Quantification of mitral valve morphology with three-dimensional echocardiography--can measurement lead to better management?

PubMed

Lee, Alex Pui-Wai; Fang, Fang; Jin, Chun-Na; Kam, Kevin Ka-Ho; Tsui, Gary K W; Wong, Kenneth K Y; Looi, Jen-Li; Wong, Randolph H L; Wan, Song; Sun, Jing Ping; Underwood, Malcolm J; Yu, Cheuk-Man

2014-01-01

The mitral valve (MV) has complex 3-dimensional (3D) morphology and motion. Advance in real-time 3D echocardiography (RT3DE) has revolutionized clinical imaging of the MV by providing clinicians with realistic visualization of the valve. Thus far, RT3DE of the MV structure and dynamics has adopted an approach that depends largely on subjective and qualitative interpretation of the 3D images of the valve, rather than objective and reproducible measurement. RT3DE combined with image-processing computer techniques provides precise segmentation and reliable quantification of the complex 3D morphology and rapid motion of the MV. This new approach to imaging may provide additional quantitative descriptions that are useful in diagnostic and therapeutic decision-making. Quantitative analysis of the MV using RT3DE has increased our understanding of the pathologic mechanism of degenerative, ischemic, functional, and rheumatic MV disease. Most recently, 3D morphologic quantification has entered into clinical use to provide more accurate diagnosis of MV disease and for planning surgery and transcatheter interventions. Current limitations of this quantitative approach to MV imaging include labor-intensiveness during image segmentation and lack of a clear definition of the clinical significance of many of the morphologic parameters. This review summarizes the current development and applications of quantitative analysis of the MV morphology using RT3DE.

Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties

PubMed Central

Nikolaisen, Julie; Nilsson, Linn I. H.; Pettersen, Ina K. N.; Willems, Peter H. G. M.; Lorens, James B.; Koopman, Werner J. H.; Tronstad, Karl J.

2014-01-01

Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D imaging and quantification are crucial for proper understanding of mitochondrial shape and topology in non-flat cells. In summary, we here present an integrative method for unbiased 3D quantification of mitochondrial shape and network properties in mammalian cells. PMID:24988307

Axial segmentation of lungs CT scan images using canny method and morphological operation

NASA Astrophysics Data System (ADS)

Noviana, Rina; Febriani, Rasal, Isram; Lubis, Eva Utari Cintamurni

2017-08-01

Segmentation is a very important topic in digital image process. It is found simply in varied fields of image analysis, particularly within the medical imaging field. Axial segmentation of lungs CT scan is beneficial in designation of abnormalities and surgery planning. It will do to ascertain every section within the lungs. The results of the segmentation are accustomed discover the presence of nodules. The method which utilized in this analysis are image cropping, image binarization, Canny edge detection and morphological operation. Image cropping is done so as to separate the lungs areas, that is the region of interest. Binarization method generates a binary image that has 2 values with grey level, that is black and white (ROI), from another space of lungs CT scan image. Canny method used for the edge detection. Morphological operation is applied to smoothing the lungs edge. The segmentation methodology shows an honest result. It obtains an awfully smooth edge. Moreover, the image background can also be removed in order to get the main focus, the lungs.

Retinal status analysis method based on feature extraction and quantitative grading in OCT images.

PubMed

Fu, Dongmei; Tong, Hejun; Zheng, Shuang; Luo, Ling; Gao, Fulin; Minar, Jiri

2016-07-22

Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.

PubMed

Wu, Shibin; Yu, Shaode; Yang, Yuhan; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

PubMed Central

Wu, Shibin; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072

Use of Proper Orthogonal Decomposition Towards Time-resolved Image Analysis of Sprays

DTIC Science & Technology

2011-03-15

High-speed movies of optically dense sprays exiting a Gas-Centered Swirl Coaxial (GCSC) injector are subjected to image analysis to determine spray...sequence prior to image analysis . Results of spray morphology including spray boundary, widths, angles and boundary oscillation frequencies, are

Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method.

PubMed

Chan, Leo Li-Ying; Kuksin, Dmitry; Laverty, Daniel J; Saldi, Stephanie; Qiu, Jean

2015-05-01

The ability to accurately determine cell viability is essential to performing a well-controlled biological experiment. Typical experiments range from standard cell culturing to advanced cell-based assays that may require cell viability measurement for downstream experiments. The traditional cell viability measurement method has been the trypan blue (TB) exclusion assay. However, since the introduction of fluorescence-based dyes for cell viability measurement using flow or image-based cytometry systems, there have been numerous publications comparing the two detection methods. Although previous studies have shown discrepancies between TB exclusion and fluorescence-based viability measurements, image-based morphological analysis was not performed in order to examine the viability discrepancies. In this work, we compared TB exclusion and fluorescence-based viability detection methods using image cytometry to observe morphological changes due to the effect of TB on dead cells. Imaging results showed that as the viability of a naturally-dying Jurkat cell sample decreased below 70 %, many TB-stained cells began to exhibit non-uniform morphological characteristics. Dead cells with these characteristics may be difficult to count under light microscopy, thus generating an artificially higher viability measurement compared to fluorescence-based method. These morphological observations can potentially explain the differences in viability measurement between the two methods.

Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens

PubMed Central

Ishikawa, Masahiro; Murakami, Yuri; Ahi, Sercan Taha; Yamaguchi, Masahiro; Kobayashi, Naoki; Kiyuna, Tomoharu; Yamashita, Yoshiko; Saito, Akira; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie

2016-01-01

Abstract. This paper proposes a digital image analysis method to support quantitative pathology by automatically segmenting the hepatocyte structure and quantifying its morphological features. To structurally analyze histopathological hepatic images, we isolate the trabeculae by extracting the sinusoids, fat droplets, and stromata. We then measure the morphological features of the extracted trabeculae, divide the image into cords, and calculate the feature values of the local cords. We propose a method of calculating the nuclear–cytoplasmic ratio, nuclear density, and number of layers using the local cords. Furthermore, we evaluate the effectiveness of the proposed method using surgical specimens. The proposed method was found to be an effective method for the quantification of the Edmondson grade. PMID:27335894

Change in Tongue Morphology in Response to Expiratory Resistance Loading Investigated by Magnetic Resonance Imaging

PubMed Central

Yanagisawa, Yukio; Matsuo, Yoshimi; Shuntoh, Hisato; Mitamura, Masaaki; Horiuchi, Noriaki

2013-01-01

[Purpose] The purpose of this study was to investigate the effect of expiratory resistance load on the tongue area encompassing the suprahyoid and genioglossus muscles. [Subjects] The subjects were 30 healthy individuals (15 males, 15 females, mean age: 28.9 years). [Methods] Magnetic resonance imaging was used to investigate morphological changes in response to resistive expiratory pressure loading in the area encompassing the suprahyoid and genioglossus muscles. Images were taken when water pressure was sustained at 0%, 10%, 30%, and 50% of maximum resistive expiratory pressure. We then measured tongue area using image analysis software, and the morphological changes were analyzed using repeated measures analysis of variance followed by post hoc comparisons. [Results] A significant change in the tongue area was detected in both sexes upon loading. Multiple comparison analysis revealed further significant differences in tongue area as well as changes in tongue area in response to the different expiratory pressures. [Conclusion] The findings demonstrate that higher expiratory pressure facilitates greater reduction in tongue area. PMID:24259824

Quantitative 3D Analysis of Nuclear Morphology and Heterochromatin Organization from Whole-Mount Plant Tissue Using NucleusJ.

PubMed

Desset, Sophie; Poulet, Axel; Tatout, Christophe

2018-01-01

Image analysis is a classical way to study nuclear organization. While nuclear organization used to be investigated by colorimetric or fluorescent labeling of DNA or specific nuclear compartments, new methods in microscopy imaging now enable qualitative and quantitative analyses of chromatin pattern, and nuclear size and shape. Several procedures have been developed to prepare samples in order to collect 3D images for the analysis of spatial chromatin organization, but only few preserve the positional information of the cell within its tissue context. Here, we describe a whole mount tissue preparation procedure coupled to DNA staining using the PicoGreen ® intercalating agent suitable for image analysis of the nucleus in living and fixed tissues. 3D Image analysis is then performed using NucleusJ, an open source ImageJ plugin, which allows for quantifying variations in nuclear morphology such as nuclear volume, sphericity, elongation, and flatness as well as in heterochromatin content and position in respect to the nuclear periphery.

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Image Analysis, Microscopic, and Spectrochemical Study of the PVC Dry Blending Process,

DTIC Science & Technology

The dry blending process used in the production of electrical grade pvc formulations has been studies using a combination of image analysis , microscopic...by image analysis techniques. Optical and scanning electron microscopy were used to assess morphological differences. Spectrochemical techniques were used to indicate chemical changes.

Computer analysis of three-dimensional morphological characteristics of the bile duct

NASA Astrophysics Data System (ADS)

Ma, Jinyuan; Chen, Houjin; Peng, Yahui; Shang, Hua

2017-01-01

In this paper, a computer image-processing algorithm for analyzing the morphological characteristics of bile ducts in Magnetic Resonance Cholangiopancreatography (MRCP) images was proposed. The algorithm consisted of mathematical morphology methods including erosion, closing and skeletonization, and a spline curve fitting method to obtain the length and curvature of the center line of the bile duct. Of 10 cases, the average length of the bile duct was 14.56 cm. The maximum curvature was in the range of 0.111 2.339. These experimental results show that using the computer image-processing algorithm to assess the morphological characteristics of the bile duct is feasible and further research is needed to evaluate its potential clinical values.

Bubble structure evaluation method of sponge cake by using image morphology

NASA Astrophysics Data System (ADS)

Kato, Kunihito; Yamamoto, Kazuhiko; Nonaka, Masahiko; Katsuta, Yukiyo; Kasamatsu, Chinatsu

2007-01-01

Nowadays, many evaluation methods for food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that have been used for the quality evaluation recently. The goal of our research is structure evaluation of sponge cake by using the image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner, because the depth of field of this type scanner is very shallow. Therefore the bubble region of the surface has low gray scale value, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. The input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

[The application of stereology in radiology imaging and cell biology fields].

PubMed

Hu, Na; Wang, Yan; Feng, Yuanming; Lin, Wang

2012-08-01

Stereology is an interdisciplinary method for 3D morphological study developed from mathematics and morphology. It is widely used in medical image analysis and cell biology studies. Because of its unbiased, simple, fast, reliable and non-invasive characteristics, stereology has been widely used in biomedical areas for quantitative analysis and statistics, such as histology, pathology and medical imaging. Because the stereological parameters show distinct differences in different pathology, many scholars use stereological methods to do quantitative analysis in their studies in recent years, for example, in the areas of the condition of cancer cells, tumor grade, disease development and the patient's prognosis, etc. This paper describes the stereological concept and estimation methods, also illustrates the applications of stereology in the fields of CT images, MRI images and cell biology, and finally reflects the universality, the superiority and reliability of stereology.

Converging evidence for abnormalities of the prefrontal cortex and evaluation of midsagittal structures in pediatric PTSD: an MRI study

PubMed Central

Carrion, Victor G.; Weems, Carl F.; Watson, Christa; Eliez, Stephan; Menon, Vinod; Reiss, Allan L.

2009-01-01

Objective Volumetric imaging research has shown abnormal brain morphology in posttraumatic stress disorder (PTSD) when compared to controls. We present results on a study of brain morphology in the prefrontal cortex (PFC) and midline structures, via indices of gray matter volume and density, in pediatric PTSD. We hypothesized that both methods would demonstrate aberrant morphology in the PFC. Further, we hypothesized aberrant brainstem anatomy and reduced corpus collosum volume in children with PTSD. Methods Twenty-four children (aged 7-14) with history of interpersonal trauma and 24 age, and gender matched controls underwent structural magnetic resonance imaging. Images of the PFC and midline brain structures were first analyzed using volumetric image analysis. The PFC data were then compared with whole-brain voxel-based techniques using statistical parametric mapping (SPM). Results The PTSD group showed significant increased gray matter volume in the right and left inferior and superior quadrants of the prefrontal cortex and smaller gray matter volume in pons, and posterior vermis areas by volumetric image analysis. The voxel-byvoxel group comparisons demonstrated increased gray matter density mostly localized to ventral PFC as compared to the control group. Conclusions Abnormal frontal lobe morphology, as revealed by separate-complementary image analysis methods, and reduced pons and posterior vermis areas are associated with pediatric PTSD. Voxel-based morphometry may help to corroborate and further localize data obtained by volume of interest methods in PTSD. PMID:19349151

Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing

NASA Astrophysics Data System (ADS)

Tatebe, Hironobu; Kato, Kunihito; Yamamoto, Kazuhiko; Katsuta, Yukio; Nonaka, Masahiko

2005-12-01

Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

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.

Comparison Through Image Analysis Between Al Foams Produced Using Two Different Methods

NASA Astrophysics Data System (ADS)

Boschetto, A.; Campana, F.; Pilone, D.

2014-02-01

Several methods are available for making metal foams. They allow to tailor their mechanical, thermal, acoustic, and electrical properties for specific applications by varying the relative density as well as the cell size and morphology. Foams have a very heterogeneous structure so that their properties may show a large scatter. In this paper, an aluminum foam produced by means of foaming of powder compacts and another one prepared via the infiltration process were analyzed and compared. Image analysis has been used as a useful tool to determine size, morphology, and distribution of cells in both foams and to correlate cell morphology with the considered manufacturing process. The results highlighted that cell size and morphology are strictly dependent upon the manufacturing method. This paper shows how some standard 2D morphological indicators may be usefully adopted to characterize foams whose structure derives from the specific manufacturing process.

Geologic map of Mars

USGS Publications Warehouse

Tanaka, Kenneth L.; Skinner, James A.; Dohm, James M.; Irwin, Rossman P.; Kolb, Eric J.; Fortezzo, Corey M.; Platz, Thomas; Michael, Gregory G.; Hare, Trent M.

2014-01-01

This global geologic map of Mars, which records the distribution of geologic units and landforms on the planet's surface through time, is based on unprecedented variety, quality, and quantity of remotely sensed data acquired since the Viking Orbiters. These data have provided morphologic, topographic, spectral, thermophysical, radar sounding, and other observations for integration, analysis, and interpretation in support of geologic mapping. In particular, the precise topographic mapping now available has enabled consistent morphologic portrayal of the surface for global mapping (whereas previously used visual-range image bases were less effective, because they combined morphologic and albedo information and, locally, atmospheric haze). Also, thermal infrared image bases used for this map tended to be less affected by atmospheric haze and thus are reliable for analysis of surface morphology and texture at even higher resolution than the topographic products.

A comparison of 3D poly(ε-caprolactone) tissue engineering scaffolds produced with conventional and additive manufacturing techniques by means of quantitative analysis of SR μ-CT images

NASA Astrophysics Data System (ADS)

Brun, F.; Intranuovo, F.; Mohammadi, S.; Domingos, M.; Favia, P.; Tromba, G.

2013-07-01

The technique used to produce a 3D tissue engineering (TE) scaffold is of fundamental importance in order to guarantee its proper morphological characteristics. An accurate assessment of the resulting structural properties is therefore crucial in order to evaluate the effectiveness of the produced scaffold. Synchrotron radiation (SR) computed microtomography (μ-CT) combined with further image analysis seems to be one of the most effective techniques to this aim. However, a quantitative assessment of the morphological parameters directly from the reconstructed images is a non trivial task. This study considers two different poly(ε-caprolactone) (PCL) scaffolds fabricated with a conventional technique (Solvent Casting Particulate Leaching, SCPL) and an additive manufacturing (AM) technique (BioCell Printing), respectively. With the first technique it is possible to produce scaffolds with random, non-regular, rounded pore geometry. The AM technique instead is able to produce scaffolds with square-shaped interconnected pores of regular dimension. Therefore, the final morphology of the AM scaffolds can be predicted and the resulting model can be used for the validation of the applied imaging and image analysis protocols. It is here reported a SR μ-CT image analysis approach that is able to effectively and accurately reveal the differences in the pore- and throat-size distributions as well as connectivity of both AM and SCPL scaffolds.

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

PubMed

Downie, H F; Adu, M O; Schmidt, S; Otten, W; Dupuy, L X; White, P J; Valentine, T A

2015-07-01

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions. © 2014 John Wiley & Sons Ltd.

Comparison of morphological and conventional edge detectors in medical imaging applications

NASA Astrophysics Data System (ADS)

Kaabi, Lotfi; Loloyan, Mansur; Huang, H. K.

1991-06-01

Recently, mathematical morphology has been used to develop efficient image analysis tools. This paper compares the performance of morphological and conventional edge detectors applied to radiological images. Two morphological edge detectors including the dilation residue found by subtracting the original signal from its dilation by a small structuring element, and the blur-minimization edge detector which is defined as the minimum of erosion and dilation residues of the blurred image version, are compared with the linear Laplacian and Sobel and the non-linear Robert edge detectors. Various structuring elements were used in this study: regular 2-dimensional, and 3-dimensional. We utilized two criterions for edge detector's performance classification: edge point connectivity and the sensitivity to the noise. CT/MR and chest radiograph images have been used as test data. Comparison results show that the blur-minimization edge detector, with a rolling ball-like structuring element outperforms other standard linear and nonlinear edge detectors. It is less noise sensitive, and performs the most closed contours.

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

Study of morphological changes in scattering and optically anisotropic medium through correlation images

NASA Astrophysics Data System (ADS)

Jain, Neha; Shukla, Prashant; Singh, Jai

2018-05-01

Correlation images are very useful in determining the morphological changes. We have investigated the correlation image analysis on depolarization and retardance matrices of polystyrene and gelatine samples respectively. We observed that that correlation images have a potential to show a significant variation with change in the concentration of samples (polystyrene and gelatine). For polystyrene microspheres the correlation value decreases with increasing scattering coefficient. In gelatine samples the correlation also decreases with sample concentration. This variation in correlation for retardance shows the change in a birefringence property of gelatine solution.

New approaches for the analysis of confluent cell layers with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Pohl, L.; Kaiser, M.; Ketelhut, S.; Pereira, S.; Goycoolea, F.; Kemper, Björn

2016-03-01

Digital holographic microscopy (DHM) enables high resolution non-destructive inspection of technical surfaces and minimally-invasive label-free live cell imaging. However, the analysis of confluent cell layers represents a challenge as quantitative DHM phase images in this case do not provide sufficient information for image segmentation, determination of the cellular dry mass or calculation of the cell thickness. We present novel strategies for the analysis of confluent cell layers with quantitative DHM phase contrast utilizing a histogram based-evaluation procedure. The applicability of our approach is illustrated by quantification of drug induced cell morphology changes and it is shown that the method is capable to quantify reliable global morphology changes of confluent cell layers.

Utility of fluorescence microscopy in embryonic/fetal topographical analysis.

PubMed

Zucker, R M; Elstein, K H; Shuey, D L; Ebron-McCoy, M; Rogers, J M

1995-06-01

For topographical analysis of developing embryos, investigators typically rely on scanning electron microscopy (SEM) to provide the surface detail not attainable with light microscopy. SEM is an expensive and time-consuming technique, however, and the preparation procedure may alter morphology and leave the specimen friable. We report that by using a high-resolution compound epifluorescence microscope with inexpensive low-power objectives and the fluorochrome acridine orange, we were able to obtain surface images of fixed or fresh whole rat embryos and fetal palates of considerably greater topographical detail than those obtained using routine light microscopy. Indeed the resulting high-resolution images afford not only superior qualitative documentation of morphological observations, but the capability for detailed morphometry via digitization and computer-assisted image analysis.

Application of morphological synthesis for understanding electrode microstructure evolution as a function of applied charge/discharge cycles

DOE PAGES

Glazoff, Michael V.; Dufek, Eric J.; Shalashnikov, Egor V.

2016-09-15

Morphological analysis and synthesis operations were employed for analysis of electrode microstructure transformations and evolution accompanying the application of charge/discharge cycles to electrochemical storage systems (batteries). Using state-of-the-art morphological algorithms, it was possible to predict microstructure evolution in porous Si electrodes for Li-ion batteries with sufficient accuracy. Algorithms for image analyses (segmentation, feature extraction, and 3D-reconstructions using 2D-images) were also developed. Altogether, these techniques could be considered supplementary to phase-field mesoscopic approach to microstructure evolution that is based upon clear and definitive changes in the appearance of microstructure. However, unlike in phase-field, the governing equations for morphological approach are geometry-,more » not physics-based. Similar non-physics based approach to understanding different phenomena was attempted with the introduction of cellular automata. It is anticipated that morphological synthesis and analysis will represent a useful supplementary tool to phase-field and will render assistance to unraveling the underlying microstructure-property relationships. The paper contains data on electrochemical characterization of different electrode materials that was conducted in parallel to morphological study.« less

Development of a diffraction imaging flow cytometer

PubMed Central

Jacobs, Kenneth M.; Lu, Jun Q.

2013-01-01

Diffraction images record angle-resolved distribution of scattered light from a particle excited by coherent light and can correlate highly with the 3D morphology of a particle. We present a jet-in-fluid design of flow chamber for acquisition of clear diffraction images in a laminar flow. Diffraction images of polystyrene spheres of different diameters were acquired and found to correlate highly with the calculated ones based on the Mie theory. Fast Fourier transform analysis indicated that the measured images can be used to extract sphere diameter values. These results demonstrate the significant potentials of high-throughput diffraction imaging flow cytometry for extracting 3D morphological features of cells. PMID:19794790

Correlation mapping: rapid method for retrieving microcirculation morphology from optical coherence tomography intensity images

NASA Astrophysics Data System (ADS)

Jonathan, E.; Enfield, J.; Leahy, M. J.

2011-03-01

The microcirculation plays a critical role is maintaining organ health and function by serving as a vascular are where trophic metabolism exchanges between blood and tissue takes place. To facilitate regular assessment in vivo, noninvasive microcirculation imagers are required in clinics. Among this group of clinical devices, are those that render microcirculation morphology such as nailfold capillaroscopy, a common device for early diagnosis and monitoring of microangiopathies. However, depth ambiguity disqualify this and other similar techniques in medical tomography where due to the 3-D nature of biological organs, imagers that support depth-resolved 2-D imaging and 3-D image reconstruction are required. Here, we introduce correlation map OCT (cmOCT), a promising technique for microcirculation morphology imaging that combines standard optical coherence tomography and an agile imaging analysis software based on correlation statistic. Promising results are presented of the microcirculation morphology images of the brain region of a small animal model as well as measurements of vessel geometry at bifurcations, such as vessel diameters, branch angles. These data will be useful for obtaining cardiovascular related characteristics such as volumetric flow, velocity profile and vessel-wall shear stress for circulatory and respiratory system.

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.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

PubMed

Kai, Chiharu; Uchiyama, Yoshikazu; Shiraishi, Junji; Fujita, Hiroshi; Doi, Kunio

2018-05-10

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes. First, statistical parametric mapping (SPM) 12 was used for three-dimensional anatomical standardization of the brain MR images. A total of 30 normal images were used to create a standard normal brain image. Z-score maps were generated to identify the differences between an abnormal image and the standard normal brain. Our experimental results revealed that cerebral atrophies, depending on genotypes, can occur in different locations and that morphological changes may differ between MCI and AD. Using a classifier to characterize cerebral atrophies related to an individual's genotype, we developed a computer-aided diagnosis (CAD) scheme to identify the disease. For the early detection of cerebral diseases, a screening system using MR images, called Brain Check-up, is widely performed in Japan. Therefore, our proposed CAD scheme would be used in Brain Check-up.

Computer-assisted adjuncts for aneurysmal morphologic assessment: toward more precise and accurate approaches

NASA Astrophysics Data System (ADS)

Rajabzadeh-Oghaz, Hamidreza; Varble, Nicole; Davies, Jason M.; Mowla, Ashkan; Shakir, Hakeem J.; Sonig, Ashish; Shallwani, Hussain; Snyder, Kenneth V.; Levy, Elad I.; Siddiqui, Adnan H.; Meng, Hui

2017-03-01

Neurosurgeons currently base most of their treatment decisions for intracranial aneurysms (IAs) on morphological measurements made manually from 2D angiographic images. These measurements tend to be inaccurate because 2D measurements cannot capture the complex geometry of IAs and because manual measurements are variable depending on the clinician's experience and opinion. Incorrect morphological measurements may lead to inappropriate treatment strategies. In order to improve the accuracy and consistency of morphological analysis of IAs, we have developed an image-based computational tool, AView. In this study, we quantified the accuracy of computer-assisted adjuncts of AView for aneurysmal morphologic assessment by performing measurement on spheres of known size and anatomical IA models. AView has an average morphological error of 0.56% in size and 2.1% in volume measurement. We also investigate the clinical utility of this tool on a retrospective clinical dataset and compare size and neck diameter measurement between 2D manual and 3D computer-assisted measurement. The average error was 22% and 30% in the manual measurement of size and aneurysm neck diameter, respectively. Inaccuracies due to manual measurements could therefore lead to wrong treatment decisions in 44% and inappropriate treatment strategies in 33% of the IAs. Furthermore, computer-assisted analysis of IAs improves the consistency in measurement among clinicians by 62% in size and 82% in neck diameter measurement. We conclude that AView dramatically improves accuracy for morphological analysis. These results illustrate the necessity of a computer-assisted approach for the morphological analysis of IAs.

An automated image analysis framework for segmentation and division plane detection of single live Staphylococcus aureus cells which can operate at millisecond sampling time scales using bespoke Slimfield microscopy

NASA Astrophysics Data System (ADS)

Wollman, Adam J. M.; Miller, Helen; Foster, Simon; Leake, Mark C.

2016-10-01

Staphylococcus aureus is an important pathogen, giving rise to antimicrobial resistance in cell strains such as Methicillin Resistant S. aureus (MRSA). Here we report an image analysis framework for automated detection and image segmentation of cells in S. aureus cell clusters, and explicit identification of their cell division planes. We use a new combination of several existing analytical tools of image analysis to detect cellular and subcellular morphological features relevant to cell division from millisecond time scale sampled images of live pathogens at a detection precision of single molecules. We demonstrate this approach using a fluorescent reporter GFP fused to the protein EzrA that localises to a mid-cell plane during division and is involved in regulation of cell size and division. This image analysis framework presents a valuable platform from which to study candidate new antimicrobials which target the cell division machinery, but may also have more general application in detecting morphologically complex structures of fluorescently labelled proteins present in clusters of other types of cells.

3D/4D multiscale imaging in acute lymphoblastic leukemia cells: visualizing dynamics of cell death

NASA Astrophysics Data System (ADS)

Sarangapani, Sreelatha; Mohan, Rosmin Elsa; Patil, Ajeetkumar; Lang, Matthew J.; Asundi, Anand

2017-06-01

Quantitative phase detection is a new methodology that provides quantitative information on cellular morphology to monitor the cell status, drug response and toxicity. In this paper the morphological changes in acute leukemia cells treated with chitosan were detected using d'Bioimager a robust imaging system. Quantitative phase image of the cells was obtained with numerical analysis. Results show that the average area and optical volume of the chitosan treated cells is significantly reduced when compared with the control cells, which reveals the effect of chitosan on the cancer cells. From the results it can be attributed that d'Bioimager can be used as a non-invasive imaging alternative to measure the morphological changes of the living cells in real time.

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.

Method for evaluation of human induced pluripotent stem cell quality using image analysis based on the biological morphology of cells.

