources with Fnu(12 microns) greater than 40 Jy. The spectra have been examined by eye and classified into nine groups based on the spectral morphology. This new classification scheme is compared with the mechanical classification of the Atlas, and the differences are noted. Oxygen-rich stars of the asymptotic giant branch make up 33 percent of the sample. Solid state features dominate the spectra of most sources. It is found that the nature of the sources as implied by the present spectral classification is consistent with the classifications based on broad-band colors of the sources.

Automatic detection of ECG cable interchange by analyzing both morphology and interlead relations.

PubMed

Han, Chengzong; Gregg, Richard E; Feild, Dirk Q; Babaeizadeh, Saeed

2014-01-01

ECG cable interchange can generate erroneous diagnoses. For algorithms detecting ECG cable interchange, high specificity is required to maintain a low total false positive rate because the prevalence of interchange is low. In this study, we propose and evaluate an improved algorithm for automatic detection and classification of ECG cable interchange. The algorithm was developed by using both ECG morphology information and redundancy information. ECG morphology features included QRS-T and P-wave amplitude, frontal axis and clockwise vector loop rotation. The redundancy features were derived based on the EASI™ lead system transformation. The classification was implemented using linear support vector machine. The development database came from multiple sources including both normal subjects and cardiac patients. An independent database was used to test the algorithm performance. Common cable interchanges were simulated by swapping either limb cables or precordial cables. For the whole validation database, the overall sensitivity and specificity for detecting precordial cable interchange were 56.5% and 99.9%, and the sensitivity and specificity for detecting limb cable interchange (excluding left arm-left leg interchange) were 93.8% and 99.9%. Defining precordial cable interchange or limb cable interchange as a single positive event, the total false positive rate was 0.7%. When the algorithm was designed for higher sensitivity, the sensitivity for detecting precordial cable interchange increased to 74.6% and the total false positive rate increased to 2.7%, while the sensitivity for detecting limb cable interchange was maintained at 93.8%. The low total false positive rate was maintained at 0.6% for the more abnormal subset of the validation database including only hypertrophy and infarction patients. The proposed algorithm can detect and classify ECG cable interchanges with high specificity and low total false positive rate, at the cost of decreased sensitivity for certain precordial cable interchanges. The algorithm could also be configured for higher sensitivity for different applications where a lower specificity can be tolerated. Copyright © 2014 Elsevier Inc. All rights reserved.

Molecular phylogeny and systematics of the Echinostomatoidea Looss, 1899 (Platyhelminthes: Digenea).

PubMed

Tkach, Vasyl V; Kudlai, Olena; Kostadinova, Aneta

2016-03-01

The Echinostomatoidea is a large, cosmopolitan group of digeneans currently including nine families and 105 genera, the vast majority parasitic, as adults, in birds with relatively few taxa parasitising mammals, reptiles and, exceptionally, fish. Despite the complex structure, diverse content and substantial species richness of the group, almost no attempt has been made to elucidate its phylogenetic relationships at the suprageneric level based on molecules due to the lack of data. Herein, we evaluate the consistency of the present morphology-based classification system of the Echinostomatoidea with the phylogenetic relationships of its members based on partial sequences of the nuclear lsrRNA gene for a broad diversity of taxa (80 species, representing eight families and 40 genera), including representatives of five subfamilies of the Echinostomatidae, which currently exhibits the most complex taxonomic structure within the superfamily. This first comprehensive phylogeny for the Echinostomatoidea challenged the current systematic framework based on comparative morphology. A morphology-based evaluation of this new molecular framework resulted in a number of systematic and nomenclatural changes consistent with the phylogenetic estimates of the generic and suprageneric boundaries and a new phylogeny-based classification of the Echinostomatoidea. In the current systematic treatment: (i) the rank of two family level lineages, the former Himasthlinae and Echinochasminae, is elevated to full family status; (ii) Caballerotrema is distinguished at the family level; (iii) the content and diagnosis of the Echinostomatidae (sensu stricto) (s. str.) are revised to reflect its phylogeny, resulting in the abolition of the Nephrostominae and Chaunocephalinae as synonyms of the Echinostomatidae (s. str.); (iv) Artyfechinostomum, Cathaemasia, Rhopalias and Ribeiroia are re-allocated within the Echinostomatidae (s. str.), resulting in the abolition of the Cathaemasiidae, Rhopaliidae and Ribeiroiinae, which become synonyms of the Echinostomatidae (s. str.); and (v) refinements of the generic boundaries within the Echinostomatidae (s. str.), Psilostomidae and Fasciolidae are made. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Phylogeny and systematic position of Opiliones: a combined analysis of chelicerate relationships using morphological and molecular data

NASA Technical Reports Server (NTRS)

Giribet, Gonzalo; Edgecombe, Gregory D.; Wheeler, Ward C.; Babbitt, Courtney

2002-01-01

The ordinal level phylogeny of the Arachnida and the suprafamilial level phylogeny of the Opiliones were studied on the basis of a combined analysis of 253 morphological characters, the complete sequence of the 18S rRNA gene, and the D3 region of the 28S rRNA gene. Molecular data were collected for 63 terminal taxa. Morphological data were collected for 35 exemplar taxa of Opiliones, but groundplans were applied to some of the remaining chelicerate groups. Six extinct terminals, including Paleozoic scorpions, are scored for morphological characters. The data were analyzed using strict parsimony for the morphological data matrix and via direct optimization for the molecular and combined data matrices. A sensitivity analysis of 15 parameter sets was undertaken, and character congruence was used as the optimality criterion to choose among competing hypotheses. The results obtained are unstable for the high-level chelicerate relationships (except for Tetrapulmonata, Pedipalpi, and Camarostomata), and the sister group of the Opiliones is not clearly established, although the monophyly of Dromopoda is supported under many parameter sets. However, the internal phylogeny of the Opiliones is robust to parameter choice and allows the discarding of previous hypotheses of opilionid phylogeny such as the "Cyphopalpatores" or "Palpatores." The topology obtained is congruent with the previous hypothesis of "Palpatores" paraphyly as follows: (Cyphophthalmi (Eupnoi (Dyspnoi + Laniatores))). Resolution within the Eupnoi, Dyspnoi, and Laniatores (the latter two united as Dyspnolaniatores nov.) is also stable to the superfamily level, permitting a new classification system for the Opiliones. c2002 The Willi Hennig Society.

Fine root morphological traits determine variation in root respiration of Quercus serrata.

PubMed

Makita, Naoki; Hirano, Yasuhiro; Dannoura, Masako; Kominami, Yuji; Mizoguchi, Takeo; Ishii, Hiroaki; Kanazawa, Yoichi

2009-04-01

Fine root respiration is a significant component of carbon cycling in forest ecosystems. Although fine roots differ functionally from coarse roots, these root types have been distinguished based on arbitrary diameter cut-offs (e.g., 2 or 5 mm). Fine root morphology is directly related to physiological function, but few attempts have been made to understand the relationships between morphology and respiration of fine roots. To examine relationships between respiration rates and morphological traits of fine roots (0.15-1.4 mm in diameter) of mature Quercus serrata Murr., we measured respiration of small fine root segments in the field with a portable closed static chamber system. We found a significant power relationship between mean root diameter and respiration rate. Respiration rates of roots<0.4 mm in mean diameter were high and variable, ranging from 3.8 to 11.3 nmol CO2 g(-1) s(-1), compared with those of larger diameter roots (0.4-1.4 mm), which ranged from 1.8 to 3.0 nmol CO2 g(-1) s(-1). Fine root respiration rate was positively correlated with specific root length (SRL) as well as with root nitrogen (N) concentration. For roots<0.4 mm in diameter, SRL had a wider range (11.3-80.4 m g(-1)) and was more strongly correlated with respiration rate than diameter. Our results indicate that a more detailed classification of fine roots<2.0 mm is needed to represent the heterogeneity of root respiration and to evaluate root biomass and root morphological traits.

Noninvasive imaging techniques in the assessment of scleroderma spectrum disorders.

PubMed

Murray, Andrea K; Moore, Tonia L; Manning, Joanne B; Taylor, Christopher; Griffiths, Christopher E M; Herrick, Ariane L

2009-08-15

Systemic sclerosis (SSc) affects both microvascular structure and function. Laser Doppler imaging (LDI) and thermal imaging can be used to measure cutaneous blood vessel function. Nailfold capillaroscopy (NC) measures capillary morphology. The aim of this study was to investigate the relationship between capillary morphology and blood flow, and to determine which combination of techniques allows the best discrimination between patients with SSc, primary Raynaud's phenomenon (RP), and healthy controls. NC was performed in 16 patients with SSc, 14 patients with primary RP, and 16 healthy controls. In addition, participants underwent cold stimulus with cold water. Hands were imaged to monitor rewarming and reperfusion. Nailfold morphologic features were measured and baseline images and rewarming curves were analyzed. Significant differences were found between groups (analysis of variance) for capillary morphologic features and rewarming curve characteristics. A correlation (P < 0.001) was found between LDI and thermal imaging at baseline (0.667) and maximum (0.729) blood flow and skin temperature, and for the areas under the rewarming curves (0.684). Receiver operating characteristic curves indicated that NC, thermal imaging, and LDI allowed 89%, 74%, and 72%, respectively, of SSc patient data to be correctly classified versus primary RP patients and controls. NC, LDI, and thermal imaging each independently provide good discrimination between patients with SSc and those with primary RP and healthy controls (NC being the most suitable technique for classifying patient groups). However, a combination of all 3 techniques improves classification. LDI and thermal imaging give equivalent information on dynamic changes in the cutaneous microcirculation; however, these only weakly correspond to capillary morphology.

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

National Plant Diagnostic Network, Taxonomic training videos: Introduction to Aphids - Part 1

USDA-ARS?s Scientific Manuscript database

Training is a critical part of aphid (Hemiptera: Aphididae) identification. This video provides visual instruction on important subject areas for aphid examination and identification. Aphid topics such as classification, morphology, plant disease transmission, and references are discussed. This dis...

Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize detection errors. Given the great expense and effort associated with morphological identification of many...

Morphological and wavelet features towards sonographic thyroid nodules evaluation.

PubMed

Tsantis, Stavros; Dimitropoulos, Nikos; Cavouras, Dionisis; Nikiforidis, George

2009-03-01

This paper presents a computer-based classification scheme that utilized various morphological and novel wavelet-based features towards malignancy risk evaluation of thyroid nodules in ultrasonography. The study comprised 85 ultrasound images-patients that were cytological confirmed (54 low-risk and 31 high-risk). A set of 20 features (12 based on nodules boundary shape and 8 based on wavelet local maxima located within each nodule) has been generated. Two powerful pattern recognition algorithms (support vector machines and probabilistic neural networks) have been designed and developed in order to quantify the power of differentiation of the introduced features. A comparative study has also been held, in order to estimate the impact speckle had onto the classification procedure. The diagnostic sensitivity and specificity of both classifiers was made by means of receiver operating characteristics (ROC) analysis. In the speckle-free feature set, the area under the ROC curve was 0.96 for the support vector machines classifier whereas for the probabilistic neural networks was 0.91. In the feature set with speckle, the corresponding areas under the ROC curves were 0.88 and 0.86 respectively for the two classifiers. The proposed features can increase the classification accuracy and decrease the rate of missing and misdiagnosis in thyroid cancer control.

Cranial morphological homogeneity in two subspecies of water deer in China and Korea.

PubMed

Kim, Yung Kun; Koyabu, Daisuke; Lee, Hang; Kimura, Junpei

2015-11-01

The water deer (Hydropotes inermis) has conventionally been classified into two subspecies according to geographic distribution and pelage color pattern: H. i. inermis from China and H. i. argyropus from Korea. However, the results of a recent molecular study have called this into question. To further reappraise this classification, we examined morphological variation in craniodental measurements of these 2 subspecies. Results of univariate and multivariate analyses demonstrated that these 2 subspecies are not well-differentiated, suggesting that individuals of the 2 populations share common morphological traits. Despite the distribution of the subspecies at different latitudes, no clear morphocline was detected, suggesting that Bergmann's rule does not apply in this case. Discriminant analysis indicated that the characteristics of individuals are shared by both populations, suggesting that not all individuals can be assigned to their original population. Results of principal component analysis showed that the two populations shared more than 75% of individuals, congruent with the "75% rule" of subspecies classification. In both the neighbor-joining and unweighted pair group methods with arithmetic mean cluster analyses, specimens of H. i. argyropus and H. i. inermis were highly mixed within the cladograms. These results suggest that the overall morphological variation in the 2 subspecies overlaps considerably and that there is no coherent craniofacial difference between the 2 groups. The present findings combined with prior observations from molecular biogeography point out that the taxonomic division of water deer into 2 subspecies should be revisited.

Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

DISTRIBUTION, MORPHOLOGY, AND PHYLOGENY OF KLEBSORMIDIUM (KLEBSORMIDIALES, CHAROPHYCEAE) IN URBAN ENVIRONMENTS IN EUROPE(1).

PubMed

Rindi, Fabio; Guiry, Michael D; López-Bautista, Juan M

2008-12-01

Klebsormidium is a cosmopolitan genus of green algae, widespread in terrestrial and freshwater habitats. The classification of Klebsormidium is entirely based on morphological characters, and very little is understood about its phylogeny at the species level. We investigated the diversity and phylogenetic relationships of Klebsormidium in urban habitats in Europe by a combination of approaches including examination of field-collected material, culture experiments conducted in many different combinations of factors, and phylogenetic analyses of the rbcL gene. Klebsormidium in European cities mainly occurs at the base of old walls, where it may produce green belts up to several meters in extent. Specimens from different cities showed a great morphological uniformity, consisting of long filaments 6-9 μm in width, with thin-walled cylindrical cells and smooth wall, devoid of false branches, H-shaped pieces, and biseriate parts. Conversely, the rbcL phylogeny showed a higher genetic diversity than expected from morphology. The strains were separated in four different clades supported by high bootstrap values and posterior probabilities. In culture, these clades differed in several characters, such as production of a superficial hydro-repellent layer, tendency to break into short fragments, and inducibility of zoosporulation. On the basis of the taxonomic information available in the literature, most strains could not be identified unambiguously at the species level. The rbcL phylogeny showed no correspondence with classification based on morphology and suggested that the identity of many species, in particular the type species K. flaccidum (kütz.) P.C. Silva, Mattox et W. H. Blackw., needs critical reassessment. © 2008 Phycological Society of America.

Classification of Human Retinal Microaneurysms Using Adaptive Optics Scanning Light Ophthalmoscope Fluorescein Angiography

PubMed Central

Dubow, Michael; Pinhas, Alexander; Shah, Nishit; Cooper, Robert F.; Gan, Alexander; Gentile, Ronald C.; Hendrix, Vernon; Sulai, Yusufu N.; Carroll, Joseph; Chui, Toco Y. P.; Walsh, Joseph B.; Weitz, Rishard; Dubra, Alfredo; Rosen, Richard B.

2014-01-01

Purpose. Microaneurysms (MAs) are considered a hallmark of retinal vascular disease, yet what little is known about them is mostly based upon histology, not clinical observation. Here, we use the recently developed adaptive optics scanning light ophthalmoscope (AOSLO) fluorescein angiography (FA) to image human MAs in vivo and to expand on previously described MA morphologic classification schemes. Methods. Patients with vascular retinopathies (diabetic, hypertensive, and branch and central retinal vein occlusion) were imaged with reflectance AOSLO and AOSLO FA. Ninety-three MAs, from 14 eyes, were imaged and classified according to appearance into six morphologic groups: focal bulge, saccular, fusiform, mixed, pedunculated, and irregular. The MA perimeter, area, and feret maximum and minimum were correlated to morphology and retinal pathology. Select MAs were imaged longitudinally in two eyes. Results. Adaptive optics scanning light ophthalmoscope fluorescein angiography imaging revealed microscopic features of MAs not appreciated on conventional images. Saccular MAs were most prevalent (47%). No association was found between the type of retinal pathology and MA morphology (P = 0.44). Pedunculated and irregular MAs were among the largest MAs with average areas of 4188 and 4116 μm2, respectively. Focal hypofluorescent regions were noted in 30% of MAs and were more likely to be associated with larger MAs (3086 vs. 1448 μm2, P = 0.0001). Conclusions. Retinal MAs can be classified in vivo into six different morphologic types, according to the geometry of their two-dimensional (2D) en face view. Adaptive optics scanning light ophthalmoscope fluorescein angiography imaging of MAs offers the possibility of studying microvascular change on a histologic scale, which may help our understanding of disease progression and treatment response. PMID:24425852

Computer analysis of digital sky surveys using citizen science and manual classification

NASA Astrophysics Data System (ADS)

Kuminski, Evan; Shamir, Lior

2015-01-01

As current and future digital sky surveys such as SDSS, LSST, DES, Pan-STARRS and Gaia create increasingly massive databases containing millions of galaxies, there is a growing need to be able to efficiently analyze these data. An effective way to do this is through manual analysis, however, this may be insufficient considering the extremely vast pipelines of astronomical images generated by the present and future surveys. Some efforts have been made to use citizen science to classify galaxies by their morphology on a larger scale than individual or small groups of scientists can. While these citizen science efforts such as Zooniverse have helped obtain reasonably accurate morphological information about large numbers of galaxies, they cannot scale to provide complete analysis of billions of galaxy images that will be collected by future ventures such as LSST. Since current forms of manual classification cannot scale to the masses of data collected by digital sky surveys, it is clear that in order to keep up with the growing databases some form of automation of the data analysis will be required, and will work either independently or in combination with human analysis such as citizen science. Here we describe a computer vision method that can automatically analyze galaxy images and deduce galaxy morphology. Experiments using Galaxy Zoo 2 data show that the performance of the method increases as the degree of agreement between the citizen scientists gets higher, providing a cleaner dataset. For several morphological features, such as the spirality of the galaxy, the algorithm agreed with the citizen scientists on around 95% of the samples. However, the method failed to analyze some of the morphological features such as the number of spiral arms, and provided accuracy of just ~36%.

[Diagnosis, prognosis, and prediction of non-small cell lung cancer. Importance of morphology, immunohistochemistry and molecular pathology].

PubMed

Warth, A

2015-11-01

Tumor diagnostics are based on histomorphology, immunohistochemistry and molecular pathological analysis of mutations, translocations and amplifications which are of diagnostic, prognostic and/or predictive value. In recent decades only histomorphology was used to classify lung cancer as either small (SCLC) or non-small cell lung cancer (NSCLC), although NSCLC was further subdivided in different entities; however, as no specific therapy options were available classification of specific subtypes was not clinically meaningful. This fundamentally changed with the discovery of specific molecular alterations in adenocarcinoma (ADC), e.g. mutations in KRAS, EGFR and BRAF or translocations of the ALK and ROS1 gene loci, which now form the basis of targeted therapies and have led to a significantly improved patient outcome. The diagnostic, prognostic and predictive value of imaging, morphological, immunohistochemical and molecular characteristics as well as their interaction were systematically assessed in a large cohort with available clinical data including patient survival. Specific and sensitive diagnostic markers and marker panels were defined and diagnostic test algorithms for predictive biomarker assessment were optimized. It was demonstrated that the semi-quantitative assessment of ADC growth patterns is a stage-independent predictor of survival and is reproducibly applicable in the routine setting. Specific histomorphological characteristics correlated with computed tomography (CT) imaging features and thus allowed an improved interdisciplinary classification, especially in the preoperative or palliative setting. Moreover, specific molecular characteristics, for example BRAF mutations and the proliferation index (Ki-67) were identified as clinically relevant prognosticators. Comprehensive clinical, morphological, immunohistochemical and molecular assessment of NSCLCs allow an optimized patient stratification. Respective algorithms now form the backbone of the 2015 lung cancer World Health Organization (WHO) classification.

MiT family translocation renal cell carcinoma.

PubMed

Argani, Pedram

2015-03-01

The MiT subfamily of transcription factors includes TFE3, TFEB, TFC, and MiTF. Gene fusions involving two of these transcription factors have been identified in renal cell carcinoma (RCC). The Xp11 translocation RCCs were first officially recognized in the 2004 WHO renal tumor classification, and harbor gene fusions involving TFE3. The t(6;11) RCCs harbor a specific Alpha-TFEB gene fusion and were first officially recognized in the 2013 International Society of Urologic Pathology (ISUP) Vancouver classification of renal neoplasia. These two subtypes of translocation RCC have many similarities. Both were initially described in and disproportionately involve young patients, though adult translocation RCC may overall outnumber pediatric cases. Both often have unusual and distinctive morphologies; the Xp11 translocation RCCs frequently have clear cells with papillary architecture and abundant psammomatous bodies, while the t(6;11) RCCs frequently have a biphasic appearance with both large and small epithelioid cells and nodules of basement membrane material. However, the morphology of these two neoplasms can overlap, with one mimicking the other. Both of these RCCs underexpress epithelial immunohistochemical markers like cytokeratin and epithelial membrane antigen (EMA) relative to most other RCCs. Unlike other RCCs, both frequently express the cysteine protease cathepsin k and often express melanocytic markers like HMB45 and Melan A. Finally, TFE3 and TFEB have overlapping functional activity as these two transcription factors frequently heterodimerize and bind to the same targets. Therefore, on the basis of clinical, morphologic, immunohistochemical, and genetic similarities, the 2013 ISUP Vancouver classification of renal neoplasia grouped these two neoplasms together under the heading of "MiT family translocation RCC." This review summarizes our current knowledge of these recently described RCCs. Copyright © 2015 Elsevier Inc. All rights reserved.

Deep learning based classification of morphological patterns in RCM to guide noninvasive diagnosis of melanocytic lesions (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kose, Kivanc; Bozkurt, Alican; Ariafar, Setareh; Alessi-Fox, Christi A.; Gill, Melissa; Dy, Jennifer G.; Brooks, Dana H.; Rajadhyaksha, Milind

2017-02-01

In this study we present a deep learning based classification algorithm for discriminating morphological patterns that appear in RCM mosaics of melanocytic lesions collected at the dermal epidermal junction (DEJ). These patterns are classified into 6 distinct types in the literature: background, meshwork, ring, clod, mixed, and aspecific. Clinicians typically identify these morphological patterns by examination of their textural appearance at 10X magnification. To mimic this process we divided mosaics into smaller regions, which we call tiles, and classify each tile in a deep learning framework. We used previously acquired DEJ mosaics of lesions deemed clinically suspicious, from 20 different patients, which were then labelled according to those 6 types by 2 expert users. We tried three different approaches for classification, all starting with a publicly available convolutional neural network (CNN) trained on natural image, consisting of a series of convolutional layers followed by a series of fully connected layers: (1) We fine-tuned this network using training data from the dataset. (2) Instead, we added an additional fully connected layer before the output layer network and then re-trained only last two layers, (3) We used only the CNN convolutional layers as a feature extractor, encoded the features using a bag of words model, and trained a support vector machine (SVM) classifier. Sensitivity and specificity were generally comparable across the three methods, and in the same ranges as our previous work using SURF features with SVM . Approach (3) was less computationally intensive to train but more sensitive to unbalanced representation of the 6 classes in the training data. However we expect CNN performance to improve as we add more training data because both the features and the classifier are learned jointly from the data. *First two authors share first authorship.

Automated diagnosis of interstitial lung diseases and emphysema in MDCT imaging

NASA Astrophysics Data System (ADS)

Fetita, Catalin; Chang Chien, Kuang-Che; Brillet, Pierre-Yves; Prêteux, Françoise

2007-09-01

Diffuse lung diseases (DLD) include a heterogeneous group of non-neoplasic disease resulting from damage to the lung parenchyma by varying patterns of inflammation. Characterization and quantification of DLD severity using MDCT, mainly in interstitial lung diseases and emphysema, is an important issue in clinical research for the evaluation of new therapies. This paper develops a 3D automated approach for detection and diagnosis of diffuse lung diseases such as fibrosis/honeycombing, ground glass and emphysema. The proposed methodology combines multi-resolution 3D morphological filtering (exploiting the sup-constrained connection cost operator) and graph-based classification for a full characterization of the parenchymal tissue. The morphological filtering performs a multi-level segmentation of the low- and medium-attenuated lung regions as well as their classification with respect to a granularity criterion (multi-resolution analysis). The original intensity range of the CT data volume is thus reduced in the segmented data to a number of levels equal to the resolution depth used (generally ten levels). The specificity of such morphological filtering is to extract tissue patterns locally contrasting with their neighborhood and of size inferior to the resolution depth, while preserving their original shape. A multi-valued hierarchical graph describing the segmentation result is built-up according to the resolution level and the adjacency of the different segmented components. The graph nodes are then enriched with the textural information carried out by their associated components. A graph analysis-reorganization based on the nodes attributes delivers the final classification of the lung parenchyma in normal and ILD/emphysematous regions. It also makes possible to discriminate between different types, or development stages, among the same class of diseases.