PubMed

Wakui, Takashi; Matsumoto, Tsuyoshi; Matsubara, Kenta; Kawasaki, Tomoyuki; Yamaguchi, Hiroshi; Akutsu, Hidenori

2017-10-01

We propose an image analysis method for quality evaluation of human pluripotent stem cells based on biologically interpretable features. It is important to maintain the undifferentiated state of induced pluripotent stem cells (iPSCs) while culturing the cells during propagation. Cell culture experts visually select good quality cells exhibiting the morphological features characteristic of undifferentiated cells. Experts have empirically determined that these features comprise prominent and abundant nucleoli, less intercellular spacing, and fewer differentiating cellular nuclei. We quantified these features based on experts' visual inspection of phase contrast images of iPSCs and found that these features are effective for evaluating iPSC quality. We then developed an iPSC quality evaluation method using an image analysis technique. The method allowed accurate classification, equivalent to visual inspection by experts, of three iPSC cell lines.

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

PubMed Central

Kurihara, Daisuke; Mizuta, Yoko; Sato, Yoshikatsu; Higashiyama, Tetsuya

2015-01-01

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research. PMID:26493404

Morphological analysis of oligomeric vs. fibrillar forms of α-synuclein aggregates with super-resolution BALM imaging

NASA Astrophysics Data System (ADS)

Huh, Hyun; Lee, Jinwoo; Kim, Hyung Jun; Hohng, Sungchul; Kim, Seong Keun

2017-12-01

Application of BALM (binding activated localization microcopy) was shown to allow facile imaging of amyloid fibrils with a typical diameter of ∼14 nm FWHM. We also observed a twisted ribbon-like substructure of mutant amyloid fibrils and even what appear to be toxic amyloid oligomers with their characteristic morphological features consistent with TEM images. Use of an easily available staining dye in this method greatly enhances the prospect of addressing amyloid-related diseases in their diagnosis and drug tests by allowing facile in situ and in vivo detection by optical imaging.

VESGEN Software for Mapping and Quantification of Vascular Regulators

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia A.; Vickerman, Mary B.; Keith, Patricia A.

2012-01-01

VESsel GENeration (VESGEN) Analysis is an automated software that maps and quantifies effects of vascular regulators on vascular morphology by analyzing important vessel parameters. Quantification parameters include vessel diameter, length, branch points, density, and fractal dimension. For vascular trees, measurements are reported as dependent functions of vessel branching generation. VESGEN maps and quantifies vascular morphological events according to fractal-based vascular branching generation. It also relies on careful imaging of branching and networked vascular form. It was developed as a plug-in for ImageJ (National Institutes of Health, USA). VESGEN uses image-processing concepts of 8-neighbor pixel connectivity, skeleton, and distance map to analyze 2D, black-and-white (binary) images of vascular trees, networks, and tree-network composites. VESGEN maps typically 5 to 12 (or more) generations of vascular branching, starting from a single parent vessel. These generations are tracked and measured for critical vascular parameters that include vessel diameter, length, density and number, and tortuosity per branching generation. The effects of vascular therapeutics and regulators on vascular morphology and branching tested in human clinical or laboratory animal experimental studies are quantified by comparing vascular parameters with control groups. VESGEN provides a user interface to both guide and allow control over the users vascular analysis process. An option is provided to select a morphological tissue type of vascular trees, network or tree-network composites, which determines the general collections of algorithms, intermediate images, and output images and measurements that will be produced.

Determination of mango fruit from binary image using randomized Hough transform

NASA Astrophysics Data System (ADS)

Rizon, Mohamed; Najihah Yusri, Nurul Ain; Abdul Kadir, Mohd Fadzil; bin Mamat, Abd. Rasid; Abd Aziz, Azim Zaliha; Nanaa, Kutiba

2015-12-01

A method of detecting mango fruit from RGB input image is proposed in this research. From the input image, the image is processed to obtain the binary image using the texture analysis and morphological operations (dilation and erosion). Later, the Randomized Hough Transform (RHT) method is used to find the best ellipse fits to each binary region. By using the texture analysis, the system can detect the mango fruit that is partially overlapped with each other and mango fruit that is partially occluded by the leaves. The combination of texture analysis and morphological operator can isolate the partially overlapped fruit and fruit that are partially occluded by leaves. The parameters derived from RHT method was used to calculate the center of the ellipse. The center of the ellipse acts as the gripping point for the fruit picking robot. As the results, the rate of detection was up to 95% for fruit that is partially overlapped and partially covered by leaves.

Spermatozoa quality assessment: a combined holographic and Raman microscopy approach

NASA Astrophysics Data System (ADS)

De Angelis, Annalisa; Ferrara, Maria A.; Di Caprio, Giuseppe; Managò, Stefano; Sirleto, Luigi; Coppola, Giuseppe; De Luca, Anna Chiara

2015-05-01

Semen analysis is widely used as diagnostic tool for assessing male fertility, controlling and managing the animal reproduction. The most important parameters measured in a semen analysis are the morphology and biochemical alterations. For obtaining such information, non-invasive, label-free and non-destructive techniques have to be used. Digital Holography (DH) combined with Raman Spectroscopy (RS) could represent the perfect candidate for a rapid, non-destructive and high-sensitive morphological and biochemical sperm cell analysis. In this study, DH-RS combined approach is used for a complete analysis of single bovine spermatozoa. High-resolution images of bovine sperm have been obtained by DH microscopy from the reconstruction of a single acquired hologram, highlighting in some cases morphological alterations. Quantitative 3D reconstructions of sperm head, both normal and anomalous, have been studied and an unexpected structure of the post-acrosomal region of the head has been detected. Such anomalies have been also confirmed by Raman imaging analysis, suggesting the protein vibrations as associated Raman marker of the defect.

Quantifying Morphological Features of α-U3O8 with Image Analysis for Nuclear Forensics.

PubMed

Olsen, Adam M; Richards, Bryony; Schwerdt, Ian; Heffernan, Sean; Lusk, Robert; Smith, Braxton; Jurrus, Elizabeth; Ruggiero, Christy; McDonald, Luther W

2017-03-07

Morphological changes in U 3 O 8 based on calcination temperature have been quantified enabling a morphological feature to serve as a signature of processing history in nuclear forensics. Five separate calcination temperatures were used to synthesize α-U 3 O 8 , and each sample was characterized using powder X-ray diffraction (p-XRD) and scanning electron microscopy (SEM). The p-XRD spectra were used to evaluate the purity of the synthesized U-oxide; the morphological analysis for materials (MAMA) software was utilized to quantitatively characterize the particle shape and size as indicated by the SEM images. Analysis comparing the particle attributes, such as particle area at each of the temperatures, was completed using the Kolmogorov-Smirnov two sample test (K-S test). These results illustrate a distinct statistical difference between each calcination temperature. To provide a framework for forensic analysis of an unknown sample, the sample distributions at each temperature were compared to randomly selected distributions (100, 250, 500, and 750 particles) from each synthesized temperature to determine if they were statistically different. It was found that 750 particles were required to differentiate between all of the synthesized temperatures with a confidence interval of 99.0%. Results from this study provide the first quantitative morphological study of U-oxides, and reveals the potential strength of morphological particle analysis in nuclear forensics by providing a framework for a more rapid characterization of interdicted uranium oxide samples.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay

PubMed Central

Bray, Mark-Anthony; Gustafsdottir, Sigrun M; Rohban, Mohammad H; Singh, Shantanu; Ljosa, Vebjorn; Sokolnicki, Katherine L; Bittker, Joshua A; Bodycombe, Nicole E; Dančík, Vlado; Hasaka, Thomas P; Hon, Cindy S; Kemp, Melissa M; Li, Kejie; Walpita, Deepika; Wawer, Mathias J; Golub, Todd R; Schreiber, Stuart L; Clemons, Paul A; Shamji, Alykhan F

2017-01-01

Abstract Background Large-scale image sets acquired by automated microscopy of perturbed samples enable a detailed comparison of cell states induced by each perturbation, such as a small molecule from a diverse library. Highly multiplexed measurements of cellular morphology can be extracted from each image and subsequently mined for a number of applications. Findings This microscopy dataset includes 919 265 five-channel fields of view, representing 30 616 tested compounds, available at “The Cell Image Library” (CIL) repository. It also includes data files containing morphological features derived from each cell in each image, both at the single-cell level and population-averaged (i.e., per-well) level; the image analysis workflows that generated the morphological features are also provided. Quality-control metrics are provided as metadata, indicating fields of view that are out-of-focus or containing highly fluorescent material or debris. Lastly, chemical annotations are supplied for the compound treatments applied. Conclusions Because computational algorithms and methods for handling single-cell morphological measurements are not yet routine, the dataset serves as a useful resource for the wider scientific community applying morphological (image-based) profiling. The dataset can be mined for many purposes, including small-molecule library enrichment and chemical mechanism-of-action studies, such as target identification. Integration with genetically perturbed datasets could enable identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future therapeutics. PMID:28327978

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%.

Optimizing morphology through blood cell image analysis.

PubMed

Merino, A; Puigví, L; Boldú, L; Alférez, S; Rodellar, J

2018-05-01

Morphological review of the peripheral blood smear is still a crucial diagnostic aid as it provides relevant information related to the diagnosis and is important for selection of additional techniques. Nevertheless, the distinctive cytological characteristics of the blood cells are subjective and influenced by the reviewer's interpretation and, because of that, translating subjective morphological examination into objective parameters is a challenge. The use of digital microscopy systems has been extended in the clinical laboratories. As automatic analyzers have some limitations for abnormal or neoplastic cell detection, it is interesting to identify quantitative features through digital image analysis for morphological characteristics of different cells. Three main classes of features are used as follows: geometric, color, and texture. Geometric parameters (nucleus/cytoplasmic ratio, cellular area, nucleus perimeter, cytoplasmic profile, RBC proximity, and others) are familiar to pathologists, as they are related to the visual cell patterns. Different color spaces can be used to investigate the rich amount of information that color may offer to describe abnormal lymphoid or blast cells. Texture is related to spatial patterns of color or intensities, which can be visually detected and quantitatively represented using statistical tools. This study reviews current and new quantitative features, which can contribute to optimize morphology through blood cell digital image processing techniques. © 2018 John Wiley & Sons Ltd.

Automated Dermoscopy Image Analysis of Pigmented Skin Lesions

PubMed Central

Baldi, Alfonso; Quartulli, Marco; Murace, Raffaele; Dragonetti, Emanuele; Manganaro, Mario; Guerra, Oscar; Bizzi, Stefano

2010-01-01

Dermoscopy (dermatoscopy, epiluminescence microscopy) is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions (PSLs), allowing a better visualization of surface and subsurface structures (from the epidermis to the papillary dermis). This diagnostic tool permits the recognition of morphologic structures not visible by the naked eye, thus opening a new dimension in the analysis of the clinical morphologic features of PSLs. In order to reduce the learning-curve of non-expert clinicians and to mitigate problems inherent in the reliability and reproducibility of the diagnostic criteria used in pattern analysis, several indicative methods based on diagnostic algorithms have been introduced in the last few years. Recently, numerous systems designed to provide computer-aided analysis of digital images obtained by dermoscopy have been reported in the literature. The goal of this article is to review these systems, focusing on the most recent approaches based on content-based image retrieval systems (CBIR). PMID:24281070

Identification Male Fertility Through Abnormalities Sperm Based Morphology (Teratospermia) using Invariant Moment Method

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Chairani, R.; Seniman; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Erliana, C. I.; Andayani, U.

2018-03-01

Sperm morphology is still a standard laboratory analysis in diagnosing infertility in men. Manually identification of sperm form is still not accurate, the difficulty in seeing the form of the invisible sperm from the digital microscope image is often a weakness in the process of identification and takes a long time. Therefore, male fertility identification application system is needed Through sperm abnormalities based on sperm morphology (teratospermia). The method used is invariant moment method. This study uses 15 data testing and 20 data training sperm image. That the process of male fertility identification through sperm abnormalities based on sperm morphology (teratospermia) has an accuracy rate of 80.77%. Use of time to process Identification of male fertility through sperm abnormalities Based on sperm morphology (teratospermia) during 0.4369 seconds.

Uncertainty in the use of MAMA software to measure particle morphological parameters from SEM images

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

Schwartz, Daniel S.; Tandon, Lav

The MAMA software package developed at LANL is designed to make morphological measurements on a wide variety of digital images of objects. At LANL, we have focused on using MAMA to measure scanning electron microscope (SEM) images of particles, as this is a critical part of our forensic analysis of interdicted radiologic materials. In order to successfully use MAMA to make such measurements, we must understand the level of uncertainty involved in the process, so that we can rigorously support our quantitative conclusions.

An image analysis toolbox for high-throughput C. elegans assays

PubMed Central

Wählby, Carolina; Kamentsky, Lee; Liu, Zihan H.; Riklin-Raviv, Tammy; Conery, Annie L.; O’Rourke, Eyleen J.; Sokolnicki, Katherine L.; Visvikis, Orane; Ljosa, Vebjorn; Irazoqui, Javier E.; Golland, Polina; Ruvkun, Gary; Ausubel, Frederick M.; Carpenter, Anne E.

2012-01-01

We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems. This WormToolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays of C. elegans for the study of diverse biological pathways relevant to human disease. PMID:22522656

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.

Real-time hyperspectral imaging for food safety applications

USDA-ARS?s Scientific Manuscript database

Multispectral imaging systems with selected bands can commonly be used for real-time applications of food processing. Recent research has demonstrated several image processing methods including binning, noise removal filter, and appropriate morphological analysis in real-time mode can remove most fa...

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.

DeepNeuron: an open deep learning toolbox for neuron tracing.

PubMed

Zhou, Zhi; Kuo, Hsien-Chi; Peng, Hanchuan; Long, Fuhui

2018-06-06

Reconstructing three-dimensional (3D) morphology of neurons is essential for understanding brain structures and functions. Over the past decades, a number of neuron tracing tools including manual, semiautomatic, and fully automatic approaches have been developed to extract and analyze 3D neuronal structures. Nevertheless, most of them were developed based on coding certain rules to extract and connect structural components of a neuron, showing limited performance on complicated neuron morphology. Recently, deep learning outperforms many other machine learning methods in a wide range of image analysis and computer vision tasks. Here we developed a new Open Source toolbox, DeepNeuron, which uses deep learning networks to learn features and rules from data and trace neuron morphology in light microscopy images. DeepNeuron provides a family of modules to solve basic yet challenging problems in neuron tracing. These problems include but not limited to: (1) detecting neuron signal under different image conditions, (2) connecting neuronal signals into tree(s), (3) pruning and refining tree morphology, (4) quantifying the quality of morphology, and (5) classifying dendrites and axons in real time. We have tested DeepNeuron using light microscopy images including bright-field and confocal images of human and mouse brain, on which DeepNeuron demonstrates robustness and accuracy in neuron tracing.

Realization of the FPGA-based reconfigurable computing environment by the example of morphological processing of a grayscale image

NASA Astrophysics Data System (ADS)

Shatravin, V.; Shashev, D. V.

2018-05-01

Currently, robots are increasingly being used in every industry. One of the most high-tech areas is creation of completely autonomous robotic devices including vehicles. The results of various global research prove the efficiency of vision systems in autonomous robotic devices. However, the use of these systems is limited because of the computational and energy resources available in the robot device. The paper describes the results of applying the original approach for image processing on reconfigurable computing environments by the example of morphological operations over grayscale images. This approach is prospective for realizing complex image processing algorithms and real-time image analysis in autonomous robotic devices.

Theoretical foundations of spatially-variant mathematical morphology part ii: gray-level images.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2008-05-01

In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the Euclidean space. The proposed theory preserves the geometrical concept of the structuring function, which provides the foundation of classical morphology and is essential in signal and image processing applications. We define the basic SV gray-level morphological operators (i.e., SV gray-level erosion, dilation, opening, and closing) and investigate their properties. We demonstrate the ubiquity of SV gray-level morphological systems by deriving a kernel representation for a large class of systems, called V-systems, in terms of the basic SV graylevel morphological operators. A V-system is defined to be a gray-level operator, which is invariant under gray-level (vertical) translations. Particular attention is focused on the class of SV flat gray-level operators. The kernel representation for increasing V-systems is a generalization of Maragos' kernel representation for increasing and translation-invariant function-processing systems. A representation of V-systems in terms of their kernel elements is established for increasing and upper-semi-continuous V-systems. This representation unifies a large class of spatially-variant linear and non-linear systems under the same mathematical framework. Finally, simulation results show the potential power of the general theory of gray-level spatially-variant mathematical morphology in several image analysis and computer vision applications.

Remote sensing of the Fram Strait marginal ice zone

USGS Publications Warehouse

Shuchman, R.A.; Burns, B.A.; Johannessen, O.M.; Josberger, E.G.; Campbell, W.J.; Manley, T.O.; Lannelongue, N.

1987-01-01

Sequential remote sensing images of the Fram Strait marginal ice zone played a key role in elucidating the complex interactions of the atmosphere, ocean, and sea ice. Analysis of a subset of these images covering a 1-week period provided quantitative data on the mesoscale ice morphology, including ice edge positions, ice concentrations, floe size distribution, and ice kinematics. The analysis showed that, under light to moderate wind conditions, the morphology of the marginal ice zone reflects the underlying ocean circulation. High-resolution radar observations showed the location and size of ocean eddies near the ice edge. Ice kinematics from sequential radar images revealed an ocean eddy beneath the interior pack ice that was verified by in situ oceanographic measurements.

Morphological and Compositional (S)TEM Analysis of Multiple Exciton Generation Solar Cells

NASA Astrophysics Data System (ADS)

Wisnivesky-Rocca-Rivarola, F.; Davis, N. J. L. K.; Bohm, M.; Ducati, C.

2015-10-01

Quantum confinement of charge carriers in semiconductor nanocrystals produces optical and electronic properties that have the potential to enhance the power conversion efficiency of solar cells. One of these properties is the efficient formation of more than one electron-hole pair from a single absorbed photon, in a process called multiple exciton generation (MEG). In this work we studied the morphology of nanocrystal multilayers of PbSe treated with CdCl2 using complementary imaging and spectroscopy techniques to characterise the chemical composition and morphology of full MEG devices made with PbSe nanorods (NRs). IN the scanning TEM (STEM), plan view images and chemical maps were obtained of the nanocrystal layers, which allowed for the analysis of crystal structure and orientation, as well as size distribution and aspect ratio. These results were complemented by cross-sectional images of full devices, which allowed accessing the structure of each layer that composes the device, including the nanorod packing in the active nanocrystal layer.

Morphological analysis of the growth stages of in-vivo mouse hair follicles by using optical coherence tomography

NASA Astrophysics Data System (ADS)

Jha, Rakesh Kumar; Kim, Kanghae; Jeon, Mansik; Kim, Jeehyun; Kang, Minyoung; Han, Insook; Kim, Moonkyu

2016-09-01

Swept-source optical coherence tomography (SS-OCT), a bio-photonic imaging modality, was used to demonstrate an initial feasibility experiment for detecting morphological variations of in-vivo mouse hair follicles for the anagen and the telogen growth stages. Two C57BL/6 adult male mice, one undergoing the anagen stage and the other undergoing the telogen stage of the hair follicle growth cycle, were selected for the experiment. The OCT cross-sectional images of mice skin were acquired in-vivo within an interval of 15 days, and the observed morphological changes were analyzed. The micro-structural features of mice skin on the 15th experimental day were further compared with corresponding histological observations. The preliminary result of this study provides clear insights into the structural details of mouse skin, confirming the resemblance of the OCT images with the corresponding histological measurements, and ensures the suitability of SS-OCT for non-invasive analysis of hair follicle conditions.

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.

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.

Image edge detection based tool condition monitoring with morphological component analysis.

PubMed

Yu, Xiaolong; Lin, Xin; Dai, Yiquan; Zhu, Kunpeng

2017-07-01

The measurement and monitoring of tool condition are keys to the product precision in the automated manufacturing. To meet the need, this study proposes a novel tool wear monitoring approach based on the monitored image edge detection. Image edge detection has been a fundamental tool to obtain features of images. This approach extracts the tool edge with morphological component analysis. Through the decomposition of original tool wear image, the approach reduces the influence of texture and noise for edge measurement. Based on the target image sparse representation and edge detection, the approach could accurately extract the tool wear edge with continuous and complete contour, and is convenient in charactering tool conditions. Compared to the celebrated algorithms developed in the literature, this approach improves the integrity and connectivity of edges, and the results have shown that it achieves better geometry accuracy and lower error rate in the estimation of tool conditions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Development of an ultralow-light-level luminescence image analysis system for dynamic measurements of transcriptional activity in living and migrating cells.

PubMed

Maire, E; Lelièvre, E; Brau, D; Lyons, A; Woodward, M; Fafeur, V; Vandenbunder, B

2000-04-10

We have developed an approach to study in single living epithelial cells both cell migration and transcriptional activation, which was evidenced by the detection of luminescence emission from cells transfected with luciferase reporter vectors. The image acquisition chain consists of an epifluorescence inverted microscope, connected to an ultralow-light-level photon-counting camera and an image-acquisition card associated to specialized image analysis software running on a PC computer. Using a simple method based on a thin calibrated light source, the image acquisition chain has been optimized following comparisons of the performance of microscopy objectives and photon-counting cameras designed to observe luminescence. This setup allows us to measure by image analysis the luminescent light emitted by individual cells stably expressing a luciferase reporter vector. The sensitivity of the camera was adjusted to a high value, which required the use of a segmentation algorithm to eliminate the background noise. Following mathematical morphology treatments, kinetic changes of luminescent sources were analyzed and then correlated with the distance and speed of migration. Our results highlight the usefulness of our image acquisition chain and mathematical morphology software to quantify the kinetics of luminescence changes in migrating cells.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia.

PubMed

Diamond, James; Anderson, Neil H; Bartels, Peter H; Montironi, Rodolfo; Hamilton, Peter W

2004-09-01

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at x 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 x 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

The Digital Fish Library: Using MRI to Digitize, Database, and Document the Morphological Diversity of Fish

PubMed Central

Berquist, Rachel M.; Gledhill, Kristen M.; Peterson, Matthew W.; Doan, Allyson H.; Baxter, Gregory T.; Yopak, Kara E.; Kang, Ning; Walker, H. J.; Hastings, Philip A.; Frank, Lawrence R.

2012-01-01

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators. PMID:22493695

The Digital Fish Library: using MRI to digitize, database, and document the morphological diversity of fish.

PubMed

Berquist, Rachel M; Gledhill, Kristen M; Peterson, Matthew W; Doan, Allyson H; Baxter, Gregory T; Yopak, Kara E; Kang, Ning; Walker, H J; Hastings, Philip A; Frank, Lawrence R

2012-01-01

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators.

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

Glioma grading using cell nuclei morphologic features in digital pathology images

NASA Astrophysics Data System (ADS)

Reza, Syed M. S.; Iftekharuddin, Khan M.

2016-03-01

This work proposes a computationally efficient cell nuclei morphologic feature analysis technique to characterize the brain gliomas in tissue slide images. In this work, our contributions are two-fold: 1) obtain an optimized cell nuclei segmentation method based on the pros and cons of the existing techniques in literature, 2) extract representative features by k-mean clustering of nuclei morphologic features to include area, perimeter, eccentricity, and major axis length. This clustering based representative feature extraction avoids shortcomings of extensive tile [1] [2] and nuclear score [3] based methods for brain glioma grading in pathology images. Multilayer perceptron (MLP) is used to classify extracted features into two tumor types: glioblastoma multiforme (GBM) and low grade glioma (LGG). Quantitative scores such as precision, recall, and accuracy are obtained using 66 clinical patients' images from The Cancer Genome Atlas (TCGA) [4] dataset. On an average ~94% accuracy from 10 fold crossvalidation confirms the efficacy of the proposed method.

Analysis of Europan Cycloid Morphology and Implications for Formation Mechanisms

NASA Technical Reports Server (NTRS)

Marshall, S. T.; Kattenhorn, S. A.

2004-01-01

Europa's highly fractured crust has been shown to contain features with a range of differing morphologies. Most lineaments on Europa are believed to have initiated as cracks, although the type of cracking (e.g. tensile vs. shear) remains unclear and may vary for different morphologies. Arcuate lineaments, called cycloids or flexi, have been observed in nearly all imaged regions of Europa and have been modeled as tensile fractures that were initiated in response to diurnal variations in tides. Despite this hypothesis about the formation mechanism, there have been no detailed analyses of the variable morphologies of cycloids. We have examined Galileo images of numerous locations on Europa to develop a catalog of the different morphologies of cycloids. This study focuses on variations in morphology along individual cycloid segments and differences in cusp styles between segments, while illustrating how morphologic evidence can help unravel formation mechanisms. In so doing, we present evidence for cycloid cusps forming due to secondary fracturing during strike-slip sliding on pre-existing cycloid segments.

Separating Bulk and Surface Contributions to Electronic Excited-State Processes in Hybrid Mixed Perovskite Thin Films via Multimodal All-Optical Imaging.

PubMed

Simpson, Mary Jane; Doughty, Benjamin; Das, Sanjib; Xiao, Kai; Ma, Ying-Zhong

2017-07-20

A comprehensive understanding of electronic excited-state phenomena underlying the impressive performance of solution-processed hybrid halide perovskite solar cells requires access to both spatially resolved electronic processes and corresponding sample morphological characteristics. Here, we demonstrate an all-optical multimodal imaging approach that enables us to obtain both electronic excited-state and morphological information on a single optical microscope platform with simultaneous high temporal and spatial resolution. Specifically, images were acquired for the same region of interest in thin films of chloride containing mixed lead halide perovskites (CH 3 NH 3 PbI 3-x Cl x ) using femtosecond transient absorption, time-integrated photoluminescence, confocal reflectance, and transmission microscopies. Comprehensive image analysis revealed the presence of surface- and bulk-dominated contributions to the various images, which describe either spatially dependent electronic excited-state properties or morphological variations across the probed region of the thin films. These results show that PL probes effectively the species near or at the film surface.

A quantitative framework for flower phenotyping in cultivated carnation (Dianthus caryophyllus L.).

PubMed

Chacón, Borja; Ballester, Roberto; Birlanga, Virginia; Rolland-Lagan, Anne-Gaëlle; Pérez-Pérez, José Manuel

2013-01-01

Most important breeding goals in ornamental crops are plant appearance and flower characteristics where selection is visually performed on direct offspring of crossings. We developed an image analysis toolbox for the acquisition of flower and petal images from cultivated carnation (Dianthus caryophyllus L.) that was validated by a detailed analysis of flower and petal size and shape in 78 commercial cultivars of D. caryophyllus, including 55 standard, 22 spray and 1 pot carnation cultivars. Correlation analyses allowed us to reduce the number of parameters accounting for the observed variation in flower and petal morphology. Convexity was used as a descriptor for the level of serration in flowers and petals. We used a landmark-based approach that allowed us to identify eight main principal components (PCs) accounting for most of the variance observed in petal shape. The effect and the strength of these PCs in standard and spray carnation cultivars are consistent with shared underlying mechanisms involved in the morphological diversification of petals in both subpopulations. Our results also indicate that neighbor-joining trees built with morphological data might infer certain phylogenetic relationships among carnation cultivars. Based on estimated broad-sense heritability values for some flower and petal features, different genetic determinants shall modulate the responses of flower and petal morphology to environmental cues in this species. We believe our image analysis toolbox could allow capturing flower variation in other species of high ornamental value.

A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line.

PubMed

Collins, Adam; Huett, Alan

2018-05-15

We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn's Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed.

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

PubMed Central

Grocott, Timothy; Thomas, Paul; Münsterberg, Andrea E.

2016-01-01

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states. PMID:26864723

Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks.

PubMed

Grocott, Timothy; Thomas, Paul; Münsterberg, Andrea E

2016-02-11

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.

A Novel Method for Block Size Forensics Based on Morphological Operations

NASA Astrophysics Data System (ADS)

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.

Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.

PubMed

Yang, Zhen; Bogovic, John A; Carass, Aaron; Ye, Mao; Searson, Peter C; Prince, Jerry L

2013-03-13

With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.

Segmentation and Morphometric Analysis of Cells from Fluorescence Microscopy Images of Cytoskeletons

PubMed Central

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures. PMID:23762186

Segmentation and morphometric analysis of cells from fluorescence microscopy images of cytoskeletons.

PubMed

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures.

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.

Label-free three-dimensional imaging of cell nucleus using third-harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Lin, Jian; Zheng, Wei; Wang, Zi; Huang, Zhiwei

2014-09-01

We report the implementation of the combined third-harmonic generation (THG) and two-photon excited fluorescence (TPEF) microscopy for label-free three-dimensional (3-D) imaging of cell nucleus morphological changes in liver tissue. THG imaging shows regular spherical shapes of normal hepatocytes nuclei with inner chromatin structures while revealing the condensation of chromatins and nuclear fragmentations in hepatocytes of diseased liver tissue. Colocalized THG and TPEF imaging provides complementary information of cell nuclei and cytoplasm in tissue. This work suggests that 3-D THG microscopy has the potential for quantitative analysis of nuclear morphology in cells at a submicron-resolution without the need for DNA staining.

Label-free three-dimensional imaging of cell nucleus using third-harmonic generation microscopy

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

Lin, Jian; Zheng, Wei; Wang, Zi

2014-09-08

We report the implementation of the combined third-harmonic generation (THG) and two-photon excited fluorescence (TPEF) microscopy for label-free three-dimensional (3-D) imaging of cell nucleus morphological changes in liver tissue. THG imaging shows regular spherical shapes of normal hepatocytes nuclei with inner chromatin structures while revealing the condensation of chromatins and nuclear fragmentations in hepatocytes of diseased liver tissue. Colocalized THG and TPEF imaging provides complementary information of cell nuclei and cytoplasm in tissue. This work suggests that 3-D THG microscopy has the potential for quantitative analysis of nuclear morphology in cells at a submicron-resolution without the need for DNA staining.

Insight into plant cell wall chemistry and structure by combination of multiphoton microscopy with Raman imaging.

PubMed

Heiner, Zsuzsanna; Zeise, Ingrid; Elbaum, Rivka; Kneipp, Janina

2018-04-01

Spontaneous Raman scattering microspectroscopy, second harmonic generation (SHG) and 2-photon excited fluorescence (2PF) were used in combination to characterize the morphology together with the chemical composition of the cell wall in native plant tissues. As the data obtained with unstained sections of Sorghum bicolor root and leaf tissues illustrate, nonresonant as well as pre-resonant Raman microscopy in combination with hyperspectral analysis reveals details about the distribution and composition of the major cell wall constituents. Multivariate analysis of the Raman data allows separation of different tissue regions, specifically the endodermis, xylem and lumen. The orientation of cellulose microfibrils is obtained from polarization-resolved SHG signals. Furthermore, 2-photon autofluorescence images can be used to image lignification. The combined compositional, morphological and orientational information in the proposed coupling of SHG, Raman imaging and 2PF presents an extension of existing vibrational microspectroscopic imaging and multiphoton microscopic approaches not only for plant tissues. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Coastal modification of a scene employing multispectral images and vector operators.

PubMed

Lira, Jorge

2017-05-01

Changes in sea level, wind patterns, sea current patterns, and tide patterns have produced morphologic transformations in the coastline area of Tamaulipas Sate in North East Mexico. Such changes generated a modification of the coastline and variations of the texture-relief and texture of the continental area of Tamaulipas. Two high-resolution multispectral satellite Satellites Pour l'Observation de la Terre images were employed to quantify the morphologic change of such continental area. The images cover a time span close to 10 years. A variant of the principal component analysis was used to delineate the modification of the land-water line. To quantify changes in texture-relief and texture, principal component analysis was applied to the multispectral images. The first principal components of each image were modeled as a discrete bidimensional vector field. The divergence and Laplacian vector operators were applied to the discrete vector field. The divergence provided the change of texture, while the Laplacian produced the change of texture-relief in the area of study.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis.

PubMed

Kuleesha, Yadav; Puah, Wee Choo; Lin, Feng; Wasser, Martin

2014-01-01

During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation.

FMAj: a tool for high content analysis of muscle dynamics in Drosophila metamorphosis

PubMed Central

2014-01-01

Background During metamorphosis in Drosophila melanogaster, larval muscles undergo two different developmental fates; one population is removed by cell death, while the other persistent subset undergoes morphological remodeling and survives to adulthood. Thanks to the ability to perform live imaging of muscle development in transparent pupae and the power of genetics, metamorphosis in Drosophila can be used as a model to study the regulation of skeletal muscle mass. However, time-lapse microscopy generates sizeable image data that require new tools for high throughput image analysis. Results We performed targeted gene perturbation in muscles and acquired 3D time-series images of muscles in metamorphosis using laser scanning confocal microscopy. To quantify the phenotypic effects of gene perturbations, we designed the Fly Muscle Analysis tool (FMAj) which is based on the ImageJ and MySQL frameworks for image processing and data storage, respectively. The image analysis pipeline of FMAj contains three modules. The first module assists in adding annotations to time-lapse datasets, such as genotypes, experimental parameters and temporal reference points, which are used to compare different datasets. The second module performs segmentation and feature extraction of muscle cells and nuclei. Users can provide annotations to the detected objects, such as muscle identities and anatomical information. The third module performs comparative quantitative analysis of muscle phenotypes. We applied our tool to the phenotypic characterization of two atrophy related genes that were silenced by RNA interference. Reduction of Drosophila Tor (Target of Rapamycin) expression resulted in enhanced atrophy compared to control, while inhibition of the autophagy factor Atg9 caused suppression of atrophy and enlarged muscle fibers of abnormal morphology. FMAj enabled us to monitor the progression of atrophic and hypertrophic phenotypes of individual muscles throughout metamorphosis. Conclusions We designed a new tool to visualize and quantify morphological changes of muscles in time-lapse images of Drosophila metamorphosis. Our in vivo imaging experiments revealed that evolutionarily conserved genes involved in Tor signalling and autophagy, perform similar functions in regulating muscle mass in mammals and Drosophila. Extending our approach to a genome-wide scale has the potential to identify new genes involved in muscle size regulation. PMID:25521203

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

Morphology-based Query for Galaxy Image Databases

NASA Astrophysics Data System (ADS)

Shamir, Lior

2017-02-01

Galaxies of rare morphology are of paramount scientific interest, as they carry important information about the past, present, and future Universe. Once a rare galaxy is identified, studying it more effectively requires a set of galaxies of similar morphology, allowing generalization and statistical analysis that cannot be done when N=1. Databases generated by digital sky surveys can contain a very large number of galaxy images, and therefore once a rare galaxy of interest is identified it is possible that more instances of the same morphology are also present in the database. However, when a researcher identifies a certain galaxy of rare morphology in the database, it is virtually impossible to mine the database manually in the search for galaxies of similar morphology. Here we propose a computer method that can automatically search databases of galaxy images and identify galaxies that are morphologically similar to a certain user-defined query galaxy. That is, the researcher provides an image of a galaxy of interest, and the pattern recognition system automatically returns a list of galaxies that are visually similar to the target galaxy. The algorithm uses a comprehensive set of descriptors, allowing it to support different types of galaxies, and it is not limited to a finite set of known morphologies. While the list of returned galaxies is neither clean nor complete, it contains a far higher frequency of galaxies of the morphology of interest, providing a substantial reduction of the data. Such algorithms can be integrated into data management systems of autonomous digital sky surveys such as the Large Synoptic Survey Telescope (LSST), where the number of galaxies in the database is extremely large. The source code of the method is available at http://vfacstaff.ltu.edu/lshamir/downloads/udat.

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

Strain relaxation induced surface morphology of heterogeneous GaInNAs layers grown on GaAs substrate

NASA Astrophysics Data System (ADS)

Gelczuk, Ł.; Jóźwiak, G.; Moczała, M.; Dłużewski, P.; Dąbrowska-Szata, M.; Gotszalk, T. P.

2017-07-01

The partially-relaxed heterogeneous GaInNAs layers grown on GaAs substrate by atmospheric pressure vapor phase epitaxy (AP-MOVPE) were investigated by transmission electron microscopy (TEM) and atomic force microscopy (AFM). The planar-view TEM image shows a regular 2D network of misfit dislocations oriented in two orthogonal 〈1 1 0〉 crystallographic directions at the (0 0 1) layer interface. Moreover, the cross-sectional view TEM image reveals InAs-rich and V-shaped precipitates in the near surface region of the GaInNAs epitaxial layer. The resultant undulating surface morphology, known as a cross-hatch pattern, is formed as observed by AFM. The numerical analysis of the AFM image of the GaInNAs layer surface with the well-defined cross-hatch morphology enabled us to determine a lower bound of actual density of misfit dislocations. However, a close correspondence between the asymmetric distribution of interfacial misfit dislocations and undulating surface morphology is observed.

Automatic identification of fault surfaces through Object Based Image Analysis of a Digital Elevation Model in the submarine area of the North Aegean Basin

NASA Astrophysics Data System (ADS)

Argyropoulou, Evangelia

2015-04-01

The current study was focused on the seafloor morphology of the North Aegean Basin in Greece, through Object Based Image Analysis (OBIA) using a Digital Elevation Model. The goal was the automatic extraction of morphologic and morphotectonic features, resulting into fault surface extraction. An Object Based Image Analysis approach was developed based on the bathymetric data and the extracted features, based on morphological criteria, were compared with the corresponding landforms derived through tectonic analysis. A digital elevation model of 150 meters spatial resolution was used. At first, slope, profile curvature, and percentile were extracted from this bathymetry grid. The OBIA approach was developed within the eCognition environment. Four segmentation levels were created having as a target "level 4". At level 4, the final classes of geomorphological features were classified: discontinuities, fault-like features and fault surfaces. On previous levels, additional landforms were also classified, such as continental platform and continental slope. The results of the developed approach were evaluated by two methods. At first, classification stability measures were computed within eCognition. Then, qualitative and quantitative comparison of the results took place with a reference tectonic map which has been created manually based on the analysis of seismic profiles. The results of this comparison were satisfactory, a fact which determines the correctness of the developed OBIA approach.

Changes in tendon spatial frequency parameters with loading.

PubMed

Pearson, Stephen J; Engel, Aaron J; Bashford, Gregory R

2017-05-24

To examine and compare the loading related changes in micro-morphology of the patellar tendon. Fifteen healthy young males (age 19±3yrs, body mass 83±5kg) were utilised in a within subjects matched pairs design. B mode ultrasound images were taken in the sagittal plane of the patellar tendon at rest with the knee at 90° flexion. Repeat images were taken whilst the subjects were carrying out maximal voluntary isometric contractions. Spatial frequency parameters related to the tendon morphology were determined within regions of interest (ROI) from the B mode images at rest and during isometric contractions. A number of spatial parameters were observed to be significantly different between resting and contracted images (Peak spatial frequency radius (PSFR), axis ratio, spatial Q-factor, PSFR amplitude ratio, and the sum). These spatial frequency parameters were indicative of acute alterations in the tendon micro-morphology with loading. Acute loading modifies the micro-morphology of the tendon, as observed via spatial frequency analysis. Further research is warranted to explore its utility with regard to different loading induced micro-morphological alterations, as these could give valuable insight not only to aid strengthening of this tissue but also optimization of recovery from injury and treatment of conditions such as tendinopathies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid reconstruction of 3D neuronal morphology from light microscopy images with augmented rayburst sampling.

PubMed

Ming, Xing; Li, Anan; Wu, Jingpeng; Yan, Cheng; Ding, Wenxiang; Gong, Hui; Zeng, Shaoqun; Liu, Qian

2013-01-01

Digital reconstruction of three-dimensional (3D) neuronal morphology from light microscopy images provides a powerful technique for analysis of neural circuits. It is time-consuming to manually perform this process. Thus, efficient computer-assisted approaches are preferable. In this paper, we present an innovative method for the tracing and reconstruction of 3D neuronal morphology from light microscopy images. The method uses a prediction and refinement strategy that is based on exploration of local neuron structural features. We extended the rayburst sampling algorithm to a marching fashion, which starts from a single or a few seed points and marches recursively forward along neurite branches to trace and reconstruct the whole tree-like structure. A local radius-related but size-independent hemispherical sampling was used to predict the neurite centerline and detect branches. Iterative rayburst sampling was performed in the orthogonal plane, to refine the centerline location and to estimate the local radius. We implemented the method in a cooperative 3D interactive visualization-assisted system named flNeuronTool. The source code in C++ and the binaries are freely available at http://sourceforge.net/projects/flneurontool/. We validated and evaluated the proposed method using synthetic data and real datasets from the Digital Reconstruction of Axonal and Dendritic Morphology (DIADEM) challenge. Then, flNeuronTool was applied to mouse brain images acquired with the Micro-Optical Sectioning Tomography (MOST) system, to reconstruct single neurons and local neural circuits. The results showed that the system achieves a reasonable balance between fast speed and acceptable accuracy, which is promising for interactive applications in neuronal image analysis.

The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging.

PubMed

Garza-Villarreal, E A; Chakravarty, M M; Hansen, B; Eskildsen, S F; Devenyi, G A; Castillo-Padilla, D; Balducci, T; Reyes-Zamorano, E; Jespersen, S N; Perez-Palacios, P; Patel, R; Gonzalez-Olvera, J J

2017-05-09

The striatum and thalamus are subcortical structures intimately involved in addiction. The morphology and microstructure of these have been studied in murine models of cocaine addiction (CA), showing an effect of drug use, but also chronological age in morphology. Human studies using non-invasive magnetic resonance imaging (MRI) have shown inconsistencies in volume changes, and have also shown an age effect. In this exploratory study, we used MRI-based volumetric and novel shape analysis, as well as a novel fast diffusion kurtosis imaging sequence to study the morphology and microstructure of striatum and thalamus in crack CA compared to matched healthy controls (HCs), while investigating the effect of age and years of cocaine consumption. We did not find significant differences in volume and mean kurtosis (MKT) between groups. However, we found significant contraction of nucleus accumbens in CA compared to HCs. We also found significant age-related changes in volume and MKT of CA in striatum and thalamus that are different to those seen in normal aging. Interestingly, we found different effects and contributions of age and years of consumption in volume, displacement and MKT changes, suggesting that each measure provides different but complementing information about morphological brain changes, and that not all changes are related to the toxicity or the addiction to the drug. Our findings suggest that the use of finer methods and sequences provides complementing information about morphological and microstructural changes in CA, and that brain alterations in CA are related cocaine use and age differently.

The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging

PubMed Central

Garza-Villarreal, E A; Chakravarty, MM; Hansen, B; Eskildsen, S F; Devenyi, G A; Castillo-Padilla, D; Balducci, T; Reyes-Zamorano, E; Jespersen, S N; Perez-Palacios, P; Patel, R; Gonzalez-Olvera, J J

2017-01-01

The striatum and thalamus are subcortical structures intimately involved in addiction. The morphology and microstructure of these have been studied in murine models of cocaine addiction (CA), showing an effect of drug use, but also chronological age in morphology. Human studies using non-invasive magnetic resonance imaging (MRI) have shown inconsistencies in volume changes, and have also shown an age effect. In this exploratory study, we used MRI-based volumetric and novel shape analysis, as well as a novel fast diffusion kurtosis imaging sequence to study the morphology and microstructure of striatum and thalamus in crack CA compared to matched healthy controls (HCs), while investigating the effect of age and years of cocaine consumption. We did not find significant differences in volume and mean kurtosis (MKT) between groups. However, we found significant contraction of nucleus accumbens in CA compared to HCs. We also found significant age-related changes in volume and MKT of CA in striatum and thalamus that are different to those seen in normal aging. Interestingly, we found different effects and contributions of age and years of consumption in volume, displacement and MKT changes, suggesting that each measure provides different but complementing information about morphological brain changes, and that not all changes are related to the toxicity or the addiction to the drug. Our findings suggest that the use of finer methods and sequences provides complementing information about morphological and microstructural changes in CA, and that brain alterations in CA are related cocaine use and age differently. PMID:28485734

Spatially variant morphological restoration and skeleton representation.

PubMed

Bouaynaya, Nidhal; Charif-Chefchaouni, Mohammed; Schonfeld, Dan

2006-11-01

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

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.

A Quantitative Framework for Flower Phenotyping in Cultivated Carnation (Dianthus caryophyllus L.)

PubMed Central

Chacón, Borja; Ballester, Roberto; Birlanga, Virginia; Rolland-Lagan, Anne-Gaëlle; Pérez-Pérez, José Manuel

2013-01-01

Most important breeding goals in ornamental crops are plant appearance and flower characteristics where selection is visually performed on direct offspring of crossings. We developed an image analysis toolbox for the acquisition of flower and petal images from cultivated carnation (Dianthus caryophyllus L.) that was validated by a detailed analysis of flower and petal size and shape in 78 commercial cultivars of D. caryophyllus, including 55 standard, 22 spray and 1 pot carnation cultivars. Correlation analyses allowed us to reduce the number of parameters accounting for the observed variation in flower and petal morphology. Convexity was used as a descriptor for the level of serration in flowers and petals. We used a landmark-based approach that allowed us to identify eight main principal components (PCs) accounting for most of the variance observed in petal shape. The effect and the strength of these PCs in standard and spray carnation cultivars are consistent with shared underlying mechanisms involved in the morphological diversification of petals in both subpopulations. Our results also indicate that neighbor-joining trees built with morphological data might infer certain phylogenetic relationships among carnation cultivars. Based on estimated broad-sense heritability values for some flower and petal features, different genetic determinants shall modulate the responses of flower and petal morphology to environmental cues in this species. We believe our image analysis toolbox could allow capturing flower variation in other species of high ornamental value. PMID:24349209

Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis.

PubMed

Luo, Xin; Zang, Xiao; Yang, Lin; Huang, Junzhou; Liang, Faming; Rodriguez-Canales, Jaime; Wistuba, Ignacio I; Gazdar, Adi; Xie, Yang; Xiao, Guanghua

2017-03-01

Pathological examination of histopathological slides is a routine clinical procedure for lung cancer diagnosis and prognosis. Although the classification of lung cancer has been updated to become more specific, only a small subset of the total morphological features are taken into consideration. The vast majority of the detailed morphological features of tumor tissues, particularly tumor cells' surrounding microenvironment, are not fully analyzed. The heterogeneity of tumor cells and close interactions between tumor cells and their microenvironments are closely related to tumor development and progression. The goal of this study is to develop morphological feature-based prediction models for the prognosis of patients with lung cancer. We developed objective and quantitative computational approaches to analyze the morphological features of pathological images for patients with NSCLC. Tissue pathological images were analyzed for 523 patients with adenocarcinoma (ADC) and 511 patients with squamous cell carcinoma (SCC) from The Cancer Genome Atlas lung cancer cohorts. The features extracted from the pathological images were used to develop statistical models that predict patients' survival outcomes in ADC and SCC, respectively. We extracted 943 morphological features from pathological images of hematoxylin and eosin-stained tissue and identified morphological features that are significantly associated with prognosis in ADC and SCC, respectively. Statistical models based on these extracted features stratified NSCLC patients into high-risk and low-risk groups. The models were developed from training sets and validated in independent testing sets: a predicted high-risk group versus a predicted low-risk group (for patients with ADC: hazard ratio = 2.34, 95% confidence interval: 1.12-4.91, p = 0.024; for patients with SCC: hazard ratio = 2.22, 95% confidence interval: 1.15-4.27, p = 0.017) after adjustment for age, sex, smoking status, and pathologic tumor stage. The results suggest that the quantitative morphological features of tumor pathological images predict prognosis in patients with lung cancer. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Colony fingerprint for discrimination of microbial species based on lensless imaging of microcolonies

PubMed Central

Maeda, Yoshiaki; Dobashi, Hironori; Sugiyama, Yui; Saeki, Tatsuya; Lim, Tae-kyu; Harada, Manabu; Matsunaga, Tadashi; Yoshino, Tomoko

2017-01-01

Detection and identification of microbial species are crucial in a wide range of industries, including production of beverages, foods, cosmetics, and pharmaceuticals. Traditionally, colony formation and its morphological analysis (e.g., size, shape, and color) with a naked eye have been employed for this purpose. However, such a conventional method is time consuming, labor intensive, and not very reproducible. To overcome these problems, we propose a novel method that detects microcolonies (diameter 10–500 μm) using a lensless imaging system. When comparing colony images of five microorganisms from different genera (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans), the images showed obvious different features. Being closely related species, St. aureus and St. epidermidis resembled each other, but the imaging analysis could extract substantial information (colony fingerprints) including the morphological and physiological features, and linear discriminant analysis of the colony fingerprints distinguished these two species with 100% of accuracy. Because this system may offer many advantages such as high-throughput testing, lower costs, more compact equipment, and ease of automation, it holds promise for microbial detection and identification in various academic and industrial areas. PMID:28369067

Applications of wavelets in morphometric analysis of medical images

NASA Astrophysics Data System (ADS)

Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

2003-11-01

Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

NASA Astrophysics Data System (ADS)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

Separating Bulk and Surface Contributions to Electronic Excited-State Processes in Hybrid Mixed Perovskite Thin Films via Multimodal All-Optical Imaging

DOE PAGES

Simpson, Mary Jane; Doughty, Benjamin; Das, Sanjib; ...

2017-07-04

A comprehensive understanding of electronic excited-state phenomena underlying the impressive performance of solution-processed hybrid halide perovskite solar cells requires access to both spatially resolved electronic processes and corresponding sample morphological characteristics. In this paper, we demonstrate an all-optical multimodal imaging approach that enables us to obtain both electronic excited-state and morphological information on a single optical microscope platform with simultaneous high temporal and spatial resolution. Specifically, images were acquired for the same region of interest in thin films of chloride containing mixed lead halide perovskites (CH 3NH 3PbI 3–xCl x) using femtosecond transient absorption, time-integrated photoluminescence, confocal reflectance, and transmissionmore » microscopies. Comprehensive image analysis revealed the presence of surface- and bulk-dominated contributions to the various images, which describe either spatially dependent electronic excited-state properties or morphological variations across the probed region of the thin films. Finally, these results show that PL probes effectively the species near or at the film surface.« less

Characterization of Homopolymer and Polymer Blend Films by Phase Sensitive Acoustic Microscopy

NASA Astrophysics Data System (ADS)

Ngwa, Wilfred; Wannemacher, Reinhold; Grill, Wolfgang

2003-03-01

CHARACTERIZATION OF HOMOPOLYMER AND POLYMER BLEND FILMS BY PHASE SENSITIVE ACOUSTIC MICROSCOPY W Ngwa, R Wannemacher, W Grill Institute of Experimental Physics II, University of Leipzig, 04103 Leipzig, Germany Abstract We have used phase sensitive acoustic microscopy (PSAM) to study homopolymer thin films of polystyrene (PS) and poly (methyl methacrylate) (PMMA), as well as PS/PMMA blend films. We show from our results that PSAM can be used as a complementary and highly valuable technique for elucidating the three-dimensional (3D) morphology and micromechanical properties of thin films. Three-dimensional image acquisition with vector contrast provides the basis for: complex V(z) analysis (per image pixel), 3D image processing, height profiling, and subsurface image analysis of the polymer films. Results show good agreement with previous studies. In addition, important new information on the three dimensional structure and properties of polymer films is obtained. Homopolymer film structure analysis reveals (pseudo-) dewetting by retraction of droplets, resulting in a morphology that can serve as a starting point for the analysis of polymer blend thin films. The outcome of confocal laser scanning microscopy studies, performed on the same samples are correlated with the obtained results. Advantages and limitations of PSAM are discussed.

SNIa detection in the SNLS photometric analysis using Morphological Component Analysis

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

Möller, A.; Ruhlmann-Kleider, V.; Neveu, J.

2015-04-01

Detection of supernovae (SNe) and, more generally, of transient events in large surveys can provide numerous false detections. In the case of a deferred processing of survey images, this implies reconstructing complete light curves for all detections, requiring sizable processing time and resources. Optimizing the detection of transient events is thus an important issue for both present and future surveys. We present here the optimization done in the SuperNova Legacy Survey (SNLS) for the 5-year data deferred photometric analysis. In this analysis, detections are derived from stacks of subtracted images with one stack per lunation. The 3-year analysis provided 300,000more » detections dominated by signals of bright objects that were not perfectly subtracted. Allowing these artifacts to be detected leads not only to a waste of resources but also to possible signal coordinate contamination. We developed a subtracted image stack treatment to reduce the number of non SN-like events using morphological component analysis. This technique exploits the morphological diversity of objects to be detected to extract the signal of interest. At the level of our subtraction stacks, SN-like events are rather circular objects while most spurious detections exhibit different shapes. A two-step procedure was necessary to have a proper evaluation of the noise in the subtracted image stacks and thus a reliable signal extraction. We also set up a new detection strategy to obtain coordinates with good resolution for the extracted signal. SNIa Monte-Carlo (MC) generated images were used to study detection efficiency and coordinate resolution. When tested on SNLS 3-year data this procedure decreases the number of detections by a factor of two, while losing only 10% of SN-like events, almost all faint ones. MC results show that SNIa detection efficiency is equivalent to that of the original method for bright events, while the coordinate resolution is improved.« less

The use of immunohistochemistry for biomarker assessment--can it compete with other technologies?

PubMed

Dunstan, Robert W; Wharton, Keith A; Quigley, Catherine; Lowe, Amanda

2011-10-01

A morphology-based assay such as immunohistochemistry (IHC) should be a highly effective means to define the expression of a target molecule of interest, especially if the target is a protein. However, over the past decade, IHC as a platform for biomarkers has been challenged by more quantitative molecular assays with reference standards but that lack morphologic context. For IHC to be considered a "top-tier" biomarker assay, it must provide truly quantitative data on par with non-morphologic assays, which means it needs to be run with reference standards. However, creating such standards for IHC will require optimizing all aspects of tissue collection, fixation, section thickness, morphologic criteria for assessment, staining processes, digitization of images, and image analysis. This will also require anatomic pathology to evolve from a discipline that is descriptive to one that is quantitative. A major step in this transformation will be replacing traditional ocular microscopes with computer monitors and whole slide images, for without digitization, there can be no accurate quantitation; without quantitation, there can be no standardization; and without standardization, the value of morphology-based IHC assays will not be realized.

Optimization of cell morphology measurement via single-molecule tracking PALM.