A New Morphological Phylogeny of the Ophiuroidea (Echinodermata) Accords with Molecular Evidence and Renders Microfossils Accessible for Cladistics

PubMed Central

Thuy, Ben; Stöhr, Sabine

2016-01-01

Ophiuroid systematics is currently in a state of upheaval, with recent molecular estimates fundamentally clashing with traditional, morphology-based classifications. Here, we attempt a long overdue recast of a morphological phylogeny estimate of the Ophiuroidea taking into account latest insights on microstructural features of the arm skeleton. Our final estimate is based on a total of 45 ingroup taxa, including 41 recent species covering the full range of extant ophiuroid higher taxon diversity and 4 fossil species known from exceptionally preserved material, and the Lower Carboniferous Aganaster gregarius as the outgroup. A total of 130 characters were scored directly on specimens. The tree resulting from the Bayesian inference analysis of the full data matrix is reasonably well resolved and well supported, and refutes all previous classifications, with most traditional families discredited as poly- or paraphyletic. In contrast, our tree agrees remarkably well with the latest molecular estimate, thus paving the way towards an integrated new classification of the Ophiuroidea. Among the characters which were qualitatively found to accord best with our tree topology, we selected a list of potential synapomorphies for future formal clade definitions. Furthermore, an analysis with 13 of the ingroup taxa reduced to the lateral arm plate characters produced a tree which was essentially similar to the full dataset tree. This suggests that dissociated lateral arm plates can be analysed in combination with fully known taxa and thus effectively unlocks the extensive record of fossil lateral arm plates for phylogenetic estimates. Finally, the age and position within our tree implies that the ophiuroid crown-group had started to diversify by the Early Triassic. PMID:27227685

Algorithm for clinical evaluation and surgical treatment of gynaecomastia.

PubMed

Cordova, Adriana; Moschella, Francesco

2008-01-01

Gynaecomastia can be classified on the basis of the main characterising factors, i.e. pathogenesis, histopathology and morphology. The morphological classifications of gynaecomastia currently made often use subjective parameters and qualifying adjectives. In this paper the authors propose a scheme for morphological classification of gynaecomastia which can serve as a guide for choosing the surgical technique, once the diagnosis of gynaecomastia as a benign pathology has been confirmed by preoperative examinations. A retrospective analysis was made of 121 cases of gynaecomastia operated on in the last 5 years. The extent of the clinical picture, the technique employed, the complications and the need to re-operate were observed and related. On the basis of this review the authors observed that when the nipple-areola complex is above the inframammary fold (grade I and grade II gynaecomastia), complete flattening of the thorax can be achieved by means of suction or ultrasound-assisted lipectomy and skin-sparing adenectomy. When the nipple-areola complex is at the same height as, or at most 1cm below the fold (grade III gynaecomastia), skin-sparing techniques are no longer sufficient to flatten the thorax, and it becomes necessary to remove the redundant skin by means of periareolar removal of epidermis. In cases of marked ptosis, when the nipple-areola complex is more than 1cm below the fold (grade IV gynaecomastia), reduction mastoplasty becomes necessary, with upper repositioning of the nipple-areola complex; in these cases central pedicle techniques make it possible to limit scarring in the periareolar areas. In the preoperative phase this simple classification may help in choosing the most suitable treatment, thus avoiding insufficient or invasive treatments and undesirable scars.

Phylogeny of palaeotropic Derris-like taxa (Fabaceae) based on chloroplast and nuclear DNA sequences shows reorganization of (infra)generic classifications is needed.

PubMed

Sirichamorn, Yotsawate; Adema, Frits A C B; Gravendeel, Barbara; van Welzen, Peter C

2012-11-01

Palaeotropic Derris-like taxa (family Fabaceae, tribe Millettieae) comprise 6-9 genera. They are well known as important sources of rotenone toxin, which are used as organic insecticide and fish poison. However, their phylogenetic relationships and classification are still problematic due to insufficient sampling and high morphological variability. Fifty species of palaeotropic Derris-like taxa were sampled, which is more than in former studies. Three chloroplast genes (trnK-matK, trnL-F IGS, and psbA-trnH IGS) and nuclear ribosomal ITS /5.8S were analyzed using parsimony and Bayesian methods. Parsimony and Bayesian analyses of individual and combined markers show more or less similar tree topologies (only varying in terminal branches). The old-world monophyletic genera Aganope, Brachypterum, and Leptoderris are distinct from Derris s.s., and their generic status is here confirmed. Aganope may be classified into two or three subgeneric taxa. Paraderris has to be included in Derris s.s. to form a monophyletic group. The genera Philenoptera, Deguelia, and Lonchocarpus are monophyletic and distinct from each other and clearly separate from Derris s.s. Morphologically highly similar species of Derris s.s. are shown to be unrelated. Our study shows that previous infrageneric classifications of Derris are incorrect. Paraderris elliptica may contain several cryptic lineages that need further investigation. The concept of the genus Derris s.s. should be reorganized with a new generic circumscription by including Paraderris but excluding Brachypterum. Synapomorphic morphological features will be examined in future studies, and the status of the newly defined Derris and its closely related taxa will be formalized.

Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach.

PubMed

Cai, Hongmin; Peng, Yanxia; Ou, Caiwen; Chen, Minsheng; Li, Li

2014-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly used for breast cancer diagnosis as supplementary to conventional imaging techniques. Combining of diffusion-weighted imaging (DWI) of morphology and kinetic features from DCE-MRI to improve the discrimination power of malignant from benign breast masses is rarely reported. The study comprised of 234 female patients with 85 benign and 149 malignant lesions. Four distinct groups of features, coupling with pathological tests, were estimated to comprehensively characterize the pictorial properties of each lesion, which was obtained by a semi-automated segmentation method. Classical machine learning scheme including feature subset selection and various classification schemes were employed to build prognostic model, which served as a foundation for evaluating the combined effects of the multi-sided features for predicting of the types of lesions. Various measurements including cross validation and receiver operating characteristics were used to quantify the diagnostic performances of each feature as well as their combination. Seven features were all found to be statistically different between the malignant and the benign groups and their combination has achieved the highest classification accuracy. The seven features include one pathological variable of age, one morphological variable of slope, three texture features of entropy, inverse difference and information correlation, one kinetic feature of SER and one DWI feature of apparent diffusion coefficient (ADC). Together with the selected diagnostic features, various classical classification schemes were used to test their discrimination power through cross validation scheme. The averaged measurements of sensitivity, specificity, AUC and accuracy are 0.85, 0.89, 90.9% and 0.93, respectively. Multi-sided variables which characterize the morphological, kinetic, pathological properties and DWI measurement of ADC can dramatically improve the discriminatory power of breast lesions.

Reflectance-based determination of age and species of blowfly puparia.

PubMed

Voss, Sasha C; Magni, Paola; Dadour, Ian; Nansen, Christian

2017-01-01

Forensic entomology is primarily concerned with the estimation of time since death and involves determination of the age of immature insects colonising decomposing remains. Accurate age determination of puparia is usually accomplished by dissection, which means destructive sampling of evidence. As part of improving abilities to correctly identify species and developmental age, it is highly desirable to have available non-destructive methods. In this study, we acquired external hyperspectral imaging (HSI) data (77 spectral bands, 389-892 nm) from the dorsal and ventral sides of individual puparia of two species of blowfly (Diptera: Calliphoridae), Calliphora dubia Macquart 1855 and Chrysomya rufifacies Macquart 1842. Puparia were dissected to determine the presence/absence of eight internal morphological development characteristics (legs, wings, labella, abdominal segments, antennae, thoracic bristles, orbital/facial bristles and eye colour and arista). Based on linear discriminant analysis and independent validation of HSI data, reflectance features from puparia could be used to successfully (1) distinguish the two species (classification accuracy = 92.5 %), (2) differentiate dorsal and ventral sides of puparia (classification accuracy C. dubia = 81.5 %; Ch. rufifacies = 89.2 %) and (3) predict the presence of these morphological characteristics and therefore the developmental stage of puparia (average classification accuracy using dorsal imaging: C. dubia = 90.3 %; Ch. rufifacies = 94.0 %). The analytical approach presented here provides proof of concept for a direct puparial age relationship (i.e. days since the onset of pupation) between external puparial reflectance features and internal morphological development. Furthermore, this approach establishes the potential for further refinement by using a non-invasive technique to determine the age and developmental stage of blowflies of forensic importance.

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

VARSEDIG: an algorithm for morphometric characters selection and statistical validation in morphological taxonomy.

PubMed

Guisande, Cástor; Vari, Richard P; Heine, Jürgen; García-Roselló, Emilio; González-Dacosta, Jacinto; Perez-Schofield, Baltasar J García; González-Vilas, Luis; Pelayo-Villamil, Patricia

2016-09-12

We present and discuss VARSEDIG, an algorithm which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test. VARSEDIG is freely available as a function of the RWizard application PlotsR (http://www.ipez.es/RWizard) and as R package on CRAN. The variables selected by VARSEDIG with the overlap method were very similar to those selected by logistic regression and discriminant analysis, but overcomes some shortcomings of these methods. VARSEDIG is, therefore, a good alternative by comparison to current classical classification methods for identifying morphometric features that significantly discriminate a taxon and for validating its morphological distinctness from other taxa. As a demonstration of the potential of VARSEDIG for this purpose, we analyze morphological discrimination among some species of the Neotropical freshwater family Characidae.

River reach classification for the Greater Mekong Region at high spatial resolution

NASA Astrophysics Data System (ADS)

Ouellet Dallaire, C.; Lehner, B.

2014-12-01

River classifications have been used in river health and ecological assessments as coarse proxies to represent aquatic biodiversity when comprehensive biological and/or species data is unavailable. Currently there are no river classifications or biological data available in a consistent format for the extent of the Greater Mekong Region (GMR; including the Irrawaddy, the Salween, the Chao Praya, the Mekong and the Red River basins). The current project proposes a new river habitat classification for the region, facilitated by the HydroSHEDS (HYDROlogical SHuttle Elevation Derivatives at multiple Scales) database at 500m pixel resolution. The classification project is based on the Global River Classification framework relying on the creation of multiple sub-classifications based on different disciplines. The resulting classes from the sub-classification are later combined into final classes to create a holistic river reach classification. For the GMR, a final habitat classification was created based on three sub-classifications: a hydrological sub-classification based only on discharge indices (river size and flow variability); a physio-climatic sub-classification based on large scale indices of climate and elevation (biomes, ecoregions and elevation); and a geomorphological sub-classification based on local morphology (presence of floodplains, reach gradient and sand transport). Key variables and thresholds were identified in collaboration with local experts to ensure that regional knowledge was included. The final classification is composed 54 unique final classes based on 3 sub-classifications with less than 15 classes each. The resulting classifications are driven by abiotic variables and do not include biological data, but they represent a state-of-the art product based on best available data (mostly global data). The most common river habitat type is the "dry broadleaf, low gradient, very small river". These classifications could be applied in a wide range of hydro-ecological assessments and useful for a variety of stakeholders such as NGO, governments and researchers.

UTILIZATION OF T-RFLP (TERMINAL RESTRICTION FRAGMENT LENGTH POLYMORPHISM) TO CHARACTERIZE MIXED ECTOMYCORRHIZAL FUNGAL COMMUNITIES

EPA Science Inventory

Studies of ectomycorrhizal community structure have used a variety of analytical regimens including sole or partial reliance on gross morphological characterization of colonized root tips. Depending on the rigor of the classification protocol, this technique can incorrectly assig...

Quantification of mammalian tumor cell state plasticity with digital holographic cytometry

NASA Astrophysics Data System (ADS)

Hejna, Miroslav; Jorapur, Aparna; Zhang, Yuntian; Song, Jun S.; Judson, Robert L.

2018-02-01

Individual cells within isogenic tumor populations can exhibit distinct cellular morphologies, behaviors, and molecular profiles. Cell state plasticity refers to the propensity of a cell to transition between these different morphologies and behaviors. Elevation of cell state plasticity is thought to contribute to critical stages in tumor evolution, including metastatic dissemination and acquisition of therapeutic resistance. However, methods for quantifying general plasticity in mammalian cells remain limited. Working with a HoloMonitor M4 digital holographic cytometry platform, we have established a machine learning-based pipeline for high accuracy and label-free classification of adherent cells. We use twenty-six morphological and optical density-derived features for label-free identification of cell state in heterogeneous cultures. The system is housed completely within a mammalian cell incubator, permitting the monitoring of changes in cell state over time. Here we present an application of our approach for studying cell state plasticity. Human melanoma cell lines of known metastatic potential were monitored in standard growth conditions. The rate of feature change was quantified for each individual cell in the populations. We observed that cells of higher metastatic potential exhibited more rapid fluctuation of cell state in homeostatic conditions. The approach we demonstrate will be advantageous for further investigations into the factors that influence cell state plasticity.