PubMed

Frost, Nicholas A; Lu, Hsiangmin E; Blanpied, Thomas A

2012-01-01

In neurons, the shape of dendritic spines relates to synapse function, which is rapidly altered during experience-dependent neural plasticity. The small size of spines makes detailed measurement of their morphology in living cells best suited to super-resolution imaging techniques. The distribution of molecular positions mapped via live-cell Photoactivated Localization Microscopy (PALM) is a powerful approach, but molecular motion complicates this analysis and can degrade overall resolution of the morphological reconstruction. Nevertheless, the motion is of additional interest because tracking single molecules provides diffusion coefficients, bound fraction, and other key functional parameters. We used Monte Carlo simulations to examine features of single-molecule tracking of practical utility for the simultaneous determination of cell morphology. We find that the accuracy of determining both distance and angle of motion depend heavily on the precision with which molecules are localized. Strikingly, diffusion within a bounded region resulted in an inward bias of localizations away from the edges, inaccurately reflecting the region structure. This inward bias additionally resulted in a counterintuitive reduction of measured diffusion coefficient for fast-moving molecules; this effect was accentuated by the long camera exposures typically used in single-molecule tracking. Thus, accurate determination of cell morphology from rapidly moving molecules requires the use of short integration times within each image to minimize artifacts caused by motion during image acquisition. Sequential imaging of neuronal processes using excitation pulses of either 2 ms or 10 ms within imaging frames confirmed this: processes appeared erroneously thinner when imaged using the longer excitation pulse. Using this pulsed excitation approach, we show that PALM can be used to image spine and spine neck morphology in living neurons. These results clarify a number of issues involved in interpretation of single-molecule data in living cells and provide a method to minimize artifacts in single-molecule experiments.

Nuclear forensics investigation of morphological signatures in the thermal decomposition of uranyl peroxide.

PubMed

Schwerdt, Ian J; Olsen, Adam; Lusk, Robert; Heffernan, Sean; Klosterman, Michael; Collins, Bryce; Martinson, Sean; Kirkham, Trenton; McDonald, Luther W

2018-01-01

The analytical techniques typically utilized in a nuclear forensic investigation often provide limited information regarding the process history and production conditions of interdicted nuclear material. In this study, scanning electron microscopy (SEM) analysis of the surface morphology of amorphous-UO 3 samples calcined at 250, 300, 350, 400, and 450°C from uranyl peroxide was performed to determine if the morphology was indicative of the synthesis route and thermal history for the samples. Thermogravimetic analysis-mass spectrometry (TGA-MS) and differential scanning calorimetry (DSC) were used to correlate transitions in the calcined material to morphological transformations. The high-resolution SEM images were processed using the Morphological Analysis for Material Attribution (MAMA) software. Morphological attributes, particle area and circularity, indicated significant trends as a result of calcination temperature. The quantitative morphological analysis was able to track the process of particle fragmentation and subsequent sintering as calcination temperature was increased. At the 90% confidence interval, with 1000 segmented particles, the use of Kolmogorov-Smirnov statistical comparisons allowed discernment between all calcination temperatures for the uranyl peroxide route. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Visualizing Morphological Changes of Abscission Zone Cells in Arabidopsis by Scanning Electron Microscope.

PubMed

Shi, Chun-Lin; Butenko, Melinka A

2018-01-01

Scanning electron microscope (SEM) is a type of electron microscope which produces detailed images of surface structures. It has been widely used in plants and animals to study cellular structures. Here, we describe a detailed protocol to prepare samples of floral abscission zones (AZs) for SEM, as well as further image analysis. We show that it is a powerful tool to detect morphologic changes at the cellular level during the course of abscission in wild-type plants and to establish the details of phenotypic alteration in abscission mutants.

Image analysis applied to luminescence microscopy

NASA Astrophysics Data System (ADS)

Maire, Eric; Lelievre-Berna, Eddy; Fafeur, Veronique; Vandenbunder, Bernard

1998-04-01

We have developed a novel approach to study luminescent light emission during migration of living cells by low-light imaging techniques. The equipment consists in an anti-vibration table with a hole for a direct output under the frame of an inverted microscope. The image is directly captured by an ultra low- light level photon-counting camera equipped with an image intensifier coupled by an optical fiber to a CCD sensor. This installation is dedicated to measure in a dynamic manner the effect of SF/HGF (Scatter Factor/Hepatocyte Growth Factor) both on activation of gene promoter elements and on cell motility. Epithelial cells were stably transfected with promoter elements containing Ets transcription factor-binding sites driving a luciferase reporter gene. Luminescent light emitted by individual cells was measured by image analysis. Images of luminescent spots were acquired with a high aperture objective and time exposure of 10 - 30 min in photon-counting mode. The sensitivity of the camera was adjusted to a high value which required the use of a segmentation algorithm dedicated to eliminate the background noise. Hence, image segmentation and treatments by mathematical morphology were particularly indicated in these experimental conditions. In order to estimate the orientation of cells during their migration, we used a dedicated skeleton algorithm applied to the oblong spots of variable intensities emitted by the cells. Kinetic changes of luminescent sources, distance and speed of migration were recorded and then correlated with cellular morphological changes for each spot. Our results highlight the usefulness of the mathematical morphology to quantify kinetic changes in luminescence microscopy.

Mandibular condylar morphology for bruxers with different grinding patterns.

PubMed

Tao, Jianxiang; Wu, Junhua; Zhang, Xuying

2015-12-29

The purpose of this study was to investigate the mandibular condylar morphology for bruxers with different grinding patterns. Condylar sectional morphology and condylar position of 30 subjects were determined by two viewers using cone beam computed tomography (CBCT) image data sets. The grinding patterns during sleep bruxism (SB) were determined objectively using a Brux-checker device.Chi-square tests were used for statistical analysis for the condylar morphology type between different tooth grinding patterns. Spearman's rank correlation coefficient was used for correlation analysis between condylar position and the canine guidance area during SB. Theincidence of condylarmorphologicaldivergence from idealwas35%.There isa significant difference in distribution of condylar morphology type between the group grinding (GG) and GG combined with mediotrusive side grinding (MG) (Pv 0.05). There was no significant correlation between condylar position and canine guidance area during bruxism. MG during SB is associated with condylar morphology that is considered not to be ideal.

Mandibular condylar morphology for bruxers with different grinding patterns.

PubMed

Tao, Jianxiang; Wu, Junhua; Zhang, Xuying

2016-07-01

The purpose of this study was to investigate the mandibular condylar morphology for bruxers with different grinding patterns. Condylar sectional morphology and condylar position of 30 subjects were determined by two viewers using cone beam computed tomography (CBCT) image data sets. The grinding patterns during sleep bruxism (SB) were determined objectively using a Brux-checker device.Chi-square tests were used for statistical analysis for the condylar morphology type between different tooth grinding patterns. Spearman's rank correlation coefficient was used for correlation analysis between condylar position and the canine guidance area during SB. Theincidence of condylarmorphologicaldivergence from idealwas35%.There isa significant difference in distribution of condylar morphology type between the group grinding (GG) and GG combined with mediotrusive side grinding (MG) (p < 0.05). There was no significant correlation between condylar position and canine guidance area during bruxism. MG during SB is associated with condylar morphology that is considered not to be ideal.

A neotropical Miocene pollen database employing image-based search and semantic modeling1

PubMed Central

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

2014-01-01

• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

CHARACTERIZATION OF THE COMPLETE FIBER NETWORK TOPOLOGY OF PLANAR FIBROUS TISSUES AND SCAFFOLDS

PubMed Central

D'Amore, Antonio; Stella, John A.; Wagner, William R.; Sacks, Michael S.

2010-01-01

Understanding how engineered tissue scaffold architecture affects cell morphology, metabolism, phenotypic expression, as well as predicting material mechanical behavior have recently received increased attention. In the present study, an image-based analysis approach that provides an automated tool to characterize engineered tissue fiber network topology is presented. Micro-architectural features that fully defined fiber network topology were detected and quantified, which include fiber orientation, connectivity, intersection spatial density, and diameter. Algorithm performance was tested using scanning electron microscopy (SEM) images of electrospun poly(ester urethane)urea (ES-PEUU) scaffolds. SEM images of rabbit mesenchymal stem cell (MSC) seeded collagen gel scaffolds and decellularized rat carotid arteries were also analyzed to further evaluate the ability of the algorithm to capture fiber network morphology regardless of scaffold type and the evaluated size scale. The image analysis procedure was validated qualitatively and quantitatively, comparing fiber network topology manually detected by human operators (n=5) with that automatically detected by the algorithm. Correlation values between manual detected and algorithm detected results for the fiber angle distribution and for the fiber connectivity distribution were 0.86 and 0.93 respectively. Algorithm detected fiber intersections and fiber diameter values were comparable (within the mean ± standard deviation) with those detected by human operators. This automated approach identifies and quantifies fiber network morphology as demonstrated for three relevant scaffold types and provides a means to: (1) guarantee objectivity, (2) significantly reduce analysis time, and (3) potentiate broader analysis of scaffold architecture effects on cell behavior and tissue development both in vitro and in vivo. PMID:20398930

Temporal and spatial variation of morphological descriptors for atmospheric aerosols collected in Mexico City

NASA Astrophysics Data System (ADS)

China, S.; Mazzoleni, C.; Dubey, M. K.; Chakrabarty, R. K.; Moosmuller, H.; Onasch, T. B.; Herndon, S. C.

2010-12-01

We present an analysis of morphological characteristics of atmospheric aerosol collected during the MILAGRO (Megacity Initiative: Local and Global Research Observations) field campaign that took place in Mexico City in March 2006. The sampler was installed on the Aerodyne mobile laboratory. The aerosol samples were collected on nuclepore clear polycarbonate filters mounted in Costar pop-top membrane holders. More than one hundred filters were collected at different ground sites with different atmospheric and geographical characteristics (urban, sub-urban, mountain-top, industrial, etc.) over a month period. Selected subsets of these filters were analyzed for aerosol morphology using a scanning electron microscope and image analysis techniques. In this study we investigate spatial and temporal variations of aerosol shape descriptors, morphological parameters, and fractal dimension. We also compare the morphological results with other aerosol measurements such as aerosol optical properties(scattering and absorption) and size distribution data. Atmospheric aerosols have different morphological characteristics depending on many parameters such as emission sources, atmospheric formation pathways, aging processes, and aerosol mixing state. The aerosol morphology influences aerosol chemical and mechanical interactions with the environment, physical properties, and radiative effects. In this study, ambient aerosol particles have been classified in different shape groups as spherical, irregularly shaped, and fractal-like aggregates. Different morphological parameters such as aspect ratio, roundness, feret diameter, etc. have been estimated for irregular shaped and spherical particles and for different kinds of soot particles including fresh soot, collapsed and coated soot. Fractal geometry and image processing have been used to obtain morphological characteristics of different soot particles. The number of monomers constituting each aggregate and their diameters were measured and used to estimate an ensemble three-dimensional (3-d) fractal dimension. One-dimensional (1-d) and two-dimensional (2-d) fractal geometries have been measured using a power-law scaling relationship between 1-d and 2-d properties of projected images. Temporal variations in fractal dimension of soot-like aggregates have been observed at the mountaintop site and spatial variation of fractal dimension and other morphological descriptors of different shaped particles have been investigated for the different ground sites.

Microscopy with spatial filtering for sorting particles and monitoring subcellular morphology

NASA Astrophysics Data System (ADS)

Zheng, Jing-Yi; Qian, Zhen; Pasternack, Robert M.; Boustany, Nada N.

2009-02-01

Optical scatter imaging (OSI) was developed to non-invasively track real-time changes in particle morphology with submicron sensitivity in situ without exogenous labeling, cell fixing, or organelle isolation. For spherical particles, the intensity ratio of wide-to-narrow angle scatter (OSIR, Optical Scatter Image Ratio) was shown to decrease monotonically with diameter and agree with Mie theory. In living cells, we recently reported this technique is able to detect mitochondrial morphological alterations, which were mediated by the Bcl-xL transmembrane domain, and could not be observed by fluorescence or differential interference contrast images. Here we further extend the ability of morphology assessment by adopting a digital micromirror device (DMD) for Fourier filtering. When placed in the Fourier plane the DMD can be used to select scattering intensities at desired combination of scattering angles. We designed an optical filter bank consisting of Gabor-like filters with various scales and rotations based on Gabor filters, which have been widely used for localization of spatial and frequency information in digital images and texture analysis. Using a model system consisting of mixtures of polystyrene spheres and bacteria, we show how this system can be used to sort particles on a microscopic slide based on their size, orientation and aspect ratio. We are currently applying this technique to characterize the morphology of subcellular organelles to help understand fundamental biological processes.

Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images.

PubMed

Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

2010-07-08

A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods. A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice. Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

Morphological Analysis of Annual Recurrence of Dark Dune Spots on Southern Polar Region of Mars

NASA Technical Reports Server (NTRS)

Horvath, A.; Ganti, T.; Berczi, Sz.; Gesztesi, A.; Szathmary, E.

2003-01-01

Analysis of the Mars Global Surveyor narrow-angle images of the dark dune spots (DDSs) in three subsequent Martian winters and springs in Southern Polar Region resulted in the recognition that year by year DDSs reappeared on the same place with almost the same configuration. Comparison of the 1999 and 2001 high-resolution images showed a very interest recovery process.

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.

Three-dimensional image study on the vascular structure after angiopoietin-1 transduction in isolated mouse pancreatic islets

NASA Astrophysics Data System (ADS)

He, Jing; Su, Dongming; Trucco, Massimo

2008-02-01

Angiopoietin-1 (Ang-1) is essential for remodeling the primitive vascular plexus during embryonic development and for reducing plasma leakage in inflammation of adult vasculature. However, the role for Ang-1 in maintenance of vascular stability in isolated pancreatic islets is not fully understood. In this study, we compared the difference of vascular morphology between Ang-1 treated (n=5) and control mouse islets (n=5) using both two- and three-dimensional optical image analysis. Isolated mouse islets were transduced with Ang-1 or Lac Z (control) vector at 37°C for 16 hours. Islets were incubated with both rat anti-CD31 antibody and rabbit anti-insulin antibody followed by incubation with Rhodamine-conjugated goat anti-rat IgG and Alexa-488 conjugated goat anti-rabbit IgG. Islets were viewed under a Nikon confocal microscope. Serial optical section images were captured and reconstructed using Nikon EZ-C1 software. Individual two-D and reconstructed three-D images were analyzed using MetaMorph Image Analysis software. Islet vascular density was determined. In two-D images, there was no significant difference of vascular density between the two groups. The vascular morphology didn't show any obvious differences in two-D images either. However, in the three-D images, we found higher vascular density and more vascular branches in the Ang-1 transducted islets and vascular dilation in control group. In conclusion, using three-D image analysis, Ang-1 displayed functions in maintenance of vascular stability and in stimulating growth of vascular branches in isolated mouse pancreatic islets. In order to study further the regeneration of different cell contents in the spherical pancreatic islet, three-D image analysis is an effective method to approach this goal.

Galaxy morphology - An unsupervised machine learning approach

NASA Astrophysics Data System (ADS)

Schutter, A.; Shamir, L.

2015-09-01

Structural properties poses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a network of similarities between galaxy morphological types, and automatically deduce a morphological sequence of galaxies. Application of the method to the EFIGI catalog show that the morphological scheme produced by the algorithm is largely in agreement with the De Vaucouleurs system, demonstrating the ability of computer vision and machine learning methods to automatically profile galaxy morphological sequences. The unsupervised analysis method is based on comprehensive computer vision techniques that compute the visual similarities between the different morphological types. Rather than relying on human cognition, the proposed system deduces the similarities between sets of galaxy images in an automatic manner, and is therefore not limited by the number of galaxies being analyzed. The source code of the method is publicly available, and the protocol of the experiment is included in the paper so that the experiment can be replicated, and the method can be used to analyze user-defined datasets of galaxy images.

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

Correlation between corneal thickness and optic disc morphology in normal tension glaucoma using modern technical analysis.

PubMed

Coman, Laurenţiu; Costescu, Monica; Alecu, Mihail; Coman, Oana Andreia

2014-01-01

The purpose of this study was to evaluate the relationship between central corneal thickness (CCT) and optic disc morphology in normal tension glaucoma (NTG). Patients with NTG underwent eye examination, optic disc imaging with Heildelberg Retina Tomograph II (HRT II) and ultrasound corneal pachymetry. The morphological parameters of the optic discs were used to classify the eyes into four groups: generalized enlargement (GE) type, myopic glaucomatous (MY) type, focal ischemic (FI) type and senile sclerotic (SS) type. A correlation between CCT and optic disc morphology obtained by HRT II was calculated. Multiple comparison and post hoc tests were performed in order to determine the significance of the differences between the four groups. The strongest correlation was between CCT and the parameters of optic disc imaging obtained at HRT II in the GE type of optic disc.

Analysis of tracheid development in suppressed-growth Ponderosa Pine using the FPL ring profiler

Treesearch

C. Tim Scott; David W. Vahey

2012-01-01

The Ring Profiler was developed to examine the cross-sectional morphology of wood tracheids in a 12.5-mm core sample. The instrument integrates a specially designed staging apparatus with an optical imaging system to obtain high-contrast, high-resolution images containing about 200-500 tracheids. These images are further enhanced and analyzed to extract tracheid cross-...

Human Lymphatic Mesenteric Vessels: Morphology and Possible Function of Aminergic and NPY-ergic Nerve Fibers.

PubMed

D'Andrea, Vito; Panarese, Alessandra; Taurone, Samanta; Coppola, Luigi; Cavallotti, Carlo; Artico, Marco

2015-09-01

The lymphatic vessels have been studied in different organs from a morphological to a clinical point of view. Nevertheless, the knowledge of the catecholaminergic control of the lymphatic circulation is still incomplete. The aim of this work is to study the presence and distribution of the catecholaminergic and NPY-ergic nerve fibers in the whole wall of the human mesenteric lymphatic vessels in order to obtain knowledge about their morphology and functional significance. The following experimental procedures were performed: 1) drawing of tissue containing lymphatic vessels; 2) cutting of tissue; 3) staining of tissue; 4) staining of nerve fibers; 5) histofluorescence microscopy for the staining of catecholaminergic nerve fibers; 6) staining of neuropeptide Y like-immune reactivity; 7) biochemical assay of proteins; 8) measurement of noradrenaline; 9) quantitative analysis of images; 10) statistical analysis of data. Numerous nerve fibers run in the wall of lymphatic vessels. Many of them are catecholaminergic in nature. Some nerve fibers are NPY-positive. The biochemical results on noradrenaline amounts are in agreement with morphological results on catecholaminergic nerve fibers. Moreover, the morphometric results, obtained by the quantitative analysis of images and the subsequent statistical analysis of data, confirm all our morphological and biochemical data. The knowledge of the physiological or pathological mechanism regulating the functions of the lymphatic system is incomplete. Nevertheless the catecholaminergic nerve fibers of the human mesenteric lymphatic vessels come from the adrenergic periarterial plexuses of the mesenterial arterial bed. NPY-ergic nerve fibers may modulate the microcirculatory mesenterial bed in different pathological conditions.

Intra- and inter-observer reliability of quantitative analysis of the infra-patellar fat pad and comparison between fat- and non-fat-suppressed imaging--Data from the osteoarthritis initiative.

PubMed

Steidle-Kloc, E; Wirth, W; Ruhdorfer, A; Dannhauer, T; Eckstein, F

2016-03-01

The infra-patellar fat pad (IPFP), as intra-articular adipose tissue represents a potential source of pro-inflammatory cytokines and its size has been suggested to be associated with osteoarthritis (OA) of the knee. This study examines inter- and intra-observer reliability of fat-suppressed (fs) and non-fat-suppressed (nfs) MR imaging for determination of IPFP morphological measurements as novel biomarkers. The IPFP of nine right knees of healthy Osteoarthritis Initiative participants was segmented by five readers, using fs and nfs baseline sagittal MRIs. The intra-observer reliability was determined from baseline and 1-year follow-up images. All segmentations were quality controlled (QC) by an expert reader. Reliability was expressed as root mean square coefficient of variation (RMS CV%). After QC, the inter-observer reliability for fs (nfs) imaging was 2.0% (1.1%) for IPFP volume, 2.1%/2.5% (1.6%/1.8%) for anterior/posterior surface areas, 1.8% (1.8%) for depth, and 2.1% (2.4%) for maximum sagittal area. The intra-observer reliability was 3.1% (5.0%) for volume, 2.3%/2.8% (2.5%/2.9%) for anterior/posterior surfaces, 1.9% (3.5%) for depth, and 3.3% (4.5%) for maximum sagittal area. IPFP volume from nfs images was systematically greater (+7.3%) than from fs images, but highly correlated (r=0.98). The results suggest that quantitative measurements of IPFP morphology can be performed with satisfactory reliability when expert QC is implemented. The IPFP is more clearly depicted in nfs images, and there is a small systematic off-set versus analysis from fs images. However, the high linear relationship between fs and nfs imaging suggests that fs images can be used to analyze IPFP morphology, when nfs images are not available. Copyright © 2015 Elsevier GmbH. All rights reserved.

Morphology and morphometry of fetal liver at 16-26 weeks of gestation by magnetic resonance imaging: Comparison with embryonic liver at Carnegie stage 23.

PubMed

Hamabe, Yui; Hirose, Ayumi; Yamada, Shigehito; Uwabe, Chigako; Okada, Tomohisa; Togashi, Kaori; Kose, Katsumi; Takakuwa, Tetsuya

2013-06-01

Normal liver growth was described morphologically and morphometrically using magnetic resonance imaging (MRI) data of human fetuses, and compared with embryonic liver to establish a normal reference chart for clinical use. MRI images from 21 fetuses at 16-26 weeks of gestation and eight embryos at Carnegie stage (CS)23 were investigated in the present study. Using the image data, the morphology of the liver as well as its adjacent organs was extracted and reconstructed three-dimensionally. Morphometry of fetal liver growth was performed using simple regression analysis. The fundamental morphology was similar in all cases of the fetal livers examined. The liver tended to grow along the transversal axis. The four lobes were clearly recognizable in the fetal liver but not in the embryonic liver. The length of the liver along the three axes, liver volume and four lobes correlated with the bodyweight (BW). The morphogenesis of the fetal liver on the dorsal and caudal sides was affected by the growth of the abdominal organs, such as the stomach, duodenum and spleen, and retroperitoneal organs, such as the right adrenal gland and right kidney. The main blood vessels such as inferior vena cava, portal vein and umbilical vein made a groove on the surface of the liver. Morphology of the fetal liver was different from that of the embryonic liver at CS23. The present data will be useful for evaluating the development of the fetal liver and the adjacent organs that affect its morphology. © 2012 The Japan Society of Hepatology.

Practical considerations of image analysis and quantification of signal transduction IHC staining.

PubMed

Grunkin, Michael; Raundahl, Jakob; Foged, Niels T

2011-01-01

The dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations. However, immunohistochemistry is a multistep procedure including a lot of technical pitfalls leading to intra- and interlaboratory variability of its outcome. The resulting variations in staining intensity and disruption of original morphology are an extra challenge for the image analysis software, which therefore preferably should be dedicated to the detection and quantification of histomorphometrical end points.

Analysis of the Tail Structures of Comet 1P/Halley 1910 II

NASA Astrophysics Data System (ADS)

Voelzke, Marcos Rincon

2013-11-01

For the purpose of identifying, measuring, and correlating the morphological structures along the plasma tail of 1P/Halley, 886 images from September 1909 to May 1911 are analysed. These images are from the Atlas of Comet Halley 1910 II (DONN; RAHE; BRANDT, 1986).

Automated Image Registration Using Morphological Region of Interest Feature Extraction

NASA Technical Reports Server (NTRS)

Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2005-01-01

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Retinal imaging and image analysis.

PubMed

Abràmoff, Michael D; Garvin, Mona K; Sonka, Milan

2010-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.

Retinal Imaging and Image Analysis

PubMed Central

Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

2011-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

Masks in Imaging Flow Cytometry

PubMed Central

Dominical, Venina; Samsel, Leigh; McCoy, J. Philip

2016-01-01

Data analysis in imaging flow cytometry incorporates elements of flow cytometry together with other aspects of morphological analysis of images. A crucial early step in this analysis is the creation of a mask to distinguish the portion of the image upon which further examination of specified features can be performed. Default masks are provided by the manufacturer of the imaging flow cytometer but additional custom masks can be created by the individual user for specific applications. Flawed or inaccurate masks can have a substantial negative impact on the overall analysis of a sample, thus great care must be taken to ensure the accuracy of masks. Here we discuss various types of masks and cite examples of their use. Furthermore we provide our insight for how to approach selecting and assessing the optimal mask for a specific analysis. PMID:27461256

A Multivariate Analysis of Unilateral Cleft Lip and Palate Facial Skeletal Morphology.

PubMed

Starbuck, John M; Ghoneima, Ahmed; Kula, Katherine

2015-07-01

Unilateral cleft lip and palate (UCLP) occurs when the maxillary and nasal facial prominences fail to fuse correctly during development, resulting in a palatal cleft and clefted soft and hard tissues of the dentoalveolus. The UCLP deformity may compromise an individual's ability to eat, chew, and speak. In this retrospective cross-sectional study, cone beam computed tomography (CBCT) images of 7-17-year-old individuals born with UCLP (n = 24) and age- and sex-matched controls (n = 24) were assessed. Coordinate values of three-dimensional anatomical landmarks (n = 32) were recorded from each CBCT image. Data were evaluated using principal coordinates analysis (PCOORD) and Euclidean distance matrix analysis (EDMA). Approximately 40% of morphometric variation is captured by PCOORD axes 1-3, and the negative and positive ends of each axis are associated with specific patterns of morphological differences. Approximately 36% of facial skeletal measures significantly differ by confidence interval testing (α = 0.10) between samples. Although significant form differences occur across the facial skeleton, strong patterns of morphological differences were localized to the lateral and superioinferior aspects of the nasal aperture, particularly on the clefted side of the face. The UCLP deformity strongly influences facial skeletal morphology of the midface and oronasal facial regions, and to a lesser extent the upper and lower facial skeletons. The pattern of strong morphological differences in the oronasal region combined with differences across the facial complex suggests that craniofacial bones are integrated and covary, despite influences from the congenital cleft.

SEM Imaging and Chemical Analysis of Aerosol Particles from Surface and Hi-altitudes in New Jersey.

NASA Astrophysics Data System (ADS)

Bandamede, M.; Boaggio, K.; Bancroft, L.; Hurler, K.; Magee, N. B.

2016-12-01

We report on Scanning Electron Microscopy analysis of aerosol particle morphology and chemistry. The work includes the first comparative SEM analysis of aerosol particles captured by balloon at high altitude. The particles were acquired in an urban/suburban environment in central New-Jersey. Particles were sampled from near the surface using ambient air filtration and at high-altitudes using a novel balloon-borne instrument (ICE-Ball, see abstract by K. Boaggio). Particle images and 3D geometry are acquired by a Hitachi SU-5000 SEM, with resolution to approximately 3 nm. Elemental analysis on particles is provided by Energy Dispersive X-Ray Spectroscopy (EDS, EDAX, Inc.). Uncoated imaging is conducted in low vacuum within the variable-pressure SEM, which provides improved detection and analysis of light-element compositions including Carbon. Preliminary results suggest that some similar particle types and chemical species are sampled at both surface and high-altitude. However, as expected, particle morphologies, concentrations, chemistry, and apparent origin vary significantly at different altitudes and under different atmospheric flow regimes. Improved characterization of high-altitude aerosol particles, and differences from surface particulate composition, may advance inputs for atmospheric cloud and radiation models.

Patellofemoral morphology is not related to pain using three-dimensional quantitative analysis in an older population: data from the Osteoarthritis Initiative

PubMed Central

Drew, Benjamin T.; Bowes, Michael A.; Redmond, Anthony C.; Dube, Bright; Kingsbury, Sarah R.; Conaghan, Philip G.

2017-01-01

Abstract Objectives Current structural associations of patellofemoral pain (PFP) are based on 2D imaging methodology with inherent measurement uncertainty due to positioning and rotation. This study employed novel technology to create 3D measures of commonly described patellofemoral joint imaging features and compared these features in people with and without PFP in a large cohort. Methods We compared two groups from the Osteoarthritis Initiative: one with localized PFP and pain on stairs, and a control group with no knee pain; both groups had no radiographic OA. MRI bone surfaces were automatically segmented and aligned using active appearance models. We applied t-tests, logistic regression and linear discriminant analysis to compare 13 imaging features (including patella position, trochlear morphology, facet area and tilt) converted into 3D equivalents, and a measure of overall 3D shape. Results One hundred and fifteen knees with PFP (mean age 59.7, BMI 27.5 kg/m2, female 58.2%) and 438 without PFP (mean age 63.6, BMI 26.9 kg/m2, female 52.9%) were included. After correction for multiple testing, no statistically significant differences were found between groups for any of the 3D imaging features or their combinations. A statistically significant discrimination was noted for overall 3D shape between genders, confirming the validity of the 3D measures. Conclusion Challenging current perceptions, no differences in patellofemoral morphology were found between older people with and without PFP using 3D quantitative imaging analysis. Further work is needed to see if these findings are replicated in a younger PFP population. PMID:28968747

Patellofemoral morphology is not related to pain using three-dimensional quantitative analysis in an older population: data from the Osteoarthritis Initiative.

PubMed

Drew, Benjamin T; Bowes, Michael A; Redmond, Anthony C; Dube, Bright; Kingsbury, Sarah R; Conaghan, Philip G

2017-12-01

Current structural associations of patellofemoral pain (PFP) are based on 2D imaging methodology with inherent measurement uncertainty due to positioning and rotation. This study employed novel technology to create 3D measures of commonly described patellofemoral joint imaging features and compared these features in people with and without PFP in a large cohort. We compared two groups from the Osteoarthritis Initiative: one with localized PFP and pain on stairs, and a control group with no knee pain; both groups had no radiographic OA. MRI bone surfaces were automatically segmented and aligned using active appearance models. We applied t-tests, logistic regression and linear discriminant analysis to compare 13 imaging features (including patella position, trochlear morphology, facet area and tilt) converted into 3D equivalents, and a measure of overall 3D shape. One hundred and fifteen knees with PFP (mean age 59.7, BMI 27.5 kg/m2, female 58.2%) and 438 without PFP (mean age 63.6, BMI 26.9 kg/m2, female 52.9%) were included. After correction for multiple testing, no statistically significant differences were found between groups for any of the 3D imaging features or their combinations. A statistically significant discrimination was noted for overall 3D shape between genders, confirming the validity of the 3D measures. Challenging current perceptions, no differences in patellofemoral morphology were found between older people with and without PFP using 3D quantitative imaging analysis. Further work is needed to see if these findings are replicated in a younger PFP population. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology.

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

PubMed

Boix, Macarena; Cantó, Begoña

2013-04-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

Shape-Constrained Segmentation Approach for Arctic Multiyear Sea Ice Floe Analysis

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Brucker, Ludovic; Ivanoff, Alvaro; Tilton, James C.

2013-01-01

The melting of sea ice is correlated to increases in sea surface temperature and associated climatic changes. Therefore, it is important to investigate how rapidly sea ice floes melt. For this purpose, a new Tempo Seg method for multi temporal segmentation of multi year ice floes is proposed. The microwave radiometer is used to track the position of an ice floe. Then,a time series of MODIS images are created with the ice floe in the image center. A Tempo Seg method is performed to segment these images into two regions: Floe and Background.First, morphological feature extraction is applied. Then, the central image pixel is marked as Floe, and shape-constrained best merge region growing is performed. The resulting tworegionmap is post-filtered by applying morphological operators.We have successfully tested our method on a set of MODIS images and estimated the area of a sea ice floe as afunction of time.

The Use of Multidimensional Image-Based Analysis to Accurately Monitor Cell Growth in 3D Bioreactor Culture

PubMed Central

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells. PMID:22028809

The use of multidimensional image-based analysis to accurately monitor cell growth in 3D bioreactor culture.

PubMed

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells.

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.

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

PubMed Central

BahadarKhan, Khan; A Khaliq, Amir; Shahid, Muhammad

2016-01-01

Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts. PMID:27441646

Evaluation of Fine Aggregate Morphology by Image Method and Its Effect on Skid-Resistance of Micro-Surfacing.

PubMed

Xiao, Yue; Wang, Feng; Cui, Peide; Lei, Lei; Lin, Juntao; Yi, Mingwei

2018-05-29

Micro-surfacing is a widely used pavement preventive maintenance technology used all over the world, due to its advantages of fast construction, low maintenance cost, good waterproofness, and skid-resistance performance. This study evaluated the fine aggregate morphology and surface texture of micro-surfacing by AIMS (aggregate image measurement system), and explored the effect of aggregate morphology on skid-resistance of single-grade micro-surfacing. Sand patch test and British pendulum test were also used to detect skid-resistance for comparison with the image-based method. Wet abrasion test was used to measure skid-resistance durability for feasibility verification of single-grade micro-surfacing. The results show that the effect of Form2D on the skid-resistance of micro-surfacing is much stronger than that of angularity. Combining the feasibility analysis of durability and skid-resistance, 1.18⁻2.36 grade micro-surfacing meets the requirements of durability and skid-resistance at the same time. This study also determined that, compared with British pendulum test, the texture result obtained by sand patch test fits better with results of image method.

Morphological imaging and quantification of axial xylem tissue in Fraxinus excelsior L. through X-ray micro-computed tomography.

PubMed

Koddenberg, Tim; Militz, Holger

2018-05-05

The popularity of X-ray based imaging methods has continued to increase in research domains. In wood research, X-ray micro-computed tomography (XμCT) is useful for structural studies examining the three-dimensional and complex xylem tissue of trees qualitatively and quantitatively. In this study, XμCT made it possible to visualize and quantify the spatial xylem organization of the angiosperm species Fraxinus excelsior L. on the microscopic level. Through image analysis, it was possible to determine morphological characteristics of the cellular axial tissue (vessel elements, fibers, and axial parenchyma cells) three-dimensionally. X-ray imaging at high resolutions provides very distinct visual insight into the xylem structure. Numerical analyses performed through semi-automatic procedures made it possible to quickly quantify cell characteristics (length, diameter, and volume of cells). Use of various spatial resolutions (0.87-5 μm) revealed boundaries users should be aware of. Nevertheless, our findings, both qualitative and quantitative, demonstrate XμCT to be a valuable tool for studying the spatial cell morphology of F. excelsior. Copyright © 2018. Published by Elsevier Ltd.

Spectral interferometry for morphological imaging in in vitro fertilization (IVF) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhu, Yizheng; Li, Chengshuai

2016-03-01

Morphological assessment of spermatozoa is of critical importance for in vitro fertilization (IVF), especially intracytoplasmic sperm injection (ICSI)-based IVF. In ICSI, a single sperm cell is selected and injected into an egg to achieve fertilization. The quality of the sperm cell is found to be highly correlated to IVF success. Sperm morphology, such as shape, head birefringence and motility, among others, are typically evaluated under a microscope. Current observation relies on conventional techniques such as differential interference contrast microscopy and polarized light microscopy. Their qualitative nature, however, limits the ability to provide accurate quantitative analysis. Here, we demonstrate quantitative morphological measurement of sperm cells using two types of spectral interferometric techniques, namely spectral modulation interferometry and spectral multiplexing interferometry. Both are based on spectral-domain low coherence interferometry, which is known for its exquisite phase determination ability. While spectral modulation interferometry encodes sample phase in a single spectrum, spectral multiplexing interferometry does so for sample birefringence. Therefore they are capable of highly sensitive phase and birefringence imaging. These features suit well in the imaging of live sperm cells, which are small, dynamic objects with only low to moderate levels of phase and birefringence contrast. We will introduce the operation of both techniques and demonstrate their application to measuring the phase and birefringence morphology of sperm cells.

Image analysis of open-door laminoplasty for cervical spondylotic myelopathy: comparing the influence of cord morphology and spine alignment.

PubMed

Lin, Bon-Jour; Lin, Meng-Chi; Lin, Chin; Lee, Meei-Shyuan; Feng, Shao-Wei; Ju, Da-Tong; Ma, Hsin-I; Liu, Ming-Ying; Hueng, Dueng-Yuan

2015-10-01

Previous studies have identified the factors affecting the surgical outcome of cervical spondylotic myelopathy (CSM) following laminoplasty. Nonetheless, the effect of these factors remains controversial. It is unknown about the association between pre-operative cervical spinal cord morphology and post-operative imaging result following laminoplasty. The goal of this study is to analyze the impact of pre-operative cervical spinal cord morphology on post-operative imaging in patients with CSM. Twenty-six patients with CSM undergoing open-door laminoplasty were classified according to pre-operative cervical spine bony alignment and cervical spinal cord morphology, and the results were evaluated in terms of post-operative spinal cord posterior drift, and post-operative expansion of the antero-posterior dura diameter. By the result of study, pre-operative spinal cord morphology was an effective classification in predicting surgical outcome - patients with anterior convexity type, description of cervical spinal cord morphology, had more spinal cord posterior migration than those with neutral or posterior convexity type after open-door laminoplasty. Otherwise, the interesting finding was that cervical spine Cobb's angle had an impact on post-operative spinal cord posterior drift in patients with neutral or posterior convexity type spinal cord morphology - the degree of kyphosis was inversely proportional to the distance of post-operative spinal cord posterior drift, but not in the anterior convexity type. These findings supported that pre-operative cervical spinal cord morphology may be used as screening for patients undergoing laminoplasty. Patients having neutral or posterior convexity type spinal cord morphology accompanied with kyphotic deformity were not suitable candidates for laminoplasty. Copyright © 2015 Elsevier B.V. All rights reserved.

3D morphological analysis of the mouse cerebral vasculature: Comparison of in vivo and ex vivo methods

PubMed Central

Steinman, Joe; Koletar, Margaret M.; Stefanovic, Bojana; Sled, John G.

2017-01-01

Ex vivo 2-photon fluorescence microscopy (2PFM) with optical clearing enables vascular imaging deep into tissue. However, optical clearing may also produce spherical aberrations if the objective lens is not index-matched to the clearing material, while the perfusion, clearing, and fixation procedure may alter vascular morphology. We compared in vivo and ex vivo 2PFM in mice, focusing on apparent differences in microvascular signal and morphology. Following in vivo imaging, the mice (four total) were perfused with a fluorescent gel and their brains fructose-cleared. The brain regions imaged in vivo were imaged ex vivo. Vessels were segmented in both images using an automated tracing algorithm that accounts for the spatially varying PSF in the ex vivo images. This spatial variance is induced by spherical aberrations caused by imaging fructose-cleared tissue with a water-immersion objective. Alignment of the ex vivo image to the in vivo image through a non-linear warping algorithm enabled comparison of apparent vessel diameter, as well as differences in signal. Shrinkage varied as a function of diameter, with capillaries rendered smaller ex vivo by 13%, while penetrating vessels shrunk by 34%. The pial vasculature attenuated in vivo microvascular signal by 40% 300 μm below the tissue surface, but this effect was absent ex vivo. On the whole, ex vivo imaging was found to be valuable for studying deep cortical vasculature. PMID:29053753

A three-dimensional image processing program for accurate, rapid, and semi-automated segmentation of neuronal somata with dense neurite outgrowth

PubMed Central

Ross, James D.; Cullen, D. Kacy; Harris, James P.; LaPlaca, Michelle C.; DeWeerth, Stephen P.

2015-01-01

Three-dimensional (3-D) image analysis techniques provide a powerful means to rapidly and accurately assess complex morphological and functional interactions between neural cells. Current software-based identification methods of neural cells generally fall into two applications: (1) segmentation of cell nuclei in high-density constructs or (2) tracing of cell neurites in single cell investigations. We have developed novel methodologies to permit the systematic identification of populations of neuronal somata possessing rich morphological detail and dense neurite arborization throughout thick tissue or 3-D in vitro constructs. The image analysis incorporates several novel automated features for the discrimination of neurites and somata by initially classifying features in 2-D and merging these classifications into 3-D objects; the 3-D reconstructions automatically identify and adjust for over and under segmentation errors. Additionally, the platform provides for software-assisted error corrections to further minimize error. These features attain very accurate cell boundary identifications to handle a wide range of morphological complexities. We validated these tools using confocal z-stacks from thick 3-D neural constructs where neuronal somata had varying degrees of neurite arborization and complexity, achieving an accuracy of ≥95%. We demonstrated the robustness of these algorithms in a more complex arena through the automated segmentation of neural cells in ex vivo brain slices. These novel methods surpass previous techniques by improving the robustness and accuracy by: (1) the ability to process neurites and somata, (2) bidirectional segmentation correction, and (3) validation via software-assisted user input. This 3-D image analysis platform provides valuable tools for the unbiased analysis of neural tissue or tissue surrogates within a 3-D context, appropriate for the study of multi-dimensional cell-cell and cell-extracellular matrix interactions. PMID:26257609

Intra- and inter-observer reliability of quantitative analysis of the infra-patellar fat pad and comparison between fat- and non-fat-suppressed imaging—Data from the osteoarthritis initiative

PubMed Central

Steidle-Kloc, E.; Wirth, W.; Ruhdorfer, A.; Dannhauer, T.; Eckstein, F.

2015-01-01

The infra-patellar fat pad (IPFP), as intra-articular adipose tissue represents a potential source of pro-inflammatory cytokines and its size has been suggested to be associated with osteoarthritis (OA) of the knee. This study examines inter- and intra-observer reliability of fat-suppressed (fs) and non-fat-suppressed (nfs) MR imaging for determination of IPFP morphological measurements as novel biomarkers. The IPFP of nine right knees of healthy Osteoarthritis Initiative participants was segmented by five readers, using fs and nfs baseline sagittal MRIs. The intra-observer reliability was determined from baseline and 1-year follow-up images. All segmentations were quality controlled (QC) by an expert reader. Reliability was expressed as root mean square coefficient of variation (RMS CV%). After QC, the inter-observer reliability for fs (nfs) imaging was 2.0% (1.1%) for IPFP volume, 2.1%/2.5% (1.6%/1.8%) for anterior/posterior surface areas, 1.8% (1.8%) for depth, and 2.1% (2.4%) for maximum sagittal area. The intra-observer reliability was 3.1% (5.0%) for volume, 2.3%/2.8% (2.5%/2.9%) for anterior/posterior surfaces, 1.9% (3.5%) for depth, and 3.3% (4.5%) for maximum sagittal area. IPFP volume from nfs images was systematically greater (+7.3%) than from fs images, but highly correlated (r = 0.98). The results suggest that quantitative measurements of IPFP morphology can be performed with satisfactory reliability when expert QC is implemented. The IPFP is more clearly depicted in nfs images, and there is a small systematic off-set versus analysis from fs images. However, the high linear relationship between fs and nfs imaging suggests that fs images can be used to analyze IPFP morphology, when nfs images are not available. PMID:26569532

Adaptive thresholding image series from fluorescence confocal scanning laser microscope using orientation intensity profiles

NASA Astrophysics Data System (ADS)

Feng, Judy J.; Ip, Horace H.; Cheng, Shuk H.

2004-05-01

Many grey-level thresholding methods based on histogram or other statistic information about the interest image such as maximum entropy and so on have been proposed in the past. However, most methods based on statistic analysis of the images concerned little about the characteristics of morphology of interest objects, which sometimes could provide very important indication which can help to find the optimum threshold, especially for those organisms which have special texture morphologies such as vasculature, neuro-network etc. in medical imaging. In this paper, we propose a novel method for thresholding the fluorescent vasculature image series recorded from Confocal Scanning Laser Microscope. After extracting the basic orientation of the slice of vessels inside a sub-region partitioned from the images, we analysis the intensity profiles perpendicular to the vessel orientation to get the reasonable initial threshold for each region. Then the threshold values of those regions near the interest one both in x-y and optical directions have been referenced to get the final result of thresholds of the region, which makes the whole stack of images look more continuous. The resulting images are characterized by suppressing both noise and non-interest tissues conglutinated to vessels, while improving the vessel connectivities and edge definitions. The value of the method for idealized thresholding the fluorescence images of biological objects is demonstrated by a comparison of the results of 3D vascular reconstruction.

Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

PubMed Central

Lu, Zhaolin

2017-01-01

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. PMID:28298925

Automatic detection of micro-aneurysms in retinal images based on curvelet transform and morphological operations

NASA Astrophysics Data System (ADS)

Mohammad Alipour, Shirin Hajeb; Rabbani, Hossein

2013-09-01

Diabetic retinopathy (DR) is one of the major complications of diabetes that changes the blood vessels of the retina and distorts patient vision that finally in high stages can lead to blindness. Micro-aneurysms (MAs) are one of the first pathologies associated with DR. The number and the location of MAs are very important in grading of DR. Early diagnosis of micro-aneurysms (MAs) can reduce the incidence of blindness. As MAs are tiny area of blood protruding from vessels in the retina and their size is about 25 to 100 microns, automatic detection of these tiny lesions is still challenging. MAs occurring in the macula can lead to visual loss. Also the position of a lesion such as MAs relative to the macula is a useful feature for analysis and classification of different stages of DR. Because MAs are more distinguishable in fundus fluorescin angiography (FFA) compared to color fundus images, we introduce a new method based on curvelet transform and morphological operations for MAs detection in FFA images. As vessels and MAs are the bright parts of FFA image, firstly extracted vessels by curvelet transform are removed from image. Then morphological operations are applied on resulted image for detecting MAs.

Morphology filter bank for extracting nodular and linear patterns in medical images.

PubMed

Hashimoto, Ryutaro; Uchiyama, Yoshikazu; Uchimura, Keiichi; Koutaki, Gou; Inoue, Tomoki

2017-04-01

Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images. We have developed a morphology filter bank that creates multiresolution representations of an image. Analysis bank of this filter bank produces nodular and linear patterns at each resolution level. Synthesis bank can then be used to perfectly reconstruct the original image from these decomposed patterns. Our proposed method shows better performance based on a quantitative evaluation using a synthesized image compared with a conventional method based on a Hessian matrix, often used to enhance nodular and linear patterns. In addition, experiments show that our method can be applied to the followings: (1) microcalcifications of various sizes in mammograms can be extracted, (2) blood vessels of various sizes in retinal fundus images can be extracted, and (3) thoracic CT images can be reconstructed while removing normal vessels. Our proposed method is useful for extracting nodular and linear shadows or removing normal structures in medical images.

Development of image analysis software for quantification of viable cells in microchips.

PubMed

Georg, Maximilian; Fernández-Cabada, Tamara; Bourguignon, Natalia; Karp, Paola; Peñaherrera, Ana B; Helguera, Gustavo; Lerner, Betiana; Pérez, Maximiliano S; Mertelsmann, Roland

2018-01-01

Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way.

The gastro-esophageal reflux barrier: biophysical analysis on 3D models of anatomy from magnetic resonance imaging.

PubMed

Roy, S; Fox, M R; Curcic, J; Schwizer, W; Pal, A

2012-07-01

The function and structure of the gastro-esophageal junction (GEJ) determine its efficacy as a reflux barrier. This study presents a novel methodology for the quantitative assessment of GEJ and proximal gastric morphology from magnetic resonance (MR) imaging. Based on this data we propose a new conceptualization of the hypothesis that a flap valve mechanism contributes to reflux protection. 3D models of the GEJ and proximal stomach were reconstructed from MR images in 12 healthy volunteers during respiration and on eating a test meal to maximum satiation. A rotating plane analysis measured the gastro-esophageal insertion angle and span of contact. An ellipsoid fit provided quantitative assessment of gastric shape and orientation relative to a fixed anatomical reference point. Position of the esophageal insertion on the 'gastric ellipse' was noted. An ellipsoid-cylinder model was designed to analyze the relationships among parameters describing the GEJ morphology. The insertion angle became more acute on expiration, but did not change with meal ingestion. In contrast the span of contact did not vary with respiration, but increased with gastric filling. Changes in gastric morphology with distension further augmented the span of gastro-esophageal contact in almost 70% of the studies. Novel MR imaging and biophysical analysis of the GEJ and proximal stomach provide a quantitative description of structures contributing to the reflux barrier. Changes in these parameters during respiration and on eating support the hypothesis that structural components of a functional 'flap valve' like mechanism contribute to reflux protection. © 2012 Blackwell Publishing Ltd.

Semi-Automated Digital Image Analysis of Pick’s Disease and TDP-43 Proteinopathy

PubMed Central

Irwin, David J.; Byrne, Matthew D.; McMillan, Corey T.; Cooper, Felicia; Arnold, Steven E.; Lee, Edward B.; Van Deerlin, Vivianna M.; Xie, Sharon X.; Lee, Virginia M.-Y.; Grossman, Murray; Trojanowski, John Q.

2015-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick’s disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. PMID:26538548

Semi-Automated Digital Image Analysis of Pick's Disease and TDP-43 Proteinopathy.

PubMed

Irwin, David J; Byrne, Matthew D; McMillan, Corey T; Cooper, Felicia; Arnold, Steven E; Lee, Edward B; Van Deerlin, Vivianna M; Xie, Sharon X; Lee, Virginia M-Y; Grossman, Murray; Trojanowski, John Q

2016-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick's disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. © The Author(s) 2015.

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.

Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

Supervised graph hashing for histopathology image retrieval and classification.

PubMed

Shi, Xiaoshuang; Xing, Fuyong; Xu, KaiDi; Xie, Yuanpu; Su, Hai; Yang, Lin

2017-12-01

In pathology image analysis, morphological characteristics of cells are critical to grade many diseases. With the development of cell detection and segmentation techniques, it is possible to extract cell-level information for further analysis in pathology images. However, it is challenging to conduct efficient analysis of cell-level information on a large-scale image dataset because each image usually contains hundreds or thousands of cells. In this paper, we propose a novel image retrieval based framework for large-scale pathology image analysis. For each image, we encode each cell into binary codes to generate image representation using a novel graph based hashing model and then conduct image retrieval by applying a group-to-group matching method to similarity measurement. In order to improve both computational efficiency and memory requirement, we further introduce matrix factorization into the hashing model for scalable image retrieval. The proposed framework is extensively validated with thousands of lung cancer images, and it achieves 97.98% classification accuracy and 97.50% retrieval precision with all cells of each query image used. Copyright © 2017 Elsevier B.V. All rights reserved.

A data model and database for high-resolution pathology analytical image informatics.

PubMed

Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

2011-01-01

The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming increasingly feasible for basic, clinical, and translational research studies to produce thousands of whole-slide images. Systematic analysis of these large datasets requires efficient data management support for representing and indexing results from hundreds of interrelated analyses generating very large volumes of quantifications such as shape and texture and of classifications of the quantified features. We have designed a data model and a database to address the data management requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines. The data model represents virtual slide related image, annotation, markup and feature information. The database supports a wide range of metadata and spatial queries on images, annotations, markups, and features. We currently have three databases running on a Dell PowerEdge T410 server with CentOS 5.5 Linux operating system. The database server is IBM DB2 Enterprise Edition 9.7.2. The set of databases consists of 1) a TMA database containing image analysis results from 4740 cases of breast cancer, with 641 MB storage size; 2) an algorithm validation database, which stores markups and annotations from two segmentation algorithms and two parameter sets on 18 selected slides, with 66 GB storage size; and 3) an in silico brain tumor study database comprising results from 307 TCGA slides, with 365 GB storage size. The latter two databases also contain human-generated annotations and markups for regions and nuclei. Modeling and managing pathology image analysis results in a database provide immediate benefits on the value and usability of data in a research study. The database provides powerful query capabilities, which are otherwise difficult or cumbersome to support by other approaches such as programming languages. Standardized, semantic annotated data representation and interfaces also make it possible to more efficiently share image data and analysis results.

3D confocal Raman imaging of oil-rich emulsion from enzyme-assisted aqueous extraction of extruded soybean powder.

PubMed

Wu, Longkun; Wang, Limin; Qi, Baokun; Zhang, Xiaonan; Chen, Fusheng; Li, Yang; Sui, Xiaonan; Jiang, Lianzhou

2018-05-30

The understanding of the structure morphology of oil-rich emulsion from enzyme-assisted extraction processing (EAEP) was a critical step to break the oil-rich emulsion structure in order to recover oil. Albeit EAEP method has been applied as an alternative way to conventional solvent extraction method, the structure morphology of oil-rich emulsion was still unclear. The current study aimed to investigate the structure morphology of oil-rich emulsion from EAEP using 3D confocal Raman imaging technique. With increasing the enzymatic hydrolysis duration from 1 to 3 h, the stability of oil-rich emulsion was decreased as visualized in the 3D confocal Raman images that the protein and oil were mixed together. The subsequent Raman spectrum analysis further revealed that the decreased stability of oil-rich emulsion was due to the protein aggregations via SS bonds or protein-lipid interactions. The conformational transfer in protein indicated the formation of a compact structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantification of Dynamic Morphological Drug Responses in 3D Organotypic Cell Cultures by Automated Image Analysis

PubMed Central

Härmä, Ville; Schukov, Hannu-Pekka; Happonen, Antti; Ahonen, Ilmari; Virtanen, Johannes; Siitari, Harri; Åkerfelt, Malin; Lötjönen, Jyrki; Nees, Matthias

2014-01-01

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation. PMID:24810913

Multispectral image restoration of historical documents based on LAAMs and mathematical morphology

NASA Astrophysics Data System (ADS)

Lechuga-S., Edwin; Valdiviezo-N., Juan C.; Urcid, Gonzalo

2014-09-01

This research introduces an automatic technique designed for the digital restoration of the damaged parts in historical documents. For this purpose an imaging spectrometer is used to acquire a set of images in the wavelength interval from 400 to 1000 nm. Assuming the presence of linearly mixed spectral pixels registered from the multispectral image, our technique uses two lattice autoassociative memories to extract the set of pure pigments conforming a given document. Through an spectral unmixing analysis, our method produces fractional abundance maps indicating the distributions of each pigment in the scene. These maps are then used to locate cracks and holes in the document under study. The restoration process is performed by the application of a region filling algorithm, based on morphological dilation, followed by a color interpolation to restore the original appearance of the filled areas. This procedure has been successfully applied to the analysis and restoration of three multispectral data sets: two corresponding to artificially superimposed scripts and a real data acquired from a Mexican pre-Hispanic codex, whose restoration results are presented.

Analysis of Cryokarstic Surface Patterns on Debris Aprons at the Mid-Latitudes of Mars

NASA Astrophysics Data System (ADS)

Orgel, Cs.

2011-03-01

This work focuses on the morphological analysis of the surface patterns (mounds, furrows, craters) and surface types (smooth surface, corn-like surface, polygonal mantling material, brain-like texture) on debris apron surfaces using HiRISE’s images.

Discerning mild cognitive impairment and Alzheimer Disease from normal aging: morphologic characterization based on univariate and multivariate models.