Airway remodelling in the transplanted lung.

PubMed

Kuehnel, Mark; Maegel, Lavinia; Vogel-Claussen, Jens; Robertus, Jan Lukas; Jonigk, Danny

2017-03-01

Following lung transplantation, fibrotic remodelling of the small airways has been recognized for almost 5 decades as the main correlate of chronic graft failure and a major obstacle to long-term survival. Mainly due to airway fibrosis, pulmonary allografts currently show the highest attrition rate of all solid organ transplants, with a 5-year survival rate of 58 % on a worldwide scale. The observation that these morphological changes are not just the hallmark of chronic rejection but rather represent a manifestation of a multitude of alloimmune-dependent and -independent injuries was made more recently, as was the discovery that chronic lung allograft dysfunction manifests in different clinical phenotypes of respiratory impairment and corresponding morphological subentities. Although recent years have seen considerable advances in identifying and categorizing these subgroups on the basis of clinical, functional and histomorphological changes, as well as susceptibility to medicinal treatment, this process is far from over. Since the actual pathophysiological mechanisms governing airway remodelling are still only poorly understood, diagnosis and therapy of chronic lung allograft dysfunction presents a major challenge to clinicians, radiologists and pathologists alike. Here, we review and discuss the current state of the literature on chronic lung allograft dysfunction and shed light on classification systems, corresponding clinical and morphological changes, key cellular players and underlying molecular pathways, as well as on emerging diagnostic and therapeutic approaches.

Skeletal trade-offs in coralline algae in response to ocean acidification

NASA Astrophysics Data System (ADS)

McCoy, S. J.; Ragazzola, F.

2014-08-01

Ocean acidification is changing the marine environment, with potentially serious consequences for many organisms. Much of our understanding of ocean acidification effects comes from laboratory experiments, which demonstrate physiological responses over relatively short timescales. Observational studies and, more recently, experimental studies in natural systems suggest that ocean acidification will alter the structure of seaweed communities. Here, we provide a mechanistic understanding of altered competitive dynamics among a group of seaweeds, the crustose coralline algae (CCA). We compare CCA from historical experiments (1981-1997) with specimens from recent, identical experiments (2012) to describe morphological changes over this time period, which coincides with acidification of seawater in the Northeastern Pacific. Traditionally thick species decreased in thickness by a factor of 2.0-2.3, but did not experience a change in internal skeletal metrics. In contrast, traditionally thin species remained approximately the same thickness but reduced their total carbonate tissue by making thinner inter-filament cell walls. These changes represent alternative mechanisms for the reduction of calcium carbonate production in CCA and suggest energetic trade-offs related to the cost of building and maintaining a calcium carbonate skeleton as pH declines. Our classification of stress response by morphological type may be generalizable to CCA at other sites, as well as to other calcifying organisms with species-specific differences in morphological types.

A New Classification of the Dictyostelids.

PubMed

Sheikh, Sanea; Thulin, Mats; Cavender, James C; Escalante, Ricardo; Kawakami, Shin-Ichi; Lado, Carlos; Landolt, John C; Nanjundiah, Vidyanand; Queller, David C; Strassmann, Joan E; Spiegel, Frederick W; Stephenson, Steven L; Vadell, Eduardo M; Baldauf, Sandra L

2018-02-01

Traditional morphology-based taxonomy of dictyostelids is rejected by molecular phylogeny. A new classification is presented based on monophyletic entities with consistent and strong molecular phylogenetic support and that are, as far as possible, morphologically recognizable. All newly named clades are diagnosed with small subunit ribosomal RNA (18S rRNA) sequence signatures plus morphological synapomorphies where possible. The two major molecular clades are given the rank of order, as Acytosteliales ord. nov. and Dictyosteliales. The two major clades within each of these orders are recognized and given the rank of family as, respectively, Acytosteliaceae and Cavenderiaceae fam. nov. in Acytosteliales, and Dictyosteliaceae and Raperosteliaceae fam. nov. in Dictyosteliales. Twelve genera are recognized: Cavenderia gen. nov. in Cavenderiaceae, Acytostelium, Rostrostelium gen. nov. and Heterostelium gen. nov. in Acytosteliaceae, Tieghemostelium gen. nov., Hagiwaraea gen. nov., Raperostelium gen. nov. and Speleostelium gen. nov. in Raperosteliaceae, and Dictyostelium and Polysphondylium in Dictyosteliaceae. The "polycephalum" complex is treated as Coremiostelium gen. nov. (not assigned to family) and the "polycarpum" complex as Synstelium gen. nov. (not assigned to order and family). Coenonia, which may not be a dictyostelid, is treated as a genus incertae sedis. Eighty-eight new combinations are made at species and variety level, and Dictyostelium ammophilum is validated. Copyright © 2017 Elsevier GmbH. All rights reserved.

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

Classification and Morphological Parameters of the Scapular Spine

PubMed Central

Wang, Hua-Jun; Giambini, Hugo; Hou, Da-Biao; Huan, Song-Wei; Liu, Ning; Yang, Jie; Chen, Chao; Gao, Yan-Ping; Shang, Ru-Guo; Li, Yi-Kai; Zha, Zhen-gang

2015-01-01

Abstract Incidence of scapular spine (SS) fractures as a result of complications of reverse total shoulder arthroplasty is relatively high leading to inferior clinical outcomes and an increased risk of revision and dislocation. Fractures of SS because of trauma, including the acromion, constitute 6% to 23% of scapula fractures. The purpose of this study was to classify the SS and present specific geometrical parameters according to osteologic features. A total of 319 intact dry scapulae were collected and classified based on morphological characteristics and shape of the SS. Nine bony landmarks were also chosen and described for their relevance to regions of interest for scapular fixation. Five specific types of SS were noted and the most prevalent groups were Type 1 (Fusiform shape) (47.17%) and Type 5 (Horizontal S-shape) (19.18%). Overall, Types 3, 4, and 1 showed thicker landmark values compared to Type 5, with Type 2 having smaller values. Our classification into 5 distinct types allowed appreciation of the anatomical variance of SSs. The contours of Types 5 and 1 presented a more complex morphology and may lead to a worse surgical approach due to a fracture. As Types 2 and 5 were much thinner than the other types, these may be more susceptible to fractures. PMID:26559282

Diagnostic index of three-dimensional osteoarthritic changes in temporomandibular joint condylar morphology

PubMed Central

Gomes, Liliane R.; Gomes, Marcelo; Jung, Bryan; Paniagua, Beatriz; Ruellas, Antonio C.; Gonçalves, João Roberto; Styner, Martin A.; Wolford, Larry; Cevidanes, Lucia

2015-01-01

Abstract. This study aimed to investigate imaging statistical approaches for classifying three-dimensional (3-D) osteoarthritic morphological variations among 169 temporomandibular joint (TMJ) condyles. Cone-beam computed tomography scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA), 15 subjects at initial diagnosis of OA, and 7 healthy controls. Three-dimensional surface models of the condyles were constructed and SPHARM-PDM established correspondent points on each model. Multivariate analysis of covariance and direction-projection-permutation (DiProPerm) were used for testing statistical significance of the differences between the groups determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering was then conducted. Compared with healthy controls, OA average condyle was significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis. We observed areas of 3.88-mm bone resorption at the superior surface and 3.10-mm bone apposition at the anterior aspect of the long-term OA average model. DiProPerm supported a significant difference between the healthy control and OA group (p-value=0.001). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3-D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition. PMID:26158119

Phylogeny and classification of Naucleeae s.l. (Rubiaceae) inferred from molecular (ITS, rBCL, and tRNT-F) and morphological data.

PubMed

Razafimandimbison, Sylvain G; Bremer, Birgitta

2002-07-01

Parsimony analyses of the tribe Naucleeae sensu lato (s.l.) using the noncoding internal transcribed spacer (ITS) regions of nuclear rDNA, the protein-coding rbcL and noncoding trnT-F regions of chloroplast DNA, and morphological data were performed to construct new intratribal classification, test the monophyly of previous subtribal circumscriptions, and evaluate the generic status of Naucleeae s.l. Fifty-two ITS, 45 rbcL, and 55 trnT-F new sequences are published here. Our study supports the monophyly of the subtribes Anthocephalidae, Mitragynae, Uncariae all sensu Haviland and Naucleinae sensu Ridsdale. There was no support for Cephalanthidae sensu Haviland and Adininae sensu Ridsdale. Naucleeae can be subdivided into six highly supported and morphologically distinct subtribes, Breoniinae, Cephalanthinae, Corynantheinae, Naucleinae, and Mitragyninae, Uncarinae, plus one, Adininae, which is poorly supported. The relationships among these subtribes were largely unresolved. We maintain the following 22 genera: Adina, Adinauclea, Breonadia, Breonia, Burttdavya, Cephalanthus, Gyrostipula, Haldina, Janotia, Ludekia, Metadina, Mitragyna, Myrmeconauclea, Nauclea, Neolamarckia, Neonauclea, Ochreinauclea, Pausinystalia, Pertusadina, Sarcocephalus, Sinoadina, and Uncaria. Pseudocinchona is reestablished. Corynanthe is restricted to C. paniculata and Hallea is reincluded in Mitragyna. Our results were inconclusive for assessing the relationships among Adina, Adinauclea, Metadina, and Pertusadina due to lack of resolution.

Three-gene based phylogeny of the Urostyloidea (Protista, Ciliophora, Hypotricha), with notes on classification of some core taxa☆

PubMed Central

Huang, Jie; Chen, Zigui; Song, Weibo; Berger, Helmut

2014-01-01

Classifications of the Urostyloidea were mainly based on morphology and morphogenesis. Since molecular phylogeny largely focused on limited sampling using mostly the one-gene information, the incongruence between morphological data and gene sequences have risen. In this work, the three-gene data (SSU-rDNA, ITS1-5.8S-ITS2 and LSU-rDNA) comprising 12 genera in the “core urostyloids” are sequenced, and the phylogenies based on these different markers are compared using maximum-likelihood and Bayesian algorithms and tested by unconstrained and constrained analyses. The molecular phylogeny supports the following conclusions: (1) the monophyly of the core group of Urostyloidea is well supported while the whole Urostyloidea is not monophyletic; (2) Thigmokeronopsis and Apokeronopsis are clearly separated from the pseudokeronopsids in analyses of all three gene markers, supporting their exclusion from the Pseudokeronopsidae and the inclusion in the Urostylidae; (3) Diaxonella and Apobakuella should be assigned to the Urostylidae; (4) Bergeriella, Monocoronella and Neourostylopsis flavicana share a most recent common ancestor; (5) all molecular trees support the transfer of Metaurostylopsis flavicana to the recently proposed genus Neourostylopsis; (6) all molecular phylogenies fail to separate the morphologically well-defined genera Uroleptopsis and Pseudokeronopsis; and (7) Arcuseries gen. nov. containing three distinctly deviating Anteholosticha species is established. PMID:24140978

Phylogeny and classification of the Litostomatea (Protista, Ciliophora), with emphasis on free-living taxa and the 18S rRNA gene.

PubMed

Vd'ačný, Peter; Bourland, William A; Orsi, William; Epstein, Slava S; Foissner, Wilhelm

2011-05-01

The class Litostomatea is a highly diverse ciliate taxon comprising hundreds of species ranging from aerobic, free-living predators to anaerobic endocommensals. This is traditionally reflected by classifying the Litostomatea into the subclasses Haptoria and Trichostomatia. The morphological classifications of the Haptoria conflict with the molecular phylogenies, which indicate polyphyly and numerous homoplasies. Thus, we analyzed the genealogy of 53 in-group species with morphological and molecular methods, including 12 new sequences from free-living taxa. The phylogenetic analyses and some strong morphological traits show: (i) body polarization and simplification of the oral apparatus as main evolutionary trends in the Litostomatea and (ii) three distinct lineages (subclasses): the Rhynchostomatia comprising Tracheliida and Dileptida; the Haptoria comprising Lacrymariida, Haptorida, Didiniida, Pleurostomatida and Spathidiida; and the Trichostomatia. The curious Homalozoon cannot be assigned to any of the haptorian orders, but is basal to a clade containing the Didiniida and Pleurostomatida. The internal relationships of the Spathidiida remain obscure because many of them and some "traditional" haptorids form separate branches within the basal polytomy of the order, indicating one or several radiations and convergent evolution. Due to the high divergence in the 18S rRNA gene, the chaeneids and cyclotrichiids are classified incertae sedis. Copyright © 2011 Elsevier Inc. All rights reserved.