PubMed

Liao, Weiqi; Long, Xiaojing; Jiang, Chunxiang; Diao, Yanjun; Liu, Xin; Zheng, Hairong; Zhang, Lijuan

2014-05-01

Differentiating mild cognitive impairment (MCI) and Alzheimer Disease (AD) from healthy aging remains challenging. This study aimed to explore the cerebral structural alterations of subjects with MCI or AD as compared to healthy elderly based on the individual and collective effects of cerebral morphologic indices using univariate and multivariate analyses. T1-weighted images (T1WIs) were retrieved from Alzheimer Disease Neuroimaging Initiative database for 116 subjects who were categorized into groups of healthy aging, MCI, and AD. Analysis of covariance (ANCOVA) and multivariate analysis of covariance (MANCOVA) were performed to explore the intergroup morphologic alterations indexed by surface area, curvature index, cortical thickness, and subjacent white matter volume with age and sex controlled as covariates, in 34 parcellated gyri regions of interest (ROIs) for both cerebral hemispheres based on the T1WI. Statistical parameters were mapped on the anatomic images to facilitate visual inspection. Global rather than region-specific structural alterations were revealed in groups of MCI and AD relative to healthy elderly using MANCOVA. ANCOVA revealed that the cortical thickness decreased more prominently in entorhinal, temporal, and cingulate cortices and was positively correlated with patients' cognitive performance in AD group but not in MCI. The temporal lobe features marked atrophy of white matter during the disease dynamics. Significant intercorrelations were observed among the morphologic indices with univariate analysis for given ROIs. Significant global structural alterations were identified in MCI and AD based on MANCOVA model with improved sensitivity. The intercorrelation among the morphologic indices may dampen the use of individual morphological parameter in featuring cerebral structural alterations. Decrease in cortical thickness is not reflective of the cognitive performance at the early stage of AD. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Online quantitative analysis of multispectral images of human body tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.

2013-08-01

A method is developed for online monitoring of structural and morphological parameters of biological tissues (haemoglobin concentration, degree of blood oxygenation, average diameter of capillaries and the parameter characterising the average size of tissue scatterers), which involves multispectral tissue imaging, image normalisation to one of its spectral layers and determination of unknown parameters based on their stable regression relation with the spectral characteristics of the normalised image. Regression is obtained by simulating numerically the diffuse reflectance spectrum of the tissue by the Monte Carlo method at a wide variation of model parameters. The correctness of the model calculations is confirmed by the good agreement with the experimental data. The error of the method is estimated under conditions of general variability of structural and morphological parameters of the tissue. The method developed is compared with the traditional methods of interpretation of multispectral images of biological tissues, based on the solution of the inverse problem for each pixel of the image in the approximation of different analytical models.

Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies.

PubMed

Sun, Wanxin; Chang, Shi; Tai, Dean C S; Tan, Nancy; Xiao, Guangfa; Tang, Huihuan; Yu, Hanry

2008-01-01

Liver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson's trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.

A feasible high spatiotemporal resolution breast DCE-MRI protocol for clinical settings.

PubMed

Tudorica, Luminita A; Oh, Karen Y; Roy, Nicole; Kettler, Mark D; Chen, Yiyi; Hemmingson, Stephanie L; Afzal, Aneela; Grinstead, John W; Laub, Gerhard; Li, Xin; Huang, Wei

2012-11-01

Three dimensional bilateral imaging is the standard for most clinical breast dynamic contrast-enhanced (DCE) MRI protocols. Because of high spatial resolution (sRes) requirement, the typical 1-2 min temporal resolution (tRes) afforded by a conventional full-k-space-sampling gradient echo (GRE) sequence precludes meaningful and accurate pharmacokinetic analysis of DCE time-course data. The commercially available, GRE-based, k-space undersampling and data sharing TWIST (time-resolved angiography with stochastic trajectories) sequence was used in this study to perform DCE-MRI exams on thirty one patients (with 36 suspicious breast lesions) before their biopsies. The TWIST DCE-MRI was immediately followed by a single-frame conventional GRE acquisition. Blinded from each other, three radiologist readers assessed agreements in multiple lesion morphology categories between the last set of TWIST DCE images and the conventional GRE images. Fleiss' κ test was used to evaluate inter-reader agreement. The TWIST DCE time-course data were subjected to quantitative pharmacokinetic analyses. With a four-channel phased-array breast coil, the TWIST sequence produced DCE images with 20 s or less tRes and ~ 1.0×1.0×1.4 mm(3) sRes. There were no significant differences in signal-to-noise (P=.45) and contrast-to-noise (P=.51) ratios between the TWIST and conventional GRE images. The agreements in morphology evaluations between the two image sets were excellent with the intra-reader agreement ranging from 79% for mass margin to 100% for mammographic density and the inter-reader κ value ranging from 0.54 (P<.0001) for lesion size to 1.00 (P<.0001) for background parenchymal enhancement. Quantitative analyses of the DCE time-course data provided higher breast cancer diagnostic accuracy (91% specificity at 100% sensitivity) than the current clinical practice of morphology and qualitative kinetics assessments. The TWIST sequence may be used in clinical settings to acquire high spatiotemporal resolution breast DCE-MRI images for both precise lesion morphology characterization and accurate pharmacokinetic analysis. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools.

PubMed

Babaloukas, Georgios; Tentolouris, Nicholas; Liatis, Stavros; Sklavounou, Alexandra; Perrea, Despoina

2011-12-01

Correction of vignetting on images obtained by a digital camera mounted on a microscope is essential before applying image analysis. The aim of this study is to evaluate three methods for retrospective correction of vignetting on medical microscopy images and compare them with a prospective correction method. One digital image from four different tissues was used and a vignetting effect was applied on each of these images. The resulted vignetted image was replicated four times and in each replica a different method for vignetting correction was applied with fiji and gimp software tools. The highest peak signal-to-noise ratio from the comparison of each method to the original image was obtained from the prospective method in all tissues. The morphological filtering method provided the highest peak signal-to-noise ratio value amongst the retrospective methods. The prospective method is suggested as the method of choice for correction of vignetting and if it is not applicable, then the morphological filtering may be suggested as the retrospective alternative method. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

Multi-Parametric Analysis and Modeling of Relationships between Mitochondrial Morphology and Apoptosis

PubMed Central

Reis, Yara; Wolf, Thomas; Brors, Benedikt; Hamacher-Brady, Anne; Eils, Roland; Brady, Nathan R.

2012-01-01

Mitochondria exist as a network of interconnected organelles undergoing constant fission and fusion. Current approaches to study mitochondrial morphology are limited by low data sampling coupled with manual identification and classification of complex morphological phenotypes. Here we propose an integrated mechanistic and data-driven modeling approach to analyze heterogeneous, quantified datasets and infer relations between mitochondrial morphology and apoptotic events. We initially performed high-content, multi-parametric measurements of mitochondrial morphological, apoptotic, and energetic states by high-resolution imaging of human breast carcinoma MCF-7 cells. Subsequently, decision tree-based analysis was used to automatically classify networked, fragmented, and swollen mitochondrial subpopulations, at the single-cell level and within cell populations. Our results revealed subtle but significant differences in morphology class distributions in response to various apoptotic stimuli. Furthermore, key mitochondrial functional parameters including mitochondrial membrane potential and Bax activation, were measured under matched conditions. Data-driven fuzzy logic modeling was used to explore the non-linear relationships between mitochondrial morphology and apoptotic signaling, combining morphological and functional data as a single model. Modeling results are in accordance with previous studies, where Bax regulates mitochondrial fragmentation, and mitochondrial morphology influences mitochondrial membrane potential. In summary, we established and validated a platform for mitochondrial morphological and functional analysis that can be readily extended with additional datasets. We further discuss the benefits of a flexible systematic approach for elucidating specific and general relationships between mitochondrial morphology and apoptosis. PMID:22272225

Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy

PubMed Central

Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin

2016-01-01

Objectives We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. Methods We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. Results An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. Conclusions The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis. PMID:27525165

Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy.

PubMed

Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin; Sohn, Dae Kyung

2016-07-01

We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.

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.

Description and interpretation of the bracts epidermis of Gramineae (Poaceae) with rotated image with maximum average power spectrum (RIMAPS) technique.

PubMed

Favret, Eduardo A; Fuentes, Néstor O; Molina, Ana M; Setten, Lorena M

2008-10-01

During the last few years, RIMAPS technique has been used to characterize the micro-relief of metallic surfaces and recently also applied to biological surfaces. RIMAPS is an image analysis technique which uses the rotation of an image and calculates its average power spectrum. Here, it is presented as a tool for describing the morphology of the trichodium net found in some grasses, which is developed on the epidermal cells of the lemma. Three different species of grasses (herbarium samples) are analyzed: Podagrostis aequivalvis (Trin.) Scribn. & Merr., Bromidium hygrometricum (Nees) Nees & Meyen and Bromidium ramboi (Parodi) Rúgolo. Simple schemes representing the real microstructure of the lemma are proposed and studied. RIMAPS spectra of both the schemes and the real microstructures are compared. These results allow inferring how similar the proposed geometrical schemes are to the real microstructures. Each geometrical pattern could be used as a reference for classifying other species. Finally, this kind of analysis is used to determine the morphology of the trichodium net of Agrostis breviculmis Hitchc. As the dried sample had shrunk and the microstructure was not clear, two kinds of morphology are proposed for the trichodium net of Agrostis L., one elliptical and the other rectilinear, the former being the most suitable.

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.

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

Morphologic Features of Magnetic Resonance Imaging as a Surrogate of Capsular Contracture in Breast Cancer Patients With Implant-based Reconstructions.

PubMed

Tyagi, Neelam; Sutton, Elizabeth; Hunt, Margie; Zhang, Jing; Oh, Jung Hun; Apte, Aditya; Mechalakos, James; Wilgucki, Molly; Gelb, Emily; Mehrara, Babak; Matros, Evan; Ho, Alice

2017-02-01

Capsular contracture (CC) is a serious complication in patients receiving implant-based reconstruction for breast cancer. Currently, no objective methods are available for assessing CC. The goal of the present study was to identify image-based surrogates of CC using magnetic resonance imaging (MRI). We analyzed a retrospective data set of 50 patients who had undergone both a diagnostic MRI scan and a plastic surgeon's evaluation of the CC score (Baker's score) within a 6-month period after mastectomy and reconstructive surgery. The MRI scans were assessed for morphologic shape features of the implant and histogram features of the pectoralis muscle. The shape features, such as roundness, eccentricity, solidity, extent, and ratio length for the implant, were compared with the Baker score. For the pectoralis muscle, the muscle width and median, skewness, and kurtosis of the intensity were compared with the Baker score. Univariate analysis (UVA) using a Wilcoxon rank-sum test and multivariate analysis with the least absolute shrinkage and selection operator logistic regression was performed to determine significant differences in these features between the patient groups categorized according to their Baker's scores. UVA showed statistically significant differences between grade 1 and grade ≥2 for morphologic shape features and histogram features, except for volume and skewness. Only eccentricity, ratio length, and volume were borderline significant in differentiating grade ≤2 and grade ≥3. Features with P<.1 on UVA were used in the multivariate least absolute shrinkage and selection operator logistic regression analysis. Multivariate analysis showed a good level of predictive power for grade 1 versus grade ≥2 CC (area under the receiver operating characteristic curve 0.78, sensitivity 0.78, and specificity 0.82) and for grade ≤2 versus grade ≥3 CC (area under the receiver operating characteristic curve 0.75, sensitivity 0.75, and specificity 0.79). The morphologic shape features described on MR images were associated with the severity of CC. MRI has the potential to further improve the diagnostic ability of the Baker score in breast cancer patients who undergo implant reconstruction. Copyright © 2016 Elsevier Inc. All rights reserved.

Arsenic distribution and valence state variation studied by fast hierarchical length-scale morphological, compositional, and speciation imaging at the Nanoscopium, Synchrotron Soleil

NASA Astrophysics Data System (ADS)

Somogyi, Andrea; Medjoubi, Kadda; Sancho-Tomas, Maria; Visscher, P. T.; Baranton, Gil; Philippot, Pascal

2017-09-01

The understanding of real complex geological, environmental and geo-biological processes depends increasingly on in-depth non-invasive study of chemical composition and morphology. In this paper we used scanning hard X-ray nanoprobe techniques in order to study the elemental composition, morphology and As speciation in complex highly heterogeneous geological samples. Multivariate statistical analytical techniques, such as principal component analysis and clustering were used for data interpretation. These measurements revealed the quantitative and valance state inhomogeneity of As and its relation to the total compositional and morphological variation of the sample at sub-μm scales.

Morphology selection for cupric oxide thin films by electrodeposition.

PubMed

Dhanasekaran, V; Mahalingam, T; Chandramohan, R

2011-10-01

Polycrystalline cupric oxide thin films were deposited using alkaline solution bath employing cathodic electrodeposition method. The thin films were electrodeposited at various solution pH. The surface morphology and elemental analyzes of the films were studied using scanning electron microscopy (SEM) and energy dispersive X-ray analysis, respectively. SEM studies revealed that the surface morphology could be tailored suitably by adjusting the pH value during deposition. Mesh average on multiple lattice mode atomic force microscopy image was obtained and reported. Copyright © 2011 Wiley-Liss, Inc.

Revealing 3D Ultrastructure and Morphology of Stem Cell Spheroids by Electron Microscopy.

PubMed

Jaros, Josef; Petrov, Michal; Tesarova, Marketa; Hampl, Ales

2017-01-01

Cell culture methods have been developed in efforts to produce biologically relevant systems for developmental and disease modeling, and appropriate analytical tools are essential. Knowledge of ultrastructural characteristics represents the basis to reveal in situ the cellular morphology, cell-cell interactions, organelle distribution, niches in which cells reside, and many more. The traditional method for 3D visualization of ultrastructural components, serial sectioning using transmission electron microscopy (TEM), is very labor-intensive due to contentious TEM slice preparation and subsequent image processing of the whole collection. In this chapter, we present serial block-face scanning electron microscopy, together with complex methodology for spheroid formation, contrasting of cellular compartments, image processing, and 3D visualization. The described technique is effective for detailed morphological analysis of stem cell spheroids, organoids, as well as organotypic cell cultures.

Integral-geometry characterization of photobiomodulation effects on retinal vessel morphology

PubMed Central

Barbosa, Marconi; Natoli, Riccardo; Valter, Kriztina; Provis, Jan; Maddess, Ted

2014-01-01

The morphological characterization of quasi-planar structures represented by gray-scale images is challenging when object identification is sub-optimal due to registration artifacts. We propose two alternative procedures that enhances object identification in the integral-geometry morphological image analysis (MIA) framework. The first variant streamlines the framework by introducing an active contours segmentation process whose time step is recycled as a multi-scale parameter. In the second variant, we used the refined object identification produced in the first variant to perform the standard MIA with exact dilation radius as multi-scale parameter. Using this enhanced MIA we quantify the extent of vaso-obliteration in oxygen-induced retinopathic vascular growth, the preventative effect (by photobiomodulation) of exposure during tissue development to near-infrared light (NIR, 670 nm), and the lack of adverse effects due to exposure to NIR light. PMID:25071966

3.0T MR imaging of the ankle: Axial traction for morphological cartilage evaluation, quantitative T2 mapping and cartilage diffusion imaging-A preliminary study.

PubMed

Jungmann, Pia M; Baum, Thomas; Schaeffeler, Christoph; Sauerschnig, Martin; Brucker, Peter U; Mann, Alexander; Ganter, Carl; Bieri, Oliver; Rummeny, Ernst J; Woertler, Klaus; Bauer, Jan S

2015-08-01

To determine the impact of axial traction during high resolution 3.0T MR imaging of the ankle on morphological assessment of articular cartilage and quantitative cartilage imaging parameters. MR images of n=25 asymptomatic ankles were acquired with and without axial traction (6kg). Coronal and sagittal T1-weighted (w) turbo spin echo (TSE) sequences with a driven equilibrium pulse and sagittal fat-saturated intermediate-w (IMfs) TSE sequences were acquired for morphological evaluation on a four-point scale (1=best, 4=worst). For quantitative assessment of cartilage degradation segmentation was performed on 2D multislice-multiecho (MSME) SE T2, steady-state free-precession (SSFP; n=8) T2 and SSFP diffusion-weighted imaging (DWI; n=8) images. Wilcoxon-tests and paired t-tests were used for statistical analysis. With axial traction, joint space width increased significantly and delineation of cartilage surfaces was rated superior (P<0.05). Cartilage surfaces were best visualized on coronal T1-w images (P<0.05). Differences for cartilage matrix evaluation were smaller. Subchondral bone evaluation, motion artifacts and image quality were not significantly different between the acquisition methods (P>0.05). T2 values were lower at the tibia than at the talus (P<0.001). Reproducibility was better for images with axial traction. Axial traction increased the joint space width, allowed for better visualization of cartilage surfaces and improved compartment discrimination and reproducibility of quantitative cartilage parameters. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Molecular Predictors of 3D Morphogenesis by Breast Cancer Cell Lines in 3D Culture

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

Han, Ju; Chang, Hang; Giricz, Orsi

Correlative analysis of molecular markers with phenotypic signatures is the simplest model for hypothesis generation. In this paper, a panel of 24 breast cell lines was grown in 3D culture, their morphology was imaged through phase contrast microscopy, and computational methods were developed to segment and represent each colony at multiple dimensions. Subsequently, subpopulations from these morphological responses were identified through consensus clustering to reveal three clusters of round, grape-like, and stellate phenotypes. In some cases, cell lines with particular pathobiological phenotypes clustered together (e.g., ERBB2 amplified cell lines sharing the same morphometric properties as the grape-like phenotype). Next, associationsmore » with molecular features were realized through (i) differential analysis within each morphological cluster, and (ii) regression analysis across the entire panel of cell lines. In both cases, the dominant genes that are predictive of the morphological signatures were identified. Specifically, PPAR? has been associated with the invasive stellate morphological phenotype, which corresponds to triple-negative pathobiology. PPAR? has been validated through two supporting biological assays.« less

Liquid petroleum gas sensing application of ZnO/CdO:ZnO nanocomposites at low temperature

NASA Astrophysics Data System (ADS)

Rajput, Jeevitesh K.; Pathak, T. K.; Kumar, V.; Swart, H. C.; Purohit, L. P.

2018-04-01

ZnO and CdO:ZnO nanoparticles are synthesized by sol-gel precipitation method. The structural analysis shows composite structure for CdO:ZnO nanoparticles with (002) and (111) phase. The SEM images show wedge like morphology and 3-D hexagonal morphology with ˜110 nm in size. The uniform growth of CdO:ZnO nanoparticles were observed in EDS element mapping image. LPG sensing was observed for CdO:ZnO nanoparticle with rapid sensing response 8.69% at operating temperature 50°C. This sensing response can be accounted due by absorption ions reactions at low operating temperature.

Automatic morphological classification of galaxy images

PubMed Central

Shamir, Lior

2009-01-01

We describe an image analysis supervised learning algorithm that can automatically classify galaxy images. The algorithm is first trained using a manually classified images of elliptical, spiral, and edge-on galaxies. A large set of image features is extracted from each image, and the most informative features are selected using Fisher scores. Test images can then be classified using a simple Weighted Nearest Neighbor rule such that the Fisher scores are used as the feature weights. Experimental results show that galaxy images from Galaxy Zoo can be classified automatically to spiral, elliptical and edge-on galaxies with accuracy of ~90% compared to classifications carried out by the author. Full compilable source code of the algorithm is available for free download, and its general-purpose nature makes it suitable for other uses that involve automatic image analysis of celestial objects. PMID:20161594

NeuronMetrics: Software for Semi-Automated Processing of Cultured-Neuron Images

PubMed Central

Narro, Martha L.; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L.

2007-01-01

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics™ for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch-number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of ~60 2D images is 1.0–2.5 hours, from a folder of images to a table of numeric data. NeuronMetrics’ output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery. PMID:17270152

NeuronMetrics: software for semi-automated processing of cultured neuron images.

PubMed

Narro, Martha L; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L

2007-03-23

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of approximately 60 2D images is 1.0-2.5 h, from a folder of images to a table of numeric data. NeuronMetrics' output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery.

Nuclear morphology for the detection of alterations in bronchial cells from lung cancer: an attempt to improve sensitivity and specificity.

PubMed

Fafin-Lefevre, Mélanie; Morlais, Fabrice; Guittet, Lydia; Clin, Bénédicte; Launoy, Guy; Galateau-Sallé, Françoise; Plancoulaine, Benoît; Herlin, Paulette; Letourneux, Marc

2011-08-01

To identify which morphologic or densitometric parameters are modified in cell nuclei from bronchopulmonary cancer based on 18 parameters involving shape, intensity, chromatin, texture, and DNA content and develop a bronchopulmonary cancer screening method relying on analysis of sputum sample cell nuclei. A total of 25 sputum samples from controls and 22 bronchial aspiration samples from patients presenting with bronchopulmonary cancer who were professionally exposed to cancer were used. After Feulgen staining, 18 morphologic and DNA content parameters were measured on cell nuclei, via image cytom- etry. A method was developed for analyzing distribution quantiles, compared with simply interpreting mean values, to characterize morphologic modifications in cell nuclei. Distribution analysis of parameters enabled us to distinguish 13 of 18 parameters that demonstrated significant differences between controls and cancer cases. These parameters, used alone, enabled us to distinguish two population types, with both sensitivity and specificity > 70%. Three parameters offered 100% sensitivity and specificity. When mean values offered high sensitivity and specificity, comparable or higher sensitivity and specificity values were observed for at least one of the corresponding quantiles. Analysis of modification in morphologic parameters via distribution analysis proved promising for screening bronchopulmonary cancer from sputum.

Correlates of Intellectual Ability with Morphology of the Hippocampus and Amygdala in Healthy Adults

ERIC Educational Resources Information Center

Amat, Jose A.; Bansal, Ravi; Whiteman, Ronald; Haggerty, Rita; Royal, Jason; Peterson, Bradley S.

2008-01-01

Several prior imaging studies of healthy adults have correlated volumes of the hippocampus and amygdala with measures of general intelligence (IQ), with variable results. In this study, we assessed correlations between volumes of the hippocampus and amygdala and full-scale IQ scores (FSIQ) using a method of image analysis that permits detailed…

Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

NASA Astrophysics Data System (ADS)

Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

2016-07-01

Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

Morphologic analysis of the zebrafish digestive system.

PubMed

Trotter, Andrew J; Parslow, Adam C; Heath, Joan K

2009-01-01

The zebrafish provides an ideal model for the study of vertebrate organogenesis, including the formation of the digestive tract and its associated organs. Despite optical transparency of embryos, the internal position of the developing digestive system and its close juxtaposition with the yolk initially made morphological analysis relatively challenging, particularly during the first 3 d of development. However, methodologies have been successfully developed to address these problems and comprehensive morphologic analysis of the developing digestive system has now been achieved using a combination of light and fluorescence microscope approaches-including confocal analysis-to visualize wholemount and histological preparations of zebrafish embryos. Furthermore, the expanding number of antibodies that cross-react with zebrafish proteins and the generation of tissue-specific transgenic green fluorescent protein reporter lines that mark specific cell and tissue compartments have greatly enhanced our ability to successfully image the developing zebrafish digestive system.

Physical reconstruction of packed beds and their morphological analysis: core-shell packings as an example.

PubMed

Bruns, Stefan; Tallarek, Ulrich

2011-04-08

We report a fast, nondestructive, and quantitative approach to characterize the morphology of packed beds of fine particles by their three-dimensional reconstruction from confocal laser scanning microscopy images, exemplarily shown for a 100μm i.d. fused-silica capillary packed with 2.6μm-sized core-shell particles. The presented method is generally applicable to silica-based capillary columns, monolithic or particulate, and comprises column pretreatment, image acquisition, image processing, and statistical analysis of the image data. It defines a unique platform for fundamental comparisons of particulate and monolithic supports using the statistical measures derived from their reconstructions. Received morphological data are column cross-sectional porosity profiles and chord length distributions from the interparticle macropore space, which are a descriptor of local density and can be characterized by a simplified k-gamma distribution. This distribution function provides a parameter of location and a parameter of dispersion which can be correlated to individual chromatographic band broadening processes (i.e., to transchannel and short-range interchannel contributions to eddy dispersion, respectively). Together with the transcolumn porosity profile the presented approach allows to analyze and quantify the packing microstructure from pore to column scale and therefore holds great promise in a comparative study of packing conditions and particle properties, particularly for characterizing and minimizing the packing process-specific heterogeneities in the final bed structure. Copyright © 2011 Elsevier B.V. All rights reserved.

Bio-photonic detection method for morphological analysis of anthracnose disease and physiological disorders of Diospyros kaki

NASA Astrophysics Data System (ADS)

Wijesinghe, Ruchire Eranga; Lee, Seung-Yeol; Ravichandran, Naresh Kumar; Shirazi, Muhammad Faizan; Moon, Byungin; Jung, Hee-Young; Jeon, Mansik; Kim, Jeehyun

2017-04-01

The pathological and physiological defects in various types of fruits lead to large amounts of economical waste. It is well recognized that internal fruit defects due to pathological infections and physiological disorders can be effectively visualized at an initial stage of the disease using a well-known bio-photonic detection method called optical coherence tomography (OCT). This work investigates the use of OCT for identifying the morphological variations of anthracnose (bitter rot) disease infected and physiologically disordered Diospyros kaki (Asian Persimmon) fruits. An experiment was conducted using fruit samples that were carefully selected from persimmon orchards. Depth-resolved images with a high axial resolution were acquired using 850-nm-based spectral-domain OCT (SD-OCT) system. The obtained exemplary high-resolution two-dimensional and volumetric three-dimensional images revealed complementary morphological differences between healthy and defected samples. Moreover, the obtained depth-profile analysis results confirmed the disappearance of the healthy cell layers among the healthy-infected boundary regions. Thus, the proposed method has the potential to increase the diagnostic accuracy of the OCT technique used in agricultural plantations.

A new method for computer-assisted detection, definition and differentiation of the urinary calculi.

PubMed

Yildirim, Duzgun; Ozturk, Ovunc; Tutar, Onur; Nurili, Fuad; Bozkurt, Halil; Kayadibi, Huseyin; Karaarslan, Ercan; Bakan, Selim

2014-09-01

Urinary stones are common and can be diagnosed with computed tomography (CT) easily. In this study, we aimed to specify the opacity characteristics of various types of calcified foci that develop through the urinary system by using an image analysis program. With this method, we try to differentiate the calculi from the non-calculous opacities and also we aimed to present how to identify the characteristic features of renal and ureteral calcules. We obtained the CT studies of the subjects (n = 48, mean age = 41 years) by using a dual source CT imaging system. We grouped the calculi detected in the dual-energy CT sections as renal (n = 40) or ureteric (n = 45) based on their locations. Other radio-opaque structures that were identified outside but within close proximity of the urinary tract were recorded as calculi "mimickers". We used ImageJ program for morphological analysis. All the acquired data were analyzed statistically. According to thorough morphological parameters, there were statistically significant differences in the angle and Feret angle values between calculi and mimickers (p < 0.001). Multivariate logistical regression analysis showed that Minor Axis and Feret angle parameters can be used to distinguish between ureteric (p = 0.003) and kidney (p = 0.001) stones. Computer-based morphologic parameters can be used simply to differentiate between calcular and noncalcular densities on CT and also between renal and ureteric stones.

The relationship of quantitative nuclear morphology to molecular genetic alterations in the adenoma-carcinoma sequence of the large bowel.

PubMed Central

Mulder, J. W.; Offerhaus, G. J.; de Feyter, E. P.; Floyd, J. J.; Kern, S. E.; Vogelstein, B.; Hamilton, S. R.

1992-01-01

The relationship of abnormal nuclear morphology to molecular genetic alterations that are important in colorectal tumorigenesis is unknown. Therefore, Feulgen-stained isolated nuclei from 22 adenomas and 42 carcinomas that had been analyzed for ras gene mutations and allelic deletions on chromosomes 5q, 18q, and 17p were characterized by computerized image analysis. Both nuclear area and the nuclear shape factor representing irregularity correlated with adenoma-carcinoma progression (r = 0.57 and r = 0.52, P < 0.0001), whereas standard nuclear texture, a parameter of chromatin homogeneity, was inversely correlated with progression (r = -0.80, P < 0.0001). The nuclear parameters were strongly interrelated (P < 0.0005). In multivariate analysis, the nuclear parameters were predominantly associated with adenoma-carcinoma progression (P < or = 0.0001) and were not influenced significantly by the individual molecular genetic alterations. Nuclear texture, however, was inversely correlated with fractional allelic loss, a global measure of genetic changes, in carcinomas (r = -0.39, P = 0.011). The findings indicate that nuclear morphology in colorectal neoplasms is strongly related to tumor progression. Nuclear morphology and biologic behavior appear to be influenced by accumulated alterations in cancer-associated genes. Images Figure 1 PMID:1357973

Micro-tattoo guided OCT imaging of site specific inflammation

NASA Astrophysics Data System (ADS)

Phillips, Kevin G.; Choudhury, Niloy; Samatham, Ravikant V.; Singh, Harvinder; Jacques, Steven L.

2010-02-01

Epithelial biologists studying human skin diseases such as cancer formation and psoriasis commonly utilize mouse models to characterize the interplay among cells and intracellular signal transduction pathways that result in programmed changes in gene expression and cellular behaviors. The information obtained from animal models is useful only when phenotypic presentations of disease recapitulate those observed in humans. Excision of tissues followed by histochemical analysis is currently the primary means of establishing the morphological presentation. Non invasive imaging of animal models provides an alternate means to characterize tissue morphology associated with the disease of interest in vivo. While useful, the ability to perform in vivo imaging at different time points in the same tissue location has been a challenge. This information is key to understanding site specific changes as the imaged tissue can now be extracted and analyzed for mRNA expression. We present a method employing a micro-tattoo to guide optical coherence tomography (OCT) imaging of ultraviolet induced inflammation over time in the same tissue locations.

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.

Analysis of Multilayer Devices for Superconducting Electronics by High-Resolution Scanning Transmission Electron Microscopy and Energy Dispersive Spectroscopy

DOE PAGES

Missert, Nancy; Kotula, Paul G.; Rye, Michael; ...

2017-02-15

We used a focused ion beam to obtain cross-sectional specimens from both magnetic multilayer and Nb/Al-AlOx/Nb Josephson junction devices for characterization by scanning transmission electron microscopy (STEM) and energy dispersive X-ray spectroscopy (EDX). An automated multivariate statistical analysis of the EDX spectral images produced chemically unique component images of individual layers within the multilayer structures. STEM imaging elucidated distinct variations in film morphology, interface quality, and/or etch artifacts that could be correlated to magnetic and/or electrical properties measured on the same devices.

Extracting relevant information for cancer diagnosis from dynamic full field OCT through image processing and learning

NASA Astrophysics Data System (ADS)

Apelian, Clément; Gastaud, Clément; Boccara, A. Claude

2017-02-01

For a large number of cancer surgeries, the lack of reliable intraoperative diagnosis leads to reoperations or bad outcomes for the patients. To deliver better diagnosis, we developed Dynamic Full Field OCT (D-FFOCT) as a complement to FFOCT. FFOCT already presents interesting results for cancer diagnosis e.g. Mohs surgery and reaching 96% accuracy on prostate cancer. D-FFOCT accesses the dynamic processes of metabolism and gives new tools to diagnose the state of a tissue at the cellular level to complement FFOCT contrast. We developed a processing framework that intends to maximize the information provided by the FFOCT technology as well as D-FFOCT and synthetize this as a meaningful image. We use different time processing to generate metrics (standard deviation of time signals, decorrelation times and more) and spatial processing to sort out structures and the corresponding imaging modality, which is the most appropriate. Sorting was achieved through quadratic discriminant analysis in a N-dimension parametric space corresponding to our metrics. Combining the best imaging modalities for each structure leads to a rich morphology image. This image displaying the morphology is then colored to represent the dynamic behavior of these structures (slow or fast) and to be quickly analyzed by doctors. Therefore, we achieved a micron resolved image, rich of both FFOCT ability of imaging fixed and highly backscattering structures as well as D-FFOCT ability of imaging low level scattering cellular level details. We believe that this morphological contrast close to histology and the dynamic behavior contrast will push forward the limits of intraoperative diagnosis further on.

An Investigation of the Morphology of the Petrotympanic Fissure Using Cone-Beam Computed Tomography

PubMed Central

Syriopoulos, Konstantinos; Sens, Rogier L.; Politis, Constantinus

2018-01-01

ABSTRACT Objectives The purpose of the present study was: a) to examine the visibility and morphology of the petrotympanic fissure on cone-beam computed tomography images, and b) to investigate whether the petrotympanic fissure morphology is significantly affected by gender and age, or not. Material and Methods Using Newtom VGi (QR Verona, Italy), 106 cone-beam computed tomography examinations (212 temporomandibular joint areas) of both genders were retrospectively and randomly selected. Two observers examined the images and subsequently classified by consensus the petrotympanic fissure morphology into the following three types: type 1 - widely open; type 2 - narrow middle; type 3 - very narrow/closed. Results The petrotympanic fissure morphology was assessed as type 1, type 2, and type 3 in 85 (40.1%), 72 (34.0%), and 55 (25.9%) cases, respectively. No significant difference was found between left and right petrotympanic fissure morphology (Kappa = 0.37; P < 0.001). Furthermore, no significant difference was found between genders, specifically P = 0.264 and P = 0.211 for the right and left petrotympanic fissure morphology, respectively. However, the ordinal logistic regression analysis showed that males tend to have narrower petrotympanic fissures, in particular OR = 1.58 for right and OR = 1.5 for left petrotympanic fissure. Conclusions The current study lends support to the conclusion that an enhanced multi-planar cone-beam computed tomography yields a clear depiction of the petrotympanic fissure's morphological characteristics. We have found that the morphology is neither gender nor age-related. PMID:29707183

An Investigation of the Morphology of the Petrotympanic Fissure Using Cone-Beam Computed Tomography.

PubMed

Damaskos, Spyros; Syriopoulos, Konstantinos; Sens, Rogier L; Politis, Constantinus

2018-01-01

The purpose of the present study was: a) to examine the visibility and morphology of the petrotympanic fissure on cone-beam computed tomography images, and b) to investigate whether the petrotympanic fissure morphology is significantly affected by gender and age, or not. Using Newtom VGi (QR Verona, Italy), 106 cone-beam computed tomography examinations (212 temporomandibular joint areas) of both genders were retrospectively and randomly selected. Two observers examined the images and subsequently classified by consensus the petrotympanic fissure morphology into the following three types: type 1 - widely open; type 2 - narrow middle; type 3 - very narrow/closed. The petrotympanic fissure morphology was assessed as type 1, type 2, and type 3 in 85 (40.1%), 72 (34.0%), and 55 (25.9%) cases, respectively. No significant difference was found between left and right petrotympanic fissure morphology (Kappa = 0.37; P < 0.001). Furthermore, no significant difference was found between genders, specifically P = 0.264 and P = 0.211 for the right and left petrotympanic fissure morphology, respectively. However, the ordinal logistic regression analysis showed that males tend to have narrower petrotympanic fissures, in particular OR = 1.58 for right and OR = 1.5 for left petrotympanic fissure. The current study lends support to the conclusion that an enhanced multi-planar cone-beam computed tomography yields a clear depiction of the petrotympanic fissure's morphological characteristics. We have found that the morphology is neither gender nor age-related.

Enhancement of morphological and vascular features in OCT images using a modified Bayesian residual transform

PubMed Central

Tan, Bingyao; Wong, Alexander; Bizheva, Kostadinka

2018-01-01

A novel image processing algorithm based on a modified Bayesian residual transform (MBRT) was developed for the enhancement of morphological and vascular features in optical coherence tomography (OCT) and OCT angiography (OCTA) images. The MBRT algorithm decomposes the original OCT image into multiple residual images, where each image presents information at a unique scale. Scale selective residual adaptation is used subsequently to enhance morphological features of interest, such as blood vessels and tissue layers, and to suppress irrelevant image features such as noise and motion artefacts. The performance of the proposed MBRT algorithm was tested on a series of cross-sectional and enface OCT and OCTA images of retina and brain tissue that were acquired in-vivo. Results show that the MBRT reduces speckle noise and motion-related imaging artefacts locally, thus improving significantly the contrast and visibility of morphological features in the OCT and OCTA images. PMID:29760996

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

Relationship between increasing concentrations of two carcinogens and statistical image descriptors of foci morphology in the cell transformation assay.

PubMed

Callegaro, Giulia; Corvi, Raffaella; Salovaara, Susan; Urani, Chiara; Stefanini, Federico M

2017-06-01

Cell Transformation Assays (CTAs) have long been proposed for the identification of chemical carcinogenicity potential. The endpoint of these in vitro assays is represented by the phenotypic alterations in cultured cells, which are characterized by the change from the non-transformed to the transformed phenotype. Despite the wide fields of application and the numerous advantages of CTAs, their use in regulatory toxicology has been limited in part due to concerns about the subjective nature of visual scoring, i.e. the step in which transformed colonies or foci are evaluated through morphological features. An objective evaluation of morphological features has been previously obtained through automated digital processing of foci images to extract the value of three statistical image descriptors. In this study a further potential of the CTA using BALB/c 3T3 cells is addressed by analysing the effect of increasing concentrations of two known carcinogens, benzo[a]pyrene and NiCl 2 , with different modes of action on foci morphology. The main result of our quantitative evaluation shows that the concentration of the considered carcinogens has an effect on foci morphology that is statistically significant for the mean of two among the three selected descriptors. Statistical significance also corresponds to visual relevance. The statistical analysis of variations in foci morphology due to concentration allowed to quantify morphological changes that can be visually appreciated but not precisely determined. Therefore, it has the potential of providing new quantitative parameters in CTAs, and of exploiting all the information encoded in foci. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Abdominal Organ Location, Morphology, and Rib Coverage for the 5(th), 50(th), and 95(th) Percentile Males and Females in the Supine and Seated Posture using Multi-Modality Imaging.

PubMed

Hayes, Ashley R; Gayzik, F Scott; Moreno, Daniel P; Martin, R Shayn; Stitzel, Joel D

The purpose of this study was to use data from a multi-modality image set of males and females representing the 5(th), 50(th), and 95(th) percentile (n=6) to examine abdominal organ location, morphology, and rib coverage variations between supine and seated postures. Medical images were acquired from volunteers in three image modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and upright MRI (uMRI). A manual and semi-automated segmentation method was used to acquire data and a registration technique was employed to conduct a comparative analysis between abdominal organs (liver, spleen, and kidneys) in both postures. Location of abdominal organs, defined by center of gravity movement, varied between postures and was found to be significant (p=0.002 to p=0.04) in multiple directions for each organ. In addition, morphology changes, including compression and expansion, were seen in each organ as a result of postural changes. Rib coverage, defined as the projected area of the ribs onto the abdominal organs, was measured in frontal, lateral, and posterior projections, and also varied between postures. A significant change in rib coverage between postures was measured for the spleen and right kidney (p=0.03 and p=0.02). The results indicate that posture affects the location, morphology and rib coverage area of abdominal organs and these implications should be noted in computational modeling efforts focused on a seated posture.

Comparative morphology analysis of live blood platelets using scanning ion conductance and robotic dark-field microscopy.

PubMed

Kraus, Max-Joseph; Seifert, Jan; Strasser, Erwin F; Gawaz, Meinrad; Schäffer, Tilman E; Rheinlaender, Johannes

2016-09-01

Many conventional microscopy techniques for investigating platelet morphology such as electron or fluorescence microscopy require highly invasive treatment of the platelets such as fixation, drying and metal coating or staining. Here, we present two unique but entirely different microscopy techniques for direct morphology analysis of live, unstained platelets: scanning ion conductance microscopy (SICM) and robotic dark-field microscopy (RDM). We demonstrate that both techniques allow for a quantitative evaluation of the morphological features of live adherent platelets. We show that their morphology can be quantified by both techniques using the same geometric parameters and therefore can be directly compared. By imaging the same identical platelets subsequently with SICM and RDM, we found that area, perimeter and circularity of the platelets are directly correlated between SICM and dark-field microscopy (DM), while the fractal dimension (FD) differed between the two microscopy techniques. We show that SICM and RDM are both valuable tools for the ex vivo investigation of the morphology of live platelets, which might contribute to new insights into the physiological and pathophysiological role of platelet spreading.

NeuronRead, an open source semi-automated tool for morphometric analysis of phase contrast and fluorescence neuronal images.

PubMed

Dias, Roberto A; Gonçalves, Bruno P; da Rocha, Joana F; da Cruz E Silva, Odete A B; da Silva, Augusto M F; Vieira, Sandra I

2017-12-01

Neurons are specialized cells of the Central Nervous System whose function is intricately related to the neuritic network they develop to transmit information. Morphological evaluation of this network and other neuronal structures is required to establish relationships between neuronal morphology and function, and may allow monitoring physiological and pathophysiologic alterations. Fluorescence-based microphotographs are the most widely used in cellular bioimaging, but phase contrast (PhC) microphotographs are easier to obtain, more affordable, and do not require invasive, complicated and disruptive techniques. Despite the various freeware tools available for fluorescence-based images analysis, few exist that can tackle the more elusive and harder-to-analyze PhC images. To surpass this, an interactive semi-automated image processing workflow was developed to easily extract relevant information (e.g. total neuritic length, average cell body area) from both PhC and fluorescence neuronal images. This workflow, named 'NeuronRead', was developed in the form of an ImageJ macro. Its robustness and adaptability were tested and validated on rat cortical primary neurons under control and differentiation inhibitory conditions. Validation included a comparison to manual determinations and to a golden standard freeware tool for fluorescence image analysis. NeuronRead was subsequently applied to PhC images of neurons at distinct differentiation days and exposed or not to DAPT, a pharmacological inhibitor of the γ-secretase enzyme, which cleaves the well-known Alzheimer's amyloid precursor protein (APP) and the Notch receptor. Data obtained confirms a neuritogenic regulatory role for γ-secretase products and validates NeuronRead as a time- and cost-effective useful monitoring tool. Copyright © 2017. Published by Elsevier Inc.

BaTMAn: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2016-12-01

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

High temperature antigen retrieval and loss of nuclear morphology: a comparison of microwave and autoclave techniques.

PubMed Central

Hunt, N C; Attanoos, R; Jasani, B

1996-01-01

The use of high temperature antigen retrieval methods has been of major importance in increasing the diagnostic utility of immunocytochemistry. However, these techniques are not without their problems and in this report attention is drawn to a loss of nuclear morphological detail, including mitotic figures, following microwave antigen retrieval. This was not seen with an equivalent autoclave technique. This phenomenon was quantified using image analysis in a group of B cell lymphomas stained with the antibody L26. Loss of nuclear morphological detail may lead to difficulty in identifying cells accurately, which is important in the diagnostic setting-for example, when trying to distinguish a malignant lymphoid infiltrate within a mixed cell population. In such cases it would clearly be wise to consider the use of alternative high temperature retrieval methods and accept their slightly lower staining enhancement capability compared with the microwave technique. Images PMID:9038766

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.

Heuristic Analysis Model of Nitrided Layers’ Formation Consisting of the Image Processing and Analysis and Elements of Artificial Intelligence

PubMed Central

Wójcicki, Tomasz; Nowicki, Michał

2016-01-01

The article presents a selected area of research and development concerning the methods of material analysis based on the automatic image recognition of the investigated metallographic sections. The objectives of the analyses of the materials for gas nitriding technology are described. The methods of the preparation of nitrided layers, the steps of the process and the construction and operation of devices for gas nitriding are given. We discuss the possibility of using the methods of digital images processing in the analysis of the materials, as well as their essential task groups: improving the quality of the images, segmentation, morphological transformations and image recognition. The developed analysis model of the nitrided layers formation, covering image processing and analysis techniques, as well as selected methods of artificial intelligence are presented. The model is divided into stages, which are formalized in order to better reproduce their actions. The validation of the presented method is performed. The advantages and limitations of the developed solution, as well as the possibilities of its practical use, are listed. PMID:28773389

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

Hemodynamic and morphologic responses in mouse brain during acute head injury imaged by multispectral structured illumination

NASA Astrophysics Data System (ADS)

Volkov, Boris; Mathews, Marlon S.; Abookasis, David

2015-03-01

Multispectral imaging has received significant attention over the last decade as it integrates spectroscopy, imaging, tomography analysis concurrently to acquire both spatial and spectral information from biological tissue. In the present study, a multispectral setup based on projection of structured illumination at several near-infrared wavelengths and at different spatial frequencies is applied to quantitatively assess brain function before, during, and after the onset of traumatic brain injury in an intact mouse brain (n=5). For the production of head injury, we used the weight drop method where weight of a cylindrical metallic rod falling along a metal tube strikes the mouse's head. Structured light was projected onto the scalp surface and diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse head. Following data analysis, we were able to concurrently show a series of hemodynamic and morphologic changes over time including higher deoxyhemoglobin, reduction in oxygen saturation, cell swelling, etc., in comparison with baseline measurements. Overall, results demonstrates the capability of multispectral imaging based structured illumination to detect and map of brain tissue optical and physiological properties following brain injury in a simple noninvasive and noncontact manner.

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

NASA Astrophysics Data System (ADS)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

Deciphering protein signatures using color, morphological, and topological analysis of immunohistochemically stained human tissues

NASA Astrophysics Data System (ADS)

Zerhouni, Erwan; Prisacari, Bogdan; Zhong, Qing; Wild, Peter; Gabrani, Maria

2016-03-01

Images of tissue specimens enable evidence-based study of disease susceptibility and stratification. Moreover, staining technologies empower the evidencing of molecular expression patterns by multicolor visualization, thus enabling personalized disease treatment and prevention. However, translating molecular expression imaging into direct health benefits has been slow. Two major factors contribute to that. On the one hand, disease susceptibility and progression is a complex, multifactorial molecular process. Diseases, such as cancer, exhibit cellular heterogeneity, impeding the differentiation between diverse grades or types of cell formations. On the other hand, the relative quantification of the stained tissue selected features is ambiguous, tedious and time consuming, prone to clerical error, leading to intra- and inter-observer variability and low throughput. Image analysis of digital histopathology images is a fast-developing and exciting area of disease research that aims to address the above limitations. We have developed a computational framework that extracts unique signatures using color, morphological and topological information and allows the combination thereof. The integration of the above information enables diagnosis of disease with AUC as high as 0.97. Multiple staining show significant improvement with respect to most proteins, and an AUC as high as 0.99.

Image acquisitions, processing and analysis in the process of obtaining characteristics of horse navicular bone

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Włodarek, J.; Przybylak, A.; Przybył, K.; Wojcieszak, D.; Czekała, W.; Ludwiczak, A.; Boniecki, P.; Koszela, K.; Przybył, J.; Skwarcz, J.

2015-07-01

The aim of this study was investigate the possibility of using methods of computer image analysis for the assessment and classification of morphological variability and the state of health of horse navicular bone. Assumption was that the classification based on information contained in the graphical form two-dimensional digital images of navicular bone and information of horse health. The first step in the research was define the classes of analyzed bones, and then using methods of computer image analysis for obtaining characteristics from these images. This characteristics were correlated with data concerning the animal, such as: side of hooves, number of navicular syndrome (scale 0-3), type, sex, age, weight, information about lace, information about heel. This paper shows the introduction to the study of use the neural image analysis in the diagnosis of navicular bone syndrome. Prepared method can provide an introduction to the study of non-invasive way to assess the condition of the horse navicular bone.

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.

Measuring the morphological characteristics of thoracolumbar fascia in ultrasound images: an inter-rater reliability study.

PubMed

De Coninck, Kyra; Hambly, Karen; Dickinson, John W; Passfield, Louis

2018-06-01

Chronic lower back pain is still regarded as a poorly understood multifactorial condition. Recently, the thoracolumbar fascia complex has been found to be a contributing factor. Ultrasound imaging has shown that people with chronic lower back pain demonstrate both a significant decrease in shear strain, and a 25% increase in thickness of the thoracolumbar fascia. There is sparse data on whether medical practitioners agree on the level of disorganisation in ultrasound images of thoracolumbar fascia. The purpose of this study was to establish inter-rater reliability of the ranking of architectural disorganisation of thoracolumbar fascia on a scale from 'very disorganised' to 'very organised'. An exploratory analysis was performed using a fully crossed design of inter-rater reliability. Thirty observers were recruited, consisting of 21 medical doctors, 7 physiotherapists and 2 radiologists, with an average of 13.03 ± 9.6 years of clinical experience. All 30 observers independently rated the architectural disorganisation of the thoracolumbar fascia in 30 ultrasound scans, on a Likert-type scale with rankings from 1 = very disorganised to 10 = very organised. Internal consistency was assessed using Cronbach's alpha. Krippendorff's alpha was used to calculate the overall inter-rater reliability. The Krippendorf's alpha was .61, indicating a modest degree of agreement between observers on the different morphologies of thoracolumbar fascia.The Cronbach's alpha (0.98), indicated that there was a high degree of consistency between observers. Experience in ultrasound image analysis did not affect constancy between observers (Cronbach's range between experienced and inexperienced raters: 0.95 and 0.96 respectively). Medical practitioners agree on morphological features such as levels of organisation and disorganisation in ultrasound images of thoracolumbar fascia, regardless of experience. Further analysis by an expert panel is required to develop specific classification criteria for thoracolumbar fascia.

A quantitative spatiotemporal analysis of microglia morphology during ischemic stroke and reperfusion

PubMed Central

2013-01-01

Background Microglia cells continuously survey the healthy brain in a ramified morphology and, in response to injury, undergo progressive morphological and functional changes that encompass microglia activation. Although ideally positioned for immediate response to ischemic stroke (IS) and reperfusion, their progressive morphological transformation into activated cells has not been quantified. In addition, it is not well understood if diverse microglia morphologies correlate to diverse microglia functions. As such, the dichotomous nature of these cells continues to confound our understanding of microglia-mediated injury after IS and reperfusion. The purpose of this study was to quantitatively characterize the spatiotemporal pattern of microglia morphology during the evolution of cerebral injury after IS and reperfusion. Methods Male C57Bl/6 mice were subjected to focal cerebral ischemia and periods of reperfusion (0, 8 and 24 h). The microglia process length/cell and number of endpoints/cell was quantified from immunofluorescent confocal images of brain regions using a skeleton analysis method developed for this study. Live cell morphology and process activity were measured from movies acquired in acute brain slices from GFP-CX3CR1 transgenic mice after IS and 24-h reperfusion. Regional CD11b and iNOS expressions were measured from confocal images and Western blot, respectively, to assess microglia proinflammatory function. Results Quantitative analysis reveals a significant spatiotemporal relationship between microglia morphology and evolving cerebral injury in the ipsilateral hemisphere after IS and reperfusion. Microglia were both hyper- and de-ramified in striatal and cortical brain regions (respectively) after 60 min of focal cerebral ischemia. However, a de-ramified morphology was prominent when ischemia was coupled to reperfusion. Live microglia were de-ramified, and, in addition, process activity was severely blunted proximal to the necrotic core after IS and 24 h of reperfusion. CD11b expression, but not iNOS expression, was increased in regions of hyper- and de-ramified microglia during the course of ischemic stroke and 24 h of reperfusion. Conclusions Our findings illustrate that microglia activation after stroke includes both increased and decreased cell ramification. Importantly, quantitative analyses of microglial morphology and activity are feasible and, in future studies, would assist in the comprehensive identification and stratification of their dichotomous contribution toward cerebral injury and recovery during IS and reperfusion. PMID:23311642

Quantitative Contour Analysis as an Image-based Discriminator Between Benign and Malignant Renal Tumors.

PubMed

Yap, Felix Y; Hwang, Darryl H; Cen, Steven Y; Varghese, Bino A; Desai, Bhushan; Quinn, Brian D; Gupta, Megha Nayyar; Rajarubendra, Nieroshan; Desai, Mihir M; Aron, Manju; Liang, Gangning; Aron, Monish; Gill, Inderbir S; Duddalwar, Vinay A

2018-04-01

To investigate whether morphologic analysis can differentiate between benign and malignant renal tumors on clinically acquired imaging. Between 2009 and 2014, 3-dimensional tumor volumes were manually segmented from contrast-enhanced computerized tomography (CT) images from 150 patients with predominantly solid, nonmacroscopic fat-containing renal tumors: 100 renal cell carcinomas and 50 benign lesions (eg, oncocytoma and lipid-poor angiomyolipoma). Tessellated 3-dimensional tumor models were created from segmented voxels using MATLAB code. Eleven shape descriptors were calculated: sphericity, compactness, mean radial distance, standard deviation of the radial distance, radial distance area ratio, zero crossing, entropy, Feret ratio, convex hull area and convex hull perimeter ratios, and elliptic compactness. Morphometric parameters were compared using the Wilcoxon rank-sum test to investigate whether malignant renal masses demonstrate more morphologic irregularity than benign ones. Only CHP in sagittal orientation (median 0.96 vs 0.97) and EC in coronal orientation (median 0.92 vs 0.93) differed significantly between malignant and benign masses (P = .04). When comparing these 2 metrics between coronal and sagittal orientations, similar but nonsignificant trends emerged (P = .07). Other metrics tested were not significantly different in any imaging plane. Computerized image analysis is feasible using shape descriptors that otherwise cannot be visually assessed and used without quantification. Shape analysis via the transverse orientation may be reasonable, but encompassing all 3 planar dimensions to characterize tumor contour can achieve a more comprehensive evaluation. Two shape metrics (CHP and EC) may help distinguish benign from malignant renal tumors, an often challenging goal to achieve on imaging and biopsy. Copyright © 2017 Elsevier Inc. All rights reserved.

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

Morphometric Characterization of Rat and Human Alveolar Macrophage Cell Models and their Response to Amiodarone using High Content Image Analysis.

PubMed

Hoffman, Ewelina; Patel, Aateka; Ball, Doug; Klapwijk, Jan; Millar, Val; Kumar, Abhinav; Martin, Abigail; Mahendran, Rhamiya; Dailey, Lea Ann; Forbes, Ben; Hutter, Victoria

2017-12-01

Progress to the clinic may be delayed or prevented when vacuolated or "foamy" alveolar macrophages are observed during non-clinical inhalation toxicology assessment. The first step in developing methods to study this response in vitro is to characterize macrophage cell lines and their response to drug exposures. Human (U937) and rat (NR8383) cell lines and primary rat alveolar macrophages obtained by bronchoalveolar lavage were characterized using high content fluorescence imaging analysis quantification of cell viability, morphometry, and phospholipid and neutral lipid accumulation. Cell health, morphology and lipid content were comparable (p < 0.05) for both cell lines and the primary macrophages in terms of vacuole number, size and lipid content. Responses to amiodarone, a known inducer of phospholipidosis, required analysis of shifts in cell population profiles (the proportion of cells with elevated vacuolation or lipid content) rather than average population data which was insensitive to the changes observed. A high content image analysis assay was developed and used to provide detailed morphological characterization of rat and human alveolar-like macrophages and their response to a phospholipidosis-inducing agent. This provides a basis for development of assays to predict or understand macrophage vacuolation following inhaled drug exposure.