A geometric morphometric analysis of hominin upper premolars. Shape variation and morphological integration.

PubMed

Gómez-Robles, Aida; Martinón-Torres, María; Bermúdez de Castro, José María; Prado-Simón, Leyre; Arsuaga, Juan Luis

2011-12-01

This paper continues the series of articles initiated in 2006 that analyse hominin dental crown morphology by means of geometric morphometric techniques. The detailed study of both upper premolar occlusal morphologies in a comprehensive sample of hominin fossils, including those coming from the Gran Dolina-TD6 and Sima de los Huesos sites from Atapuerca, Spain, complement previous works on lower first and second premolars and upper first molars. A morphological gradient consisting of the change from asymmetric to symmetric upper premolars and a marked reduction of the lingual cusp in recent Homo species has been observed in both premolars. Although percentages of correct classification based on upper premolar morphologies are not very high, significant morphological differences between Neanderthals (and European middle Pleistocene fossils) and modern humans have been identified, especially in upper second premolars. The study of morphological integration between premolar morphologies reveals significant correlations that are weaker between upper premolars than between lower ones and significant correlations between antagonists. These results have important implications for understanding the genetic and functional factors underlying dental phenotypic variation and covariation. Copyright © 2011 Elsevier Ltd. All rights reserved.

The correlation of sperm morphology with unexplained recurrent spontaneous abortion: A systematic review and meta-analysis

PubMed Central

Cao, Xiaodan; Cui, Yun; Zhang, Xiaoxia; Lou, Jiangtao; Zhou, Jun; Wei, Renxiong

2017-01-01

Sperm morphology displays a potential impact on sperm function and may ultimately impact reproductive function. Current studies have investigated the correlation between sperm morphology with unexplained recurrent spontaneous abortion (RSA) but have shown inconsistent results. Hence, we systematically searched MEDLINE, EMBASE, CNKI databases, as well as the Cochrane Library for studies that examined the association between sperm morphology and unexplained RSA. Fifteen studies were identified, including 883 cases and 530 controls. Our meta-analysis results indicated that the percentage of normal sperm morphology from men with RSA partners was significantly lower than those from normal controls(SMD [95% CI]: − 0.60 [−0.81, −0.40]; P<0.00001) and the percentage of sperm morphologic alterations was significantly higher in patients with RSA compared with the control group (SMD [95% CI]: 0.92 [0.42, 1.43]; P=0.0004). The present study suggested that the percentage of normal sperm morphology may indeed decrease in men from RSA group compared with controls. However, there were some limitations in the study such as the differences in stain techniques and classification criteria. Further evidences are needed to better elucidate the relationship between sperm morphology and unexplained RSA. PMID:28903451

White blood cells identification system based on convolutional deep neural learning networks.

PubMed

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A proposed new classification for the renal collecting system of cattle.

PubMed

Pereira-Sampaio, Marco A; Bagetti Filho, Helio J S; Carvalho, Francismar S; Sampaio, Francisco J B; Henry, Robert W

2010-11-01

To evaluate the intrarenal anatomy of kidneys obtained from cattle and to propose a new classification for the renal collecting system of cattle. 37 kidneys from 20 adult male mixed-breed cattle. Intrarenal anatomy was evaluated by the use of 3-D endocasts made of the kidneys. The number of renal lobes and minor renal calyces in each kidney and each renal region (cranial pole, caudal pole, and hilus) was quantified. The renal pelvis was evident in all casts and was classified into 2 types (nondilated [28/37 {75.7%}] or dilated [9/37 {24.3%}]). All casts had a major renal calyx associated with the cranial pole and the caudal pole. The number of minor renal calices per kidney ranged from 13 to 64 (mean, 22.7). There was a significant correlation between the number of renal lobes and the number of minor renal calices for the entire kidney, the cranial pole region, and the hilus region; however, there was not a similar significant correlation for the caudal pole region. Major and minor renal calices were extremely narrow, compared with major and minor renal calices in pigs and humans. The renal collecting system of cattle, with a renal pelvis and 2 major renal calices connected to several minor renal calices by an infundibulum, differed substantially from the renal collecting system of pigs and humans. From a morphological standpoint, the kidneys of cattle were not suitable for use as a model in endourologic research and training.

Classification and Characterization of Therapeutic Antibody Aggregates

PubMed Central

Joubert, Marisa K.; Luo, Quanzhou; Nashed-Samuel, Yasser; Wypych, Jette; Narhi, Linda O.

2011-01-01

A host of diverse stress techniques was applied to a monoclonal antibody (IgG2) to yield protein particles with varying attributes and morphologies. Aggregated solutions were evaluated for percent aggregation, particle counts, size distribution, morphology, changes in secondary and tertiary structure, surface hydrophobicity, metal content, and reversibility. Chemical modifications were also identified in a separate report (Luo, Q., Joubert, M. K., Stevenson, R., Narhi, L. O., and Wypych, J. (2011) J. Biol. Chem. 286, 25134–25144). Aggregates were categorized into seven discrete classes, based on the traits described. Several additional molecules (from the IgG1 and IgG2 subtypes as well as intravenous IgG) were stressed and found to be defined with the same classification system. The mechanism of protein aggregation and the type of aggregate formed depends on the nature of the stress applied. Different IgG molecules appear to aggregate by a similar mechanism under the same applied stress. Aggregates created by harsh mechanical stress showed the largest number of subvisible particles, and the class generated by thermal stress displayed the largest number of visible particles. Most classes showed a disruption of the higher order structure, with the degree of disorder depending on the stress process. Particles in all classes (except thermal stress) were at least partially reversible upon dilution in pH 5 buffer. High copper content was detected in isolated metal-catalyzed aggregates, a stress previously shown to produce immunogenic aggregates. In conclusion, protein aggregates can be a very heterogeneous population, whose qualities are the result of the type of stress that was experienced. PMID:21454532

Comparison of mandibular first molar mesial root canal morphology using micro-computed tomography and clearing technique.

PubMed

Kim, Yeun; Perinpanayagam, Hiran; Lee, Jong-Ki; Yoo, Yeon-Jee; Oh, Soram; Gu, Yu; Lee, Seung-Pyo; Chang, Seok Woo; Lee, Woocheol; Baek, Seung-Ho; Zhu, Qiang; Kum, Kee-Yeon

2015-08-01

Micro-computed tomography (MCT) with alternative image reformatting techniques shows complex and detailed root canal anatomy. This study compared two-dimensional (2D) and 3D MCT image reformatting with standard tooth clearing for studying mandibular first molar mesial root canal morphology. Extracted human mandibular first molar mesial roots (n=31) were scanned by MCT (Skyscan 1172). 2D thin-slab minimum intensity projection (TS-MinIP) and 3D volume rendered images were constructed. The same teeth were then processed by clearing and staining. For each root, images obtained from clearing, 2D, 3D and combined 2D and 3D techniques were examined independently by four endodontists and categorized according to Vertucci's classification. Fine anatomical structures such as accessory canals, intercanal communications and loops were also identified. Agreement among the four techniques for Vertucci's classification was 45.2% (14/31). The most frequent were Vertucci's type IV and then type II, although many had complex configurations that were non-classifiable. Generally, complex canal systems were more clearly visible in MCT images than with standard clearing and staining. Fine anatomical structures such as intercanal communications, accessory canals and loops were mostly detected with a combination of 2D TS-MinIP and 3D volume-rendering MCT images. Canal configurations and fine anatomic structures were more clearly observed in the combined 2D and 3D MCT images than the clearing technique. The frequency of non-classifiable configurations demonstrated the complexity of mandibular first molar mesial root canal anatomy.

Evaluation of cell count and classification capabilities in body fluids using a fully automated Sysmex XN equipped with high-sensitive Analysis (hsA) mode and DI-60 hematology analyzer system.

PubMed

Takemura, Hiroyuki; Ai, Tomohiko; Kimura, Konobu; Nagasaka, Kaori; Takahashi, Toshihiro; Tsuchiya, Koji; Yang, Haeun; Konishi, Aya; Uchihashi, Kinya; Horii, Takashi; Tabe, Yoko; Ohsaka, Akimichi

2018-01-01

The XN series automated hematology analyzer has been equipped with a body fluid (BF) mode to count and differentiate leukocytes in BF samples including cerebrospinal fluid (CSF). However, its diagnostic accuracy is not reliable for CSF samples with low cell concentration at the border between normal and pathologic level. To overcome this limitation, a new flow cytometry-based technology, termed "high sensitive analysis (hsA) mode," has been developed. In addition, the XN series analyzer has been equipped with the automated digital cell imaging analyzer DI-60 to classify cell morphology including normal leukocytes differential and abnormal malignant cells detection. Using various BF samples, we evaluated the performance of the XN-hsA mode and DI-60 compared to manual microscopic examination. The reproducibility of the XN-hsA mode showed good results in samples with low cell densities (coefficient of variation; % CV: 7.8% for 6 cells/μL). The linearity of the XN-hsA mode was established up to 938 cells/μL. The cell number obtained using the XN-hsA mode correlated highly with the corresponding microscopic examination. Good correlation was also observed between the DI-60 analyses and manual microscopic classification for all leukocyte types, except monocytes. In conclusion, the combined use of cell counting with the XN-hsA mode and automated morphological analyses using the DI-60 mode is potentially useful for the automated analysis of BF cells.

Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics

PubMed Central

Ruvindy, Rendy; White III, Richard Allen; Neilan, Brett Anthony; Burns, Brendan Paul

2016-01-01

Modern microbial mats are potential analogues of some of Earth's earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic next-generation sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats. PMID:26023869

UNDERSTANDING THE INTERNATIONAL CONSENSUS FOR ACUTE PANCREATITIS: CLASSIFICATION OF ATLANTA 2012

PubMed Central

de SOUZA, Gleim Dias; SOUZA, Luciana Rodrigues Queiroz; CUENCA, Ronaldo Máfia; JERÔNIMO, Bárbara Stephane de Medeiros; de SOUZA, Guilherme Medeiros; VILELA, Vinícius Martins

2016-01-01

ABSTRACT Introduction: Contrast computed tomography and magnetic resonance imaging are widely used due to its image quality and ability to study pancreatic and peripancreatic morphology. The understanding of the various subtypes of the disease and identification of possible complications requires a familiarity with the terminology, which allows effective communication between the different members of the multidisciplinary team. Aim: Demonstrate the terminology and parameters to identify the different classifications and findings of the disease based on the international consensus for acute pancreatitis ( Atlanta Classification 2012). Methods: Search and analysis of articles in the "CAPES Portal de Periódicos with headings "acute pancreatitis" and "Atlanta Review". Results: Were selected 23 articles containing radiological descriptions, management or statistical data related to pathology. Additional statistical data were obtained from Datasus and Population Census 2010. The radiological diagnostic criterion adopted was the Radiology American College system. The "acute pancreatitis - 2012 Rating: Review Atlanta classification and definitions for international consensus" tries to eliminate inconsistency and divergence from the determination of uniformity to the radiological findings, especially the terminology related to fluid collections. More broadly as "pancreatic abscess" and "phlegmon" went into disuse and the evolution of the collection of patient fluids can be described as "acute peripancreatic collections", "acute necrotic collections", "pseudocyst" and "necrosis pancreatic walled or isolated". Conclusion: Computed tomography and magnetic resonance represent the best techniques with sequential images available for diagnosis. Standardization of the terminology is critical and should improve the management of patients with multiple professionals care, risk stratification and adequate treatment. PMID:27759788

Australian sea-floor survey data, with images and expert annotations.

PubMed

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Marzinelli, Ezequiel M; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Australian sea-floor survey data, with images and expert annotations

PubMed Central

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research. PMID:26528396

Australian sea-floor survey data, with images and expert annotations

NASA Astrophysics Data System (ADS)

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-10-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management.

PubMed

Williams, Bradley S; D'Amico, Ellen; Kastens, Jude H; Thorp, James H; Flotemersch, Joseph E; Thoms, Martin C

2013-09-01

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.

MDS classification is improving in an era of the WHO 2016 criteria of MDS: A population-based analysis among 9159 MDS patients diagnosed in the Netherlands.

PubMed

Dinmohamed, Avinash G; Visser, Otto; Posthuma, Eduardus F M; Huijgens, Peter C; Sonneveld, Pieter; van de Loosdrecht, Arjan A; Jongen-Lavrencic, Mojca

2017-10-01

Morphologic and cytogenetic assessments are required to characterize diagnostic and prognostic features of myelodysplastic syndromes (MDS). We assessed whether these assessments were performed among newly diagnosed MDS patients in the Netherlands. MDS cases were retrieved from the nationwide Netherlands Cancer Registry (N=9159; period 2001-2014) and the regional PHAROS MDS registry (N=676; period 2008-2011). The proportion of unclassified MDS decreased from 58% in 2001 to 13% in 2014. Data from the more detailed PHAROS registry revealed that the degree of bone marrow dysplasia was only reported in ∼30% of all evaluable bone marrow aspirates. Further, the International Prognostic Scoring System was undetermined in 55% of patients, primarily owing to unperformed cytogenetics in 46% of patients. The classification of MDS is improving in the Netherlands. Nevertheless, particular diagnostic and prognostic procedures that are essential for the diagnosis and subsequent treatment decision-making of MDS were not fully utilized in particular patient subsets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Random-Forest Classification of High-Resolution Remote Sensing Images and Ndsm Over Urban Areas

NASA Astrophysics Data System (ADS)

Sun, X. F.; Lin, X. G.

2017-09-01

As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3D geometry data, our method proceeds in three main stages: feature extraction, classification, and classified result refinement. First, we extract color, vegetation index and texture features from the multi-spectral image and compute the height, elevation texture and differential morphological profile (DMP) features from the 3D geometry data. Then in the classification stage, multiple random forest (RF) classifiers are trained separately, then combined to form a RF ensemble to estimate each sample's category probabilities. Finally the probabilities along with the feature importance indicator outputted by RF ensemble are used to construct a fully connected conditional random field (FCCRF) graph model, by which the classification results are refined through mean-field based statistical inference. Experiments on the ISPRS Semantic Labeling Contest dataset show that our proposed 3-stage method achieves 86.9% overall accuracy on the test data.

Wavelet-based multicomponent denoising on GPU to improve the classification of hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco; Mouriño, J. C.

2017-10-01

Supervised classification allows handling a wide range of remote sensing hyperspectral applications. Enhancing the spatial organization of the pixels over the image has proven to be beneficial for the interpretation of the image content, thus increasing the classification accuracy. Denoising in the spatial domain of the image has been shown as a technique that enhances the structures in the image. This paper proposes a multi-component denoising approach in order to increase the classification accuracy when a classification method is applied. It is computed on multicore CPUs and NVIDIA GPUs. The method combines feature extraction based on a 1Ddiscrete wavelet transform (DWT) applied in the spectral dimension followed by an Extended Morphological Profile (EMP) and a classifier (SVM or ELM). The multi-component noise reduction is applied to the EMP just before the classification. The denoising recursively applies a separable 2D DWT after which the number of wavelet coefficients is reduced by using a threshold. Finally, inverse 2D-DWT filters are applied to reconstruct the noise free original component. The computational cost of the classifiers as well as the cost of the whole classification chain is high but it is reduced achieving real-time behavior for some applications through their computation on NVIDIA multi-GPU platforms.

Traditional knowledge among Zapotecs of Sierra Madre Del Sur, Oaxaca. Does it represent a base for plant resources management and conservation?

PubMed

Luna-José, Azucena de Lourdes; Aguilar, Beatriz Rendón

2012-07-12

Traditional classification systems represent cognitive processes of human cultures in the world. It synthesizes specific conceptions of nature, as well as cumulative learning, beliefs and customs that are part of a particular human community or society. Traditional knowledge has been analyzed from different viewpoints, one of which corresponds to the analysis of ethnoclassifications. In this work, a brief analysis of the botanical traditional knowledge among Zapotecs of the municipality of San Agustin Loxicha, Oaxaca was conducted. The purposes of this study were: a) to analyze the traditional ecological knowledge of local plant resources through the folk classification of both landscapes and plants and b) to determine the role that this knowledge has played in plant resource management and conservation. The study was developed in five communities of San Agustín Loxicha. From field trips, plant specimens were collected and showed to local people in order to get the Spanish or Zapotec names; through interviews with local people, we obtained names and identified classification categories of plants, vegetation units, and soil types. We found a logic structure in Zapotec plant names, based on linguistic terms, as well as morphological and ecological caracteristics. We followed the classification principles proposed by Berlin [6] in order to build a hierarchical structure of life forms, names and other characteristics mentioned by people. We recorded 757 plant names. Most of them (67%) have an equivalent Zapotec name and the remaining 33% had mixed names with Zapotec and Spanish terms. Plants were categorized as native plants, plants introduced in pre-Hispanic times, or plants introduced later. All of them are grouped in a hierarchical classification, which include life form, generic, specific, and varietal categories. Monotypic and polytypic names are used to further classify plants. This holistic classification system plays an important role for local people in many aspects: it helps to organize and make sense of the diversity, to understand the interrelation among plants-soil-vegetation and to classify their physical space since they relate plants with a particular vegetation unit and a kind of soil. The locals also make a rational use of these elements, because they know which crops can grow in any vegetation unit, or which places are indicated to recollect plants. These aspects are interconnected and could be fundamental for a rational use and management of plant resources.

A study of morphology, provenance, and movement of desert sand seas in Africa, Asia, and Australia

NASA Technical Reports Server (NTRS)

Mckee, E. D.; Breed, C. S.

1973-01-01

A description and classification of major types of sand seas on the basis of morphological pattern and lineation are discussed. The steps involved in analyzing the patterns of deposits on ERTS-1 imagery, where the visible forms are mostly dune complexes rather than individual dunes are outlined. After completion of thematic maps portraying the pattern and lineation of the sand bodies, data on directions and intensity of prevailing and other winds are plotted on corresponding bases, as a preliminary to determination of internal structures through ground truth.

Ecological Land Classification: Applications to Identify the Productive Potential of Southern Forests

Treesearch

Dennis L. Mengel; D. Thompson Tew; [Editors

1991-01-01

Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.

The Continuous Plankton Imaging and Classification Sensor (CPICS): A Sensor for Quantifying Mesoplankton Biodiversity and Community Structure

NASA Astrophysics Data System (ADS)

Gallager, S. M.

2016-02-01

Marine ecosystems are changing at a variety of time scales as a function of a diverse suite of forcing functions both natural and anthropogenic. Establishing a continuous plankton time series consisting of scales from rapid (seconds) to long-term (decades), provides a sentinel for ecosystem change. The key is to measure plankton biodiversity at sufficiently fast time scales that allow disentanglement of physical (transport) and biological (growth) properties of an ecosystem. CPICS is a plankton and particle imaging microscope system that is designed to produce crisp darkfield images of light scattering material in aquatic environments. The open flow design is non-invasive and non-restrictive providing images of very fragile plankton in their natural orientation. Several magnifications are possible from 0.5 to 5x forming a field of view of 10cm to 1mm, respectively. CPICS has been installed on several cabled observing systems called OceanCubes off the coast of Okinawa and Tokyo, Japan providing a continuous stream of plankton images to a machine vision image classifier located at WHOI. Image features include custom algorithms for texture, color pattern, morphology and shape, which are extracted from in-focus target. The features are then used to train a classifier (e.g., Random Forest) resulting in classifications that are tested using cross-validation, confusion matrices and ROC curves. High (>90%) classification accuracies are possible depending on the number of training categories and target complexity. A web-based utility allows access to raw images, training sets, classifiers and classification results. Combined with chemical and physical data from the observatories, an ecologically meaningful plankton index of biodiversity and its variance is developed using a combination of species and taxon groups, which provides an approach for understanding ecosystem change without the need to identify all targets to species. http://oceancubes.whoi.edu/instruments/CPICS

Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus.

PubMed

Jouhet, Vianney; Mougin, Fleur; Bréchat, Bérénice; Thiessard, Frantz

2017-02-07

Identifying incident cancer cases within a population remains essential for scientific research in oncology. Data produced within electronic health records can be useful for this purpose. Due to the multiplicity of providers, heterogeneous terminologies such as ICD-10 and ICD-O-3 are used for oncology diagnosis recording purpose. To enable disease identification based on these diagnoses, there is a need for integrating disease classifications in oncology. Our aim was to build a model integrating concepts involved in two disease classifications, namely ICD-10 (diagnosis) and ICD-O-3 (topography and morphology), despite their structural heterogeneity. Based on the NCIt, a "derivative" model for linking diagnosis and topography-morphology combinations was defined and built. ICD-O-3 and ICD-10 codes were then used to instantiate classes of the "derivative" model. Links between terminologies obtained through the model were then compared to mappings provided by the Surveillance, Epidemiology, and End Results (SEER) program. The model integrated 42% of neoplasm ICD-10 codes (excluding metastasis), 98% of ICD-O-3 morphology codes (excluding metastasis) and 68% of ICD-O-3 topography codes. For every codes instantiating at least a class in the "derivative" model, comparison with SEER mappings reveals that all mappings were actually available in the model as a link between the corresponding codes. We have proposed a method to automatically build a model for integrating ICD-10 and ICD-O-3 based on the NCIt. The resulting "derivative" model is a machine understandable resource that enables an integrated view of these heterogeneous terminologies. The NCIt structure and the available relationships can help to bridge disease classifications taking into account their structural and granular heterogeneities. However, (i) inconsistencies exist within the NCIt leading to misclassifications in the "derivative" model, (ii) the "derivative" model only integrates a part of ICD-10 and ICD-O-3. The NCIt is not sufficient for integration purpose and further work based on other termino-ontological resources is needed in order to enrich the model and avoid identified inconsistencies.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Galaxy Classifications with Deep Learning

NASA Astrophysics Data System (ADS)

Lukic, Vesna; Brüggen, Marcus

2017-06-01

Machine learning techniques have proven to be increasingly useful in astronomical applications over the last few years, for example in object classification, estimating redshifts and data mining. One example of object classification is classifying galaxy morphology. This is a tedious task to do manually, especially as the datasets become larger with surveys that have a broader and deeper search-space. The Kaggle Galaxy Zoo competition presented the challenge of writing an algorithm to find the probability that a galaxy belongs in a particular class, based on SDSS optical spectroscopy data. The use of convolutional neural networks (convnets), proved to be a popular solution to the problem, as they have also produced unprecedented classification accuracies in other image databases such as the database of handwritten digits (MNIST †) and large database of images (CIFAR ‡). We experiment with the convnets that comprised the winning solution, but using broad classifications. The effect of changing the number of layers is explored, as well as using a different activation function, to help in developing an intuition of how the networks function and to see how they can be applied to radio galaxy images.

Hyperspectral Image Enhancement and Mixture Deep-Learning Classification of Corneal Epithelium Injuries.

PubMed

Noor, Siti Salwa Md; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-11-16

In our preliminary study, the reflectance signatures obtained from hyperspectral imaging (HSI) of normal and abnormal corneal epithelium tissues of porcine show similar morphology with subtle differences. Here we present image enhancement algorithms that can be used to improve the interpretability of data into clinically relevant information to facilitate diagnostics. A total of 25 corneal epithelium images without the application of eye staining were used. Three image feature extraction approaches were applied for image classification: (i) image feature classification from histogram using a support vector machine with a Gaussian radial basis function (SVM-GRBF); (ii) physical image feature classification using deep-learning Convolutional Neural Networks (CNNs) only; and (iii) the combined classification of CNNs and SVM-Linear. The performance results indicate that our chosen image features from the histogram and length-scale parameter were able to classify with up to 100% accuracy; particularly, at CNNs and CNNs-SVM, by employing 80% of the data sample for training and 20% for testing. Thus, in the assessment of corneal epithelium injuries, HSI has high potential as a method that could surpass current technologies regarding speed, objectivity, and reliability.

Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

PubMed

Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

2016-06-01

Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (p<0.001) compared to BCC tissue group. Histopathology indicated that these differences partially arise from BCC-related characteristic changes in tissue morphology. Wilks lambda statistics demonstrated the potential of all investigated polarimetric properties for computer assisted classification of the two tissue groups. Based on differences in polarimetric properties, partial least square (PLS) regression classified the samples with 100% accuracy, sensitivity and specificity. These findings indicate that optical polarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. All rights reserved.

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

PubMed

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

Sexing California Clapper Rails using morphological measurements

USGS Publications Warehouse

Overton, Cory T.; Casazza, Michael L.; Takekawa, John Y.; Rohmer, Tobias M.

2009-01-01

California Clapper Rails (Rallus longirostris obsoletus) have monomorphic plumage, a trait that makes identification of sex difficult without extensive behavioral observation or genetic testing. Using 31 Clapper Rails (22 females, 9 males), caught in south San Francisco Bay, CA, and using easily measurable morphological characteristics, we developed a discriminant function to distinguish sex. We then validated this function on 33 additional rails. Seven morphological measurements were considered, resulting in three which were selected in the discriminate function: culmen length, tarsometatarsus length, and flat wing length. We had no classification errors for the development or testing datasets either with resubstitution or cross-validation procedures. Male California Clapper Rails were 6-22% larger than females for individual morphological traits, and the largest difference was in body mass.  Variables in our discriminant function closely match variables developed for sexing Clapper Rails of Gulf Coast populations. However, a universal discriminant function to sex all Clapper Rail subspecies is not likely because of large and inconsistent differences in morphological traits among subspecies. 

DEPENDENCE OF MORPHOMETRIC PARAMETERS OF THE DENTAL OCCLUSION ON THE TYPE OF THE LOWER JAW GROWTH IN CHILDREN WITH CLASS II1 DENTOFACIAL ANOMALIES WHO LINE IN THE NORTHERN UKRAINE.

PubMed

Galich, L V; Kuroedova, V; Lakhtin, Yu; Galich, L B; Moskalenko, P

2017-03-01

The aim of the work was to study the structure of dentofacial anomalies in children and adolescents in Sumy city and Sumy oblast, to identify dentoalveolar morphological peculiarities of the occlusion in 10-13 years old patients with class ІІ1 anomalies according to Angle's classification with different types of lower jaw bone growth. A retrospective analysis of 2236 outpatient dental cards of urban and rural patients with orthodontic pathology was conducted. Patients were divided into three age groups: 6-9 years old (early mixed occlusion) - 592 children; 10-13 years old (late mixed occlusion) - 1180 children; over 13 years old (permanent occlusion) - 464 persons; besides 76 patients with class ІІ1 anomalies according to Angle's classification aged 10-13 years were examined. To determine the type of lower jaw growth, the children underwent orthopantomographic examination, diagnostic models were made and biometric indicators were calculated to determine the severity of the morphological changes. It was established that anomalies of individual teeth and dental curve dominated in all age groups (71.24%). Among the occlusion anomalies, a large part falls to class ІІ anomalies according to Angle's classification (19.18%). A third of these patients have a neutral type of lower jaw growth (36.84±5.53%), horizontal and vertical types of growth reach 18.42±4.47% and 19.74±4.56%, respectively. The combination of neutral and vertical type of growth of the lower jaw occurs in 1.7 times more than the combination of neutral and horizontal. The most pronounced morphological changes were observed in the group of patients with a horizontal type of lower jaw growth. When planning treatment and prophylactic measures among patients of the orthodontic profile, it is necessary to take into account the peculiarities of both the prevalence of pathology in the region and the morphological changes of different severity in the dental curves of the jaws.

Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection.

PubMed

Park, Juyoung; Kang, Mingon; Gao, Jean; Kim, Younghoon; Kang, Kyungtae

2017-01-01

Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.

The Reliability and Validity of the Thoracolumbar Injury Classification System in Pediatric Spine Trauma.

PubMed

Savage, Jason W; Moore, Timothy A; Arnold, Paul M; Thakur, Nikhil; Hsu, Wellington K; Patel, Alpesh A; McCarthy, Kathryn; Schroeder, Gregory D; Vaccaro, Alexander R; Dimar, John R; Anderson, Paul A

2015-09-15

The thoracolumbar injury classification system (TLICS) was evaluated in 20 consecutive pediatric spine trauma cases. The purpose of this study was to determine the reliability and validity of the TLICS in pediatric spine trauma. The TLICS was developed to improve the categorization and management of thoracolumbar trauma. TLICS has been shown to have good reliability and validity in the adult population. The clinical and radiographical findings of 20 pediatric thoracolumbar fractures were prospectively presented to 20 surgeons with disparate levels of training and experience with spinal trauma. These injuries were consecutively scored using the TLICS. Cohen unweighted κ coefficients and Spearman rank order correlation values were calculated for the key parameters (injury morphology, status of posterior ligamentous complex, neurological status, TLICS total score, and proposed management) to assess the inter-rater reliabilities. Five surgeons scored the same cases 3 months later to assess the intra-rater reliability. The actual management of each case was then compared with the treatment recommended by the TLICS algorithm to assess validity. The inter-rater κ statistics of all subgroups (injury morphology, status of the posterior ligamentous complex, neurological status, TLICS total score, and proposed treatment) were within the range of moderate to substantial reproducibility (0.524-0.958). All subgroups had excellent intra-rater reliability (0.748-1.000). The various indices for validity were calculated (80.3% correct, 0.836 sensitivity, 0.785 specificity, 0.676 positive predictive value, 0.899 negative predictive value). Overall, TLICS demonstrated good validity. The TLICS has good reliability and validity when used in the pediatric population. The inter-rater reliability of predicting management and indices for validity are lower than those in adults with thoracolumbar fractures, which is likely due to differences in the way children are treated for certain types of injuries. TLICS can be used to reliably categorize thoracolumbar injuries in the pediatric population; however, modifications may be needed to better guide treatment in this specific patient population. 4.

How should children with speech sound disorders be classified? A review and critical evaluation of current classification systems.

PubMed

Waring, R; Knight, R

2013-01-01

Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of theoretically differing classification systems have been proposed based on either an aetiological (medical) approach, a descriptive-linguistic approach or a processing approach. To describe and review the supporting evidence, and to provide a critical evaluation of the current childhood SSD classification systems. Descriptions of the major specific approaches to classification are reviewed and research papers supporting the reliability and validity of the systems are evaluated. Three specific paediatric SSD classification systems; the aetiologic-based Speech Disorders Classification System, the descriptive-linguistic Differential Diagnosis system, and the processing-based Psycholinguistic Framework are identified as potentially useful in classifying children with SSD into homogeneous subgroups. The Differential Diagnosis system has a growing body of empirical support from clinical population studies, across language error pattern studies and treatment efficacy studies. The Speech Disorders Classification System is currently a research tool with eight proposed subgroups. The Psycholinguistic Framework is a potential bridge to linking cause and surface level speech errors. There is a need for a universally agreed-upon classification system that is useful to clinicians and researchers. The resulting classification system needs to be robust, reliable and valid. A universal classification system would allow for improved tailoring of treatments to subgroups of SSD which may, in turn, lead to improved treatment efficacy. © 2012 Royal College of Speech and Language Therapists.

Diagnostic index of 3D osteoarthritic changes in TMJ condylar morphology

NASA Astrophysics Data System (ADS)

Gomes, Liliane R.; Gomes, Marcelo; Jung, Bryan; Paniagua, Beatriz; Ruellas, Antonio C.; Gonçalves, João. Roberto; Styner, Martin A.; Wolford, Larry; Cevidanes, Lucia

2015-03-01

The aim of this study was to investigate imaging statistical approaches for classifying 3D osteoarthritic morphological variations among 169 Temporomandibular Joint (TMJ) condyles. Cone beam Computed Tomography (CBCT) scans were acquired from 69 patients with long-term TMJ Osteoarthritis (OA) (39.1 ± 15.7 years), 15 patients at initial diagnosis of OA (44.9 ± 14.8 years) and 7 healthy controls (43 ± 12.4 years). 3D surface models of the condyles were constructed and Shape Correspondence was used to establish correspondent points on each model. The statistical framework included a multivariate analysis of covariance (MANCOVA) and Direction-Projection- Permutation (DiProPerm) for testing statistical significance of the differences between healthy control and the OA group determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering (HAC) was then conducted. Condylar morphology in OA and healthy subjects varied widely. Compared with healthy controls, OA average condyle was statistically significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis (p < 0.05). It was observed areas of 3.88 mm bone resorption at the superior surface and 3.10 mm bone apposition at the anterior aspect of the long-term OA average model. 1000 permutation statistics of DiProPerm supported a significant difference between the healthy control group and OA group (t = 6.7, empirical p-value = 0.001). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition.

Faint Blue Objects at High Galactic Latitude. VIII. Performance Characteristics of the US Survey

NASA Astrophysics Data System (ADS)

Mitchell, Kenneth J.; Usher, P. D.

2004-07-01

The US survey has cataloged 3987 objects in seven high Galactic latitude fields according to their optical colors, magnitudes, and morphologies using photographic techniques. This paper analyzes the effectiveness of the survey at producing finding lists for complete samples of hot stars and quasars that exhibit blue and/or ultraviolet excess (B-UVX) relative to the colors of halo F and G subdwarf stars. A table of 599 spectroscopic identifications summarizes the spectroscopic coverage of the US objects that has been accomplished to date. In addition, some of the survey plates have been reexamined for objects missed during the original selection, and the literature has been searched for all other spectroscopically identified blue stars and quasars with z<2.2 that have been selected by other surveys within the US survey areas. These results are used to estimate empirically both the accuracy of the US survey selection boundaries (in color, morphology, and brightness) and the completeness of the resulting samples of B-UVX US objects within those boundaries. In particular, it is shown that the reliability of the US color classifications is high and that the previously derived US morphological boundary for the complete selection of unresolved quasars is accurate. The contribution of color and morphological classification errors to B-UVX sample incompleteness is therefore correspondingly small. The empirical tests indicate high levels of completeness (95+1-2%) for the samples of US quasars and hot stars isolated within the stated survey selection limits. Errata and improvements to some of the published catalog data are presented in Appendices.

5 CFR 9701.231 - Conversion of positions and employees to the DHS classification system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the DHS classification system. 9701.231 Section 9701.231 Administrative Personnel DEPARTMENT OF... MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Transitional Provisions § 9701.231 Conversion of positions and employees to the DHS classification system. (a) This...

Sensitivity and accuracy of high-throughput metabarcoding methods used to describe aquatic communities for early detection of invasve fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize Type I and II detection errors. Given the great expense and effort associated with morphological identifi...

Overview: Pyraloidea adults (Insecta: Lepidoptera)

USDA-ARS?s Scientific Manuscript database

There are over 16,000 species of pyraloid or snout moths worldwide and many are pests of crops and stored products. The purpose of this video is twofold: to provide an overview of the current, modern classification of snout moths and to provide tools using morphology to identify adult snout moths t...

A novel summary report of colonoscopy: timeline visualization providing meaningful colonoscopy video information.

PubMed

Cho, Minwoo; Kim, Jee Hyun; Kong, Hyoun Joong; Hong, Kyoung Sup; Kim, Sungwan

2018-05-01

The colonoscopy adenoma detection rate depends largely on physician experience and skill, and overlooked colorectal adenomas could develop into cancer. This study assessed a system that detects polyps and summarizes meaningful information from colonoscopy videos. One hundred thirteen consecutive patients had colonoscopy videos prospectively recorded at the Seoul National University Hospital. Informative video frames were extracted using a MATLAB support vector machine (SVM) model and classified as bleeding, polypectomy, tool, residue, thin wrinkle, folded wrinkle, or common. Thin wrinkle, folded wrinkle, and common frames were reanalyzed using SVM for polyp detection. The SVM model was applied hierarchically for effective classification and optimization of the SVM. The mean classification accuracy according to type was over 93%; sensitivity was over 87%. The mean sensitivity for polyp detection was 82.1%, and the positive predicted value (PPV) was 39.3%. Polyps detected using the system were larger (6.3 ± 6.4 vs. 4.9 ± 2.5 mm; P = 0.003) with a more pedunculated morphology (Yamada type III, 10.2 vs. 0%; P < 0.001; Yamada type IV, 2.8 vs. 0%; P < 0.001) than polyps missed by the system. There were no statistically significant differences in polyp distribution or histology between the groups. Informative frames and suspected polyps were presented on a timeline. This summary was evaluated using the system usability scale questionnaire; 89.3% of participants expressed positive opinions. We developed and verified a system to extract meaningful information from colonoscopy videos. Although further improvement and validation of the system is needed, the proposed system is useful for physicians and patients.

Probabilisitc Geobiological Classification Using Elemental Abundance Distributions and Lossless Image Compression in Recent and Modern Organisms

NASA Technical Reports Server (NTRS)

Storrie-Lombardi, Michael C.; Hoover, Richard B.

2005-01-01

Last year we presented techniques for the detection of fossils during robotic missions to Mars using both structural and chemical signatures[Storrie-Lombardi and Hoover, 2004]. Analyses included lossless compression of photographic images to estimate the relative complexity of a putative fossil compared to the rock matrix [Corsetti and Storrie-Lombardi, 2003] and elemental abundance distributions to provide mineralogical classification of the rock matrix [Storrie-Lombardi and Fisk, 2004]. We presented a classification strategy employing two exploratory classification algorithms (Principal Component Analysis and Hierarchical Cluster Analysis) and non-linear stochastic neural network to produce a Bayesian estimate of classification accuracy. We now present an extension of our previous experiments exploring putative fossil forms morphologically resembling cyanobacteria discovered in the Orgueil meteorite. Elemental abundances (C6, N7, O8, Na11, Mg12, Ai13, Si14, P15, S16, Cl17, K19, Ca20, Fe26) obtained for both extant cyanobacteria and fossil trilobites produce signatures readily distinguishing them from meteorite targets. When compared to elemental abundance signatures for extant cyanobacteria Orgueil structures exhibit decreased abundances for C6, N7, Na11, All3, P15, Cl17, K19, Ca20 and increases in Mg12, S16, Fe26. Diatoms and silicified portions of cyanobacterial sheaths exhibiting high levels of silicon and correspondingly low levels of carbon cluster more closely with terrestrial fossils than with extant cyanobacteria. Compression indices verify that variations in random and redundant textural patterns between perceived forms and the background matrix contribute significantly to morphological visual identification. The results provide a quantitative probabilistic methodology for discriminating putatitive fossils from the surrounding rock matrix and &om extant organisms using both structural and chemical information. The techniques described appear applicable to the geobiological analysis of meteoritic samples or in situ exploration of the Mars regolith. Keywords: cyanobacteria, microfossils, Mars, elemental abundances, complexity analysis, multifactor analysis, principal component analysis, hierarchical cluster analysis, artificial neural networks, paleo-biosignatures

Viruses of haloarchaea.

PubMed

Luk, Alison W S; Williams, Timothy J; Erdmann, Susanne; Papke, R Thane; Cavicchioli, Ricardo

2014-11-13

In hypersaline environments, haloarchaea (halophilic members of the Archaea) are the dominant organisms, and the viruses that infect them, haloarchaeoviruses are at least ten times more abundant. Since their discovery in 1974, described haloarchaeoviruses include head-tailed, pleomorphic, spherical and spindle-shaped morphologies, representing Myoviridae, Siphoviridae, Podoviridae, Pleolipoviridae, Sphaerolipoviridae and Fuselloviridae families. This review overviews current knowledge of haloarchaeoviruses, providing information about classification, morphotypes, macromolecules, life cycles, genetic manipulation and gene regulation, and host-virus responses. In so doing, the review incorporates knowledge from laboratory studies of isolated viruses, field-based studies of environmental samples, and both genomic and metagenomic analyses of haloarchaeoviruses. What emerges is that some haloarchaeoviruses possess unique morphological and life cycle properties, while others share features with other viruses (e.g., bacteriophages). Their interactions with hosts influence community structure and evolution of populations that exist in hypersaline environments as diverse as seawater evaporation ponds, to hot desert or Antarctic lakes. The discoveries of their wide-ranging and important roles in the ecology and evolution of hypersaline communities serves as a strong motivator for future investigations of both laboratory-model and environmental systems.

An implementation of Elman neural network for polycystic ovary classification based on ultrasound images

NASA Astrophysics Data System (ADS)

Thufailah, I. F.; Adiwijaya; Wisesty, U. N.; Jondri

2018-03-01

Polycystic Ovary Syndrome (PCOS) is a reproduction problem that causes irregular menstruation period. Insulin and androgen hormone have big roles for this problem. This syndrome should be detected shortly, since it is able to cause a more serious disease, such as cardiovascular, diabetes, and obesity. The detection of this syndrome is done by analyzing ovary morphology and hormone test. However, the more economical way of test is by identifying the ovary morphology using ultrasonography. To classify whether one ovary is normal or it has polycystic ovary (PCO) follicle, the analysis will be done manually by a gynecologist. This paper will design a system to detect PCO using Gabor Wavelet method for feature extraction and Elman Neural Network is used to classify PCO and non-PCO. Elman Neural Network is chosen because it contains context layer to recall the previous condition. This paper compared the accuracy and process time of each dataset, then also did testing on elman’s parameters, such as layer delay, hidden layer, and training function. Based on tests done in this paper, the most accurate number is 78.1% with 32 features.

Global phylogeographic limits of Hawaii's avian malaria

USGS Publications Warehouse

Beadell, J.S.; Ishtiaq, F.; Covas, R.; Melo, M.; Warren, B.H.; Atkinson, C.T.; Bensch, S.; Graves, G.R.; Jhala, Y.V.; Peirce, M.A.; Rahmani, A.R.; Fonseca, D.M.; Fleischer, R.C.

2006-01-01

The introduction of avian malaria (Plasmodium relictum) to Hawaii has provided a model system for studying the influence of exotic disease on naive host populations. Little is known, however, about the origin or the genetic variation of Hawaii's malaria and traditional classification methods have confounded attempts to place the parasite within a global ecological and evolutionary context. Using fragments of the parasite mitochondrial gene cytochrome b and the nuclear gene dihydrofolate reductase-thymidylate synthase obtained from a global survey of greater than 13 000 avian samples, we show that Hawaii's avian malaria, which can cause high mortality and is a major limiting factor for many species of native passerines, represents just one of the numerous lineages composing the morphological parasite species. The single parasite lineage detected in Hawaii exhibits a broad host distribution worldwide and is dominant on several other remote oceanic islands, including Bermuda and Moorea, French Polynesia. The rarity of this lineage in the continental New World and the restriction of closely related lineages to the Old World suggest limitations to the transmission of reproductively isolated parasite groups within the morphological species. ?? 2006 The Royal Society.

Automated analysis and classification of melanocytic tumor on skin whole slide images.

PubMed

Xu, Hongming; Lu, Cheng; Berendt, Richard; Jha, Naresh; Mandal, Mrinal

2018-06-01

This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Pruning Neural Network Model in Credit Classification Analysis

PubMed Central

Tang, Yajiao; Ji, Junkai; Dai, Hongwei; Yu, Yang; Todo, Yuki

2018-01-01

Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs) have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN) and apply it to solve credit classification problem by adopting the well-known Australian and Japanese credit datasets. The model is inspired by synaptic nonlinearity of a dendritic tree in a biological neural model. And it is trained by an error back-propagation algorithm. The model is capable of realizing a neuronal pruning function by removing the superfluous synapses and useless dendrites and forms a tidy dendritic morphology at the end of learning. Furthermore, we utilize logic circuits (LCs) to simulate the dendritic structures successfully which makes PNN be implemented on the hardware effectively. The statistical results of our experiments have verified that PNN obtains superior performance in comparison with other classical algorithms in terms of accuracy and computational efficiency. PMID:29606961

CLASSIFYING MEDICAL IMAGES USING MORPHOLOGICAL APPEARANCE MANIFOLDS.

PubMed

Varol, Erdem; Gaonkar, Bilwaj; Davatzikos, Christos

2013-12-31

Input features for medical image classification algorithms are extracted from raw images using a series of pre processing steps. One common preprocessing step in computational neuroanatomy and functional brain mapping is the nonlinear registration of raw images to a common template space. Typically, the registration methods used are parametric and their output varies greatly with changes in parameters. Most results reported previously perform registration using a fixed parameter setting and use the results as input to the subsequent classification step. The variation in registration results due to choice of parameters thus translates to variation of performance of the classifiers that depend on the registration step for input. Analogous issues have been investigated in the computer vision literature, where image appearance varies with pose and illumination, thereby making classification vulnerable to these confounding parameters. The proposed methodology addresses this issue by sampling image appearances as registration parameters vary, and shows that better classification accuracies can be obtained this way, compared to the conventional approach.

Morphological image analysis for classification of gastrointestinal tissues using optical coherence tomography

NASA Astrophysics Data System (ADS)

Garcia-Allende, P. Beatriz; Amygdalos, Iakovos; Dhanapala, Hiruni; Goldin, Robert D.; Hanna, George B.; Elson, Daniel S.

2012-01-01

Computer-aided diagnosis of ophthalmic diseases using optical coherence tomography (OCT) relies on the extraction of thickness and size measures from the OCT images, but such defined layers are usually not observed in emerging OCT applications aimed at "optical biopsy" such as pulmonology or gastroenterology. Mathematical methods such as Principal Component Analysis (PCA) or textural analyses including both spatial textural analysis derived from the two-dimensional discrete Fourier transform (DFT) and statistical texture analysis obtained independently from center-symmetric auto-correlation (CSAC) and spatial grey-level dependency matrices (SGLDM), as well as, quantitative measurements of the attenuation coefficient have been previously proposed to overcome this problem. We recently proposed an alternative approach consisting of a region segmentation according to the intensity variation along the vertical axis and a pure statistical technology for feature quantification. OCT images were first segmented in the axial direction in an automated manner according to intensity. Afterwards, a morphological analysis of the segmented OCT images was employed for quantifying the features that served for tissue classification. In this study, a PCA processing of the extracted features is accomplished to combine their discriminative power in a lower number of dimensions. Ready discrimination of gastrointestinal surgical specimens is attained demonstrating that the approach further surpasses the algorithms previously reported and is feasible for tissue classification in the clinical setting.

Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

PubMed

Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

2017-03-01

Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

Automated noninvasive classification of renal cancer on multiphase CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linguraru, Marius George; Wang, Shijun; Shah, Furhawn

2011-10-15

Purpose: To explore the added value of the shape of renal lesions for classifying renal neoplasms. To investigate the potential of computer-aided analysis of contrast-enhanced computed-tomography (CT) to quantify and classify renal lesions. Methods: A computer-aided clinical tool based on adaptive level sets was employed to analyze 125 renal lesions from contrast-enhanced abdominal CT studies of 43 patients. There were 47 cysts and 78 neoplasms: 22 Von Hippel-Lindau (VHL), 16 Birt-Hogg-Dube (BHD), 19 hereditary papillary renal carcinomas (HPRC), and 21 hereditary leiomyomatosis and renal cell cancers (HLRCC). The technique quantified the three-dimensional size and enhancement of lesions. Intrapatient and interphasemore » registration facilitated the study of lesion serial enhancement. The histograms of curvature-related features were used to classify the lesion types. The areas under the curve (AUC) were calculated for receiver operating characteristic curves. Results: Tumors were robustly segmented with 0.80 overlap (0.98 correlation) between manual and semi-automated quantifications. The method further identified morphological discrepancies between the types of lesions. The classification based on lesion appearance, enhancement and morphology between cysts and cancers showed AUC = 0.98; for BHD + VHL (solid cancers) vs. HPRC + HLRCC AUC = 0.99; for VHL vs. BHD AUC = 0.82; and for HPRC vs. HLRCC AUC = 0.84. All semi-automated classifications were statistically significant (p < 0.05) and superior to the analyses based solely on serial enhancement. Conclusions: The computer-aided clinical tool allowed the accurate quantification of cystic, solid, and mixed renal tumors. Cancer types were classified into four categories using their shape and enhancement. Comprehensive imaging biomarkers of renal neoplasms on abdominal CT may facilitate their noninvasive classification, guide clinical management, and monitor responses to drugs or interventions.« less

How many taxa can be recognized within the complex Tillandsia capillaris (Bromeliaceae, Tillandsioideae)? Analysis of the available classifications using a multivariate approach.

PubMed

Castello, Lucía V; Galetto, Leonardo

2013-01-01

Tillandsia capillaris Ruiz & Pav., which belongs to the subgenus Diaphoranthema is distributed in Ecuador, Peru, Bolivia, northern and central Argentina, and Chile, and includes forms that are difficult to circumscribe, thus considered to form a complex. The entities of this complex are predominantly small-sized epiphytes, adapted to xeric environments. The most widely used classification defines 5 forms for this complex based on few morphological reproductive traits: Tillandsia capillaris Ruiz & Pav. f. capillaris, Tillandsia capillaris f. incana (Mez) L.B. Sm., Tillandsia capillaris f. cordobensis (Hieron.) L.B. Sm., Tillandsia capillaris f. hieronymi (Mez) L.B. Sm. and Tillandsia capillaris f. virescens (Ruiz & Pav.) L.B. Sm. In this study, 35 floral and vegetative characters were analyzed with a multivariate approach in order to assess and discuss different proposals for classification of the Tillandsia capillaris complex, which presents morphotypes that co-occur in central and northern Argentina. To accomplish this, data of quantitative and categorical morphological characters of flowers and leaves were collected from herbarium specimens and field collections and were analyzed with statistical multivariate techniques. The results suggest that the last classification for the complex seems more comprehensive and three taxa were delimited: Tillandsia capillaris (=Tillandsia capillaris f. incana-hieronymi), Tillandsia virescens s. str. (=Tillandsia capillaris f. cordobensis) and Tillandsia virescens s. l. (=Tillandsia capillaris f. virescens). While Tillandsia capillaris and Tillandsia virescens s. str. co-occur, Tillandsia virescens s. l. is restricted to altitudes above 2000 m in Argentina. Characters previously used for taxa delimitation showed continuous variation and therefore were not useful. New diagnostic characters are proposed and a key is provided for delimiting these three taxa within the complex.