Segmentation and feature extraction of retinal vascular morphology

NASA Astrophysics Data System (ADS)

Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

2017-02-01

Analysis of retinal fundus images is essential for physicians, optometrists and ophthalmologists in the diagnosis, care and treatment of patients. The first step of almost all forms of automated fundus analysis begins with the segmentation and subtraction of the retinal vasculature, while analysis of that same structure can aid in the diagnosis of certain retinal and cardiovascular conditions, such as diabetes or stroke. This paper investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using DRIVE, a database of fundus images. The result of the network with the application of a confidence threshold was slightly below the 2nd observer and gold standard, with an accuracy of 0.9419 and ROC of 0.9707. The output of the network with on post-processing boasted the highest sensitivity found in the literature with a score of 0.9568 and a good ROC score of 0.9689. The high sensitivity of the system makes it suitable for longitudinal morphology assessments, disease detection and other similar tasks.

High-frequency Electrocardiogram Analysis in the Ability to Predict Reversible Perfusion Defects during Adenosine Myocardial Perfusion Imaging

NASA Technical Reports Server (NTRS)

Tragardh, Elin; Schlegel, Todd T.; Carlsson, Marcus; Pettersson, Jonas; Nilsson, Klas; Pahlm, Olle

2007-01-01

Background: A previous study has shown that analysis of high-frequency QRS components (HF-QRS) is highly sensitive and reasonably specific for detecting reversible perfusion defects on myocardial perfusion imaging (MPI) scans during adenosine. The purpose of the present study was to try to reproduce those findings. Methods: 12-lead high-resolution electrocardiogram recordings were obtained from 100 patients before (baseline) and during adenosine Tc-99m-tetrofosmin MPI tests. HF-QRS were analyzed regarding morphology and changes in root mean square (RMS) voltages from before the adenosine infusion to peak infusion. Results: The best area under the curve (AUC) was found in supine patients (AUC=0.736) in a combination of morphology and RMS changes. None of the measurements, however, were statistically better than tossing a coin (AUC=0.5). Conclusion: Analysis of HF-QRS was not significantly better than tossing a coin for determining reversible perfusion defects on MPI scans.

Intraoperative assisting diagnosis of esophageal submucosal cancer using multiphoton microscopy

NASA Astrophysics Data System (ADS)

Zeng, Yaping; Xu, Jian; Zhou, Qun; Kang, Deyong; Zhuo, Shuangmu; Zhu, Xiaoqin; Lin, Jiangbo; Chen, Jianxin

2018-07-01

Multiphoton microscopy (MPM) based on two-photon excited fluorescence and second harmonic generation can achieve high-resolution images of biological tissues at the cellular and subcellular levels. In this work, we used MPM imaging of intraoperative hematoxylin and eosin (H&E)-stained frozen sections (FSs) of esophagus to explore whether MPM can provide complementary information to the auxiliary diagnosis of esophageal submucosal cancer during the intraoperative period. It was found that MPM has the ability not only to clearly reveal biological tissue microstructure and its morphological changes, but can reveal information not distinguishable in H&E-stained images. The complementary information of nonlinear spectral analysis, orientation and morphology changes in the collagen showed that MPM has important accessory diagnostic value for the differential diagnosis of submucosal carcinoma of the esophagus during the intraoperative period.

Neuronal Morphology goes Digital: A Research Hub for Cellular and System Neuroscience

PubMed Central

Parekh, Ruchi; Ascoli, Giorgio A.

2013-01-01

Summary The importance of neuronal morphology in brain function has been recognized for over a century. The broad applicability of “digital reconstructions” of neuron morphology across neuroscience sub-disciplines has stimulated the rapid development of numerous synergistic tools for data acquisition, anatomical analysis, three-dimensional rendering, electrophysiological simulation, growth models, and data sharing. Here we discuss the processes of histological labeling, microscopic imaging, and semi-automated tracing. Moreover, we provide an annotated compilation of currently available resources in this rich research “ecosystem” as a central reference for experimental and computational neuroscience. PMID:23522039

Polished sample preparing and backscattered electron imaging and of fly ash-cement paste

NASA Astrophysics Data System (ADS)

Feng, Shuxia; Li, Yanqi

2018-03-01

In recent decades, the technology of backscattered electron imaging and image analysis was applied in more and more study of mixed cement paste because of its special advantages. Test accuracy of this technology is affected by polished sample preparation and image acquisition. In our work, effects of two factors in polished sample preparing and backscattered electron imaging were investigated. The results showed that increasing smoothing pressure could improve the flatness of polished surface and then help to eliminate interference of morphology on grey level distribution of backscattered electron images; increasing accelerating voltage was beneficial to increase gray difference among different phases in backscattered electron images.

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

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

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

Detailed Morphological Changes of Foveoschisis in Patient with X-Linked Retinoschisis Detected by SD-OCT and Adaptive Optics Fundus Camera.

PubMed

Akeo, Keiichiro; Kameya, Shuhei; Gocho, Kiyoko; Kubota, Daiki; Yamaki, Kunihiko; Takahashi, Hiroshi

2015-01-01

Purpose. To report the morphological and functional changes associated with a regression of foveoschisis in a patient with X-linked retinoschisis (XLRS). Methods. A 42-year-old man with XLRS underwent genetic analysis and detailed ophthalmic examinations. Functional assessments included best-corrected visual acuity (BCVA), full-field electroretinograms (ERGs), and multifocal ERGs (mfERGs). Morphological assessments included fundus photography, spectral-domain optical coherence tomography (SD-OCT), and adaptive optics (AO) fundus imaging. After the baseline clinical data were obtained, topical dorzolamide was applied to the patient. The patient was followed for 24 months. Results. A reported RS1 gene mutation was found (P203L) in the patient. At the baseline, his decimal BCVA was 0.15 in the right and 0.3 in the left eye. Fundus photographs showed bilateral spoke wheel-appearing maculopathy. SD-OCT confirmed the foveoschisis in the left eye. The AO images of the left eye showed spoke wheel retinal folds, and the folds were thinner than those in fundus photographs. During the follow-up period, the foveal thickness in the SD-OCT images and the number of retinal folds in the AO images were reduced. Conclusions. We have presented the detailed morphological changes of foveoschisis in a patient with XLRS detected by SD-OCT and AO fundus camera. However, the findings do not indicate whether the changes were influenced by topical dorzolamide or the natural history.

In vitro and in vivo analysis and characterization of engineered spinal neural implants (Conference Presentation)

NASA Astrophysics Data System (ADS)

Shor, Erez; Shoham, Shy; Levenberg, Shulamit

2016-03-01

Spinal cord injury is a devastating medical condition. Recent developments in pre-clinical and clinical research have started to yield neural implants inducing functional recovery after spinal cord transection injury. However, the functional performance of the transplants was assessed using histology and behavioral experiments which are unable to study cell dynamics and the therapeutic response. Here, we use neurophotonic tools and optogenetic probes to investigate cellular level morphology and activity characteristics of neural implants over time at the cellular level. These methods were used in-vitro and in-vivo, in a mouse spinal cord injury implant model. Following previous attempts to induce recovery after spinal cord injury, we engineered a pre-vascularized implant to obtain better functional performance. To image network activity of a construct implanted in a mouse spinal cord, we transfected the implant to express GCaMP6 calcium activity indicators and implanted these constructs under a spinal cord chamber enabling 2-photon chronic in vivo neural activity imaging. Activity and morphology analysis image processing software was developed to automatically quantify the behavior of the neural and vascular networks. Our experimental results and analyses demonstrate that vascularized and non-vascularized constructs exhibit very different morphologic and activity patterns at the cellular level. This work enables further optimization of neural implants and also provides valuable tools for continuous cellular level monitoring and evaluation of transplants designed for various neurodegenerative disease models.

Pre-cancer risk assessment in habitual smokers from DIC images of oral exfoliative cells using active contour and SVM analysis.

PubMed

Dey, Susmita; Sarkar, Ripon; Chatterjee, Kabita; Datta, Pallab; Barui, Ananya; Maity, Santi P

2017-04-01

Habitual smokers are known to be at higher risk for developing oral cancer, which is increasing at an alarming rate globally. Conventionally, oral cancer is associated with high mortality rates, although recent reports show the improved survival outcomes by early diagnosis of disease. An effective prediction system which will enable to identify the probability of cancer development amongst the habitual smokers, is thus expected to benefit sizable number of populations. Present work describes a non-invasive, integrated method for early detection of cellular abnormalities based on analysis of different cyto-morphological features of exfoliative oral epithelial cells. Differential interference contrast (DIC) microscopy provides a potential optical tool as this mode provides a pseudo three dimensional (3-D) image with detailed morphological and textural features obtained from noninvasive, label free epithelial cells. For segmentation of DIC images, gradient vector flow snake model active contour process has been adopted. To evaluate cellular abnormalities amongst habitual smokers, the selected morphological and textural features of epithelial cells are compared with the non-smoker (-ve control group) group and clinically diagnosed pre-cancer patients (+ve control group) using support vector machine (SVM) classifier. Accuracy of the developed SVM based classification has been found to be 86% with 80% sensitivity and 89% specificity in classifying the features from the volunteers having smoking habit. Copyright © 2017 Elsevier Ltd. All rights reserved.

Particle shape analysis of volcanic clast samples with the Matlab tool MORPHEO

NASA Astrophysics Data System (ADS)

Charpentier, Isabelle; Sarocchi, Damiano; Rodriguez Sedano, Luis Angel

2013-02-01

This paper presents a modular Matlab tool, namely MORPHEO, devoted to the study of particle morphology by Fourier analysis. A benchmark made of four sample images with different features (digitized coins, a pebble chart, gears, digitized volcanic clasts) is then proposed to assess the abilities of the software. Attention is brought to the Weibull distribution introduced to enhance fine variations of particle morphology. Finally, as an example, samples pertaining to a lahar deposit located in La Lumbre ravine (Colima Volcano, Mexico) are analysed. MORPHEO and the benchmark are freely available for research purposes.

Comparison of SAM and OBIA as Tools for Lava Morphology Classification - A Case Study in Krafla, NE Iceland

NASA Astrophysics Data System (ADS)

Aufaristama, Muhammad; Hölbling, Daniel; Höskuldsson, Ármann; Jónsdóttir, Ingibjörg

2017-04-01

The Krafla volcanic system is part of the Icelandic North Volcanic Zone (NVZ). During Holocene, two eruptive events occurred in Krafla, 1724-1729 and 1975-1984. The last eruptive episode (1975-1984), known as the "Krafla Fires", resulted in nine volcanic eruption episodes. The total area covered by the lavas from this eruptive episode is 36 km2 and the volume is about 0.25-0.3 km3. Lava morphology is related to the characteristics of the surface morphology of a lava flow after solidification. The typical morphology of lava can be used as primary basis for the classification of lava flows when rheological properties cannot be directly observed during emplacement, and also for better understanding the behavior of lava flow models. Although mapping of lava flows in the field is relatively accurate such traditional methods are time consuming, especially when the lava covers large areas such as it is the case in Krafla. Semi-automatic mapping methods that make use of satellite remote sensing data allow for an efficient and fast mapping of lava morphology. In this study, two semi-automatic methods for lava morphology classification are presented and compared using Landsat 8 (30 m spatial resolution) and SPOT-5 (10 m spatial resolution) satellite images. For assessing the classification accuracy, the results from semi-automatic mapping were compared to the respective results from visual interpretation. On the one hand, the Spectral Angle Mapper (SAM) classification method was used. With this method an image is classified according to the spectral similarity between the image reflectance spectrums and the reference reflectance spectra. SAM successfully produced detailed lava surface morphology maps. However, the pixel-based approach partly leads to a salt-and-pepper effect. On the other hand, we applied the Random Forest (RF) classification method within an object-based image analysis (OBIA) framework. This statistical classifier uses a randomly selected subset of training samples to produce multiple decision trees. For final classification of pixels or - in the present case - image objects, the average of the class assignments probability predicted by the different decision trees is used. While the resulting OBIA classification of lava morphology types shows a high coincidence with the reference data, the approach is sensitive to the segmentation-derived image objects that constitute the base units for classification. Both semi-automatic methods produce reasonable results in the Krafla lava field, even if the identification of different pahoehoe and aa types of lava appeared to be difficult. The use of satellite remote sensing data shows a high potential for fast and efficient classification of lava morphology, particularly over large and inaccessible areas.

Constraints on the Formation and Modification of Lobate Debris Aprons Through Categorized Crater Counts

NASA Astrophysics Data System (ADS)

Berman, D. C.; Crown, D. A.; Joseph, E. C. S.

2012-03-01

Compilation of crater counts using CTX images and analysis of SFD, coupled with categorization of crater morphologies, provides important insights into interpretation of the formation and modification of lobate debris aprons.

Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

PubMed

Knowles, David W; Biggin, Mark D

2013-01-01

Animals comprise dynamic three-dimensional arrays of cells that express gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution. Here we summarize light microscopy-based approaches to establish permanent, quantitative datasets-atlases-that record this information. We focus on experiments that capture data for whole embryos or large areas of tissue in three dimensions, often at multiple time points. We compare and contrast the advantages and limitations of different methods and highlight some of the discoveries made. We emphasize the need for interdisciplinary collaborations and integrated experimental pipelines that link sample preparation, image acquisition, image analysis, database design, visualization, and quantitative analysis. Copyright © 2013 Wiley Periodicals, Inc.

Image analysis supported moss cell disruption in photo-bioreactors.

PubMed

Lucumi, A; Posten, C; Pons, M-N

2005-05-01

Diverse methods for the disruption of cell entanglements and pellets of the moss Physcomitrella patens were tested in order to improve the homogeneity of suspension cultures. The morphological characterization of the moss was carried out by means of image analysis. Selected morphological parameters were defined and compared to the reduction of the carbon dioxide fixation, and the released pigments after cell disruption. The size control of the moss entanglements based on the rotor stator principle allowed a focused shear stress, avoiding a severe reduction in the photosynthesis. Batch cultures of P. patens in a 30.0-l pilot tubular photo-bioreactor with cell disruption showed no significant variation in growth rate and a delayed cell differentiation, when compared to undisrupted cultures. A highly controlled photoautotrophic culture of P. patens in a scalable photo-bioreactor was established, contributing to the development required for the future use of mosses as producers of relevant heterologous proteins.

Diffusion-weighted magnetic resonance imaging to differentiate malignant from benign gallbladder disorders.

PubMed

Kitazume, Yoshio; Taura, Shin-Ichi; Nakaminato, Shuichiro; Noguchi, Osamu; Masaki, Yukiyoshi; Kasahara, Ichiro; Kishino, Mitsuhiro; Tateishi, Ukihide

2016-04-01

To retrospectively evaluate the utility of apparent diffusion coefficient (ADC) and lesion to spinal cord ratio (LSR) in diffusion-weighted magnetic resonance (MR) imaging (DWI) as compared with morphological assessment alone, for differentiating malignant from benign gallbladder disorders. This study was approved by the ethics committee, and written informed consent was waived. Ninety-one patients (13 malignancy and 78 benignancy) were reviewed. ADC was calculated using two DW images with different motion-probing gradient strengths (b=0, 1000s/mm(2)). LSR was measured by dividing the signal intensity of a thickened gallbladder wall by the maximum signal intensity of the lumbar enlargement of the spinal cord. In addition, the morphology of the gallbladders was assessed with conventional MR imaging. In receiver operating characteristic curve analysis, the areas under the curves for ADC and LSR were 0.861 and 0.906, respectively. Three morphological findings were considered: a massive formation, a disrupted mucosal line, and the absence of a two-layered pattern. When a combination of two or more of these morphological findings was positive for malignancy, the sensitivity, specificity, and accuracy were 76.9%, 84.0%, and 83.0%, respectively. When a combination of three or more of the above morphological findings together with ADC of less than 1.2 × 10(-3)mm(2)/s or LSR of more than 0.48 were positive for malignancy, these values were 73.0%, 96.2%, and 92.9%, respectively. There were significant differences in specificity and accuracy. Use of ADC and LSR in DWI can improve diagnostic performance for differentiating malignant from benign gallbladder disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Anthropometric Study of Three-Dimensional Facial Morphology in Malay Adults

PubMed Central

Majawit, Lynnora Patrick; Mohd Razi, Roziana

2016-01-01

Objectives To establish the three-dimensional (3D) facial soft tissue morphology of adult Malaysian subjects of the Malay ethnic group; and to determine the morphological differences between the genders, using a non-invasive stereo-photogrammetry 3D camera. Material and Methods One hundred and nine subjects participated in this research, 54 Malay men and 55 Malay women, aged 20–30 years old with healthy BMI and with no adverse skeletal deviation. Twenty-three facial landmarks were identified on 3D facial images captured using a VECTRA M5-360 Head System (Canfield Scientific Inc, USA). Two angular, 3 ratio and 17 linear measurements were identified using Canfield Mirror imaging software. Intra- and inter-examiner reliability tests were carried out using 10 randomly selected images, analyzed using the intra-class correlation coefficient (ICC). Multivariate analysis of variance (MANOVA) was carried out to investigate morphologic differences between genders. Results ICC scores were generally good for both intra-examiner (range 0.827–0.987) and inter-examiner reliability (range 0.700–0.983) tests. Generally, all facial measurements were larger in men than women, except the facial profile angle which was larger in women. Clinically significant gender dimorphisms existed in biocular width, nose height, nasal bridge length, face height and lower face height values (mean difference > 3mm). Clinical significance was set at 3mm. Conclusion Facial soft tissue morphological values can be gathered efficiently and measured effectively from images captured by a non-invasive stereo-photogrammetry 3D camera. Adult men in Malaysia when compared to women had a wider distance between the eyes, a longer and more prominent nose and a longer face. PMID:27706220

Ultrafast Microfluidic Cellular Imaging by Optical Time-Stretch.

PubMed

Lau, Andy K S; Wong, Terence T W; Shum, Ho Cheung; Wong, Kenneth K Y; Tsia, Kevin K

2016-01-01

There is an unmet need in biomedicine for measuring a multitude of parameters of individual cells (i.e., high content) in a large population efficiently (i.e., high throughput). This is particularly driven by the emerging interest in bringing Big-Data analysis into this arena, encompassing pathology, drug discovery, rare cancer cell detection, emulsion microdroplet assays, to name a few. This momentum is particularly evident in recent advancements in flow cytometry. They include scaling of the number of measurable colors from the labeled cells and incorporation of imaging capability to access the morphological information of the cells. However, an unspoken predicament appears in the current technologies: higher content comes at the expense of lower throughput, and vice versa. For example, accessing additional spatial information of individual cells, imaging flow cytometers only achieve an imaging throughput ~1000 cells/s, orders of magnitude slower than the non-imaging flow cytometers. In this chapter, we introduce an entirely new imaging platform, namely optical time-stretch microscopy, for ultrahigh speed and high contrast label-free single-cell (in a ultrafast microfluidic flow up to 10 m/s) imaging and analysis with an ultra-fast imaging line-scan rate as high as tens of MHz. Based on this technique, not only morphological information of the individual cells can be obtained in an ultrafast manner, quantitative evaluation of cellular information (e.g., cell volume, mass, refractive index, stiffness, membrane tension) at nanometer scale based on the optical phase is also possible. The technology can also be integrated with conventional fluorescence measurements widely adopted in the non-imaging flow cytometers. Therefore, these two combinatorial and complementary measurement capabilities in long run is an attractive platform for addressing the pressing need for expanding the "parameter space" in high-throughput single-cell analysis. This chapter provides the general guidelines of constructing the optical system for time stretch imaging, fabrication and design of the microfluidic chip for ultrafast fluidic flow, as well as the image acquisition and processing.

A workflow for the automatic segmentation of organelles in electron microscopy image stacks

PubMed Central

Perez, Alex J.; Seyedhosseini, Mojtaba; Deerinck, Thomas J.; Bushong, Eric A.; Panda, Satchidananda; Tasdizen, Tolga; Ellisman, Mark H.

2014-01-01

Electron microscopy (EM) facilitates analysis of the form, distribution, and functional status of key organelle systems in various pathological processes, including those associated with neurodegenerative disease. Such EM data often provide important new insights into the underlying disease mechanisms. The development of more accurate and efficient methods to quantify changes in subcellular microanatomy has already proven key to understanding the pathogenesis of Parkinson's and Alzheimer's diseases, as well as glaucoma. While our ability to acquire large volumes of 3D EM data is progressing rapidly, more advanced analysis tools are needed to assist in measuring precise three-dimensional morphologies of organelles within data sets that can include hundreds to thousands of whole cells. Although new imaging instrument throughputs can exceed teravoxels of data per day, image segmentation and analysis remain significant bottlenecks to achieving quantitative descriptions of whole cell structural organellomes. Here, we present a novel method for the automatic segmentation of organelles in 3D EM image stacks. Segmentations are generated using only 2D image information, making the method suitable for anisotropic imaging techniques such as serial block-face scanning electron microscopy (SBEM). Additionally, no assumptions about 3D organelle morphology are made, ensuring the method can be easily expanded to any number of structurally and functionally diverse organelles. Following the presentation of our algorithm, we validate its performance by assessing the segmentation accuracy of different organelle targets in an example SBEM dataset and demonstrate that it can be efficiently parallelized on supercomputing resources, resulting in a dramatic reduction in runtime. PMID:25426032

The Role of Color and Morphologic Characteristics in Dermoscopic Diagnosis.

PubMed

Bajaj, Shirin; Marchetti, Michael A; Navarrete-Dechent, Cristian; Dusza, Stephen W; Kose, Kivanc; Marghoob, Ashfaq A

2016-06-01

Both colors and structures are considered important in the dermoscopic evaluation of skin lesions but their relative significance is unknown. To determine if diagnostic accuracy for common skin lesions differs between gray-scale and color dermoscopic images. A convenience sample of 40 skin lesions (8 nevi, 8 seborrheic keratoses, 7 basal cell carcinomas, 7 melanomas, 4 hemangiomas, 4 dermatofibromas, 2 squamous cell carcinomas [SCCs]) was selected and shown to attendees of a dermoscopy course (2014 Memorial Sloan Kettering Cancer Center dermoscopy course). Twenty lesions were shown only once, either in gray-scale (n = 10) or color (n = 10) (nonpaired). Twenty lesions were shown twice, once in gray-scale (n = 20) and once in color (n = 20) (paired). Participants provided their diagnosis and confidence level for each of the 60 images. Of the 261 attendees, 158 participated (60.5%) in the study. Most were attending physicians (n = 76 [48.1%]). Most participants were practicing or training in dermatology (n = 144 [91.1%]). The median (interquartile range) experience evaluating skin lesions and using dermoscopy of participants was 6 (13.5) and 2 (4.0) years, respectively. Diagnostic accuracy and confidence level of participants evaluating gray-scale and color images. Two separate analyses were performed: (1) an unpaired evaluation comparing gray-scale and color images shown either once or for the first time, and (2) a paired evaluation comparing pairs of gray-scale and color images of the same lesion. In univariate analysis of unpaired images, color images were less likely to be diagnosed correctly compared with gray-scale images (odds ratio [OR], 0.8; P < .001). Using gray-scale images as the reference, multivariate analyses of both unpaired and paired images found no association between correct lesion diagnosis and use of color images (OR, 1.0; P = .99, and OR, 1.2; P = .82, respectively). Stratified analysis of paired images using a color by diagnosis interaction term showed that participants were more likely to make a correct diagnosis of SCC and hemangioma in color (P < .001 for both comparisons) and dermatofibroma in gray-scale (P < .001). Morphologic characteristics (ie, structures and patterns), not color, provide the primary diagnostic clue in dermoscopy. Use of gray-scale images may improve teaching of dermoscopy to novices by emphasizing the evaluation of morphology.

Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops

PubMed Central

2018-01-01

Plant phenotyping by imaging allows automated analysis of plants for various morphological and physiological traits. In this work, we developed a low-cost RGB imaging phenotyping lab (LCP lab) for low-throughput imaging and analysis using affordable imaging equipment and freely available software. LCP lab comprising RGB imaging and analysis pipeline is set up and demonstrated with early vigour analysis in wheat. Using this lab, a few hundred pots can be photographed in a day and the pots are tracked with QR codes. The software pipeline for both imaging and analysis is built from freely available software. The LCP lab was evaluated for early vigour analysis of five wheat cultivars. A high coefficient of determination (R2 0.94) was obtained between the dry weight and the projected leaf area of 20-day-old wheat plants and R2 of 0.9 for the relative growth rate between 10 and 20 days of plant growth. Detailed description for setting up such a lab is provided together with custom scripts built for imaging and analysis. The LCP lab is an affordable alternative for analysis of cereal crops when access to a high-throughput phenotyping facility is unavailable or when the experiments require growing plants in highly controlled climate chambers. The protocols described in this work are useful for building affordable imaging system for small-scale research projects and for education. PMID:29850536

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

PubMed Central

Gutman, David A; Cobb, Jake; Somanna, Dhananjaya; Park, Yuna; Wang, Fusheng; Kurc, Tahsin; Saltz, Joel H; Brat, Daniel J; Cooper, Lee A D

2013-01-01

Background The integration and visualization of multimodal datasets is a common challenge in biomedical informatics. Several recent studies of The Cancer Genome Atlas (TCGA) data have illustrated important relationships between morphology observed in whole-slide images, outcome, and genetic events. The pairing of genomics and rich clinical descriptions with whole-slide imaging provided by TCGA presents a unique opportunity to perform these correlative studies. However, better tools are needed to integrate the vast and disparate data types. Objective To build an integrated web-based platform supporting whole-slide pathology image visualization and data integration. Materials and methods All images and genomic data were directly obtained from the TCGA and National Cancer Institute (NCI) websites. Results The Cancer Digital Slide Archive (CDSA) produced is accessible to the public (http://cancer.digitalslidearchive.net) and currently hosts more than 20 000 whole-slide images from 22 cancer types. Discussion The capabilities of CDSA are demonstrated using TCGA datasets to integrate pathology imaging with associated clinical, genomic and MRI measurements in glioblastomas and can be extended to other tumor types. CDSA also allows URL-based sharing of whole-slide images, and has preliminary support for directly sharing regions of interest and other annotations. Images can also be selected on the basis of other metadata, such as mutational profile, patient age, and other relevant characteristics. Conclusions With the increasing availability of whole-slide scanners, analysis of digitized pathology images will become increasingly important in linking morphologic observations with genomic and clinical endpoints. PMID:23893318

Segmentation-free image processing and analysis of precipitate shapes in 2D and 3D

NASA Astrophysics Data System (ADS)

Bales, Ben; Pollock, Tresa; Petzold, Linda

2017-06-01

Segmentation based image analysis techniques are routinely employed for quantitative analysis of complex microstructures containing two or more phases. The primary advantage of these approaches is that spatial information on the distribution of phases is retained, enabling subjective judgements of the quality of the segmentation and subsequent analysis process. The downside is that computing micrograph segmentations with data from morphologically complex microstructures gathered with error-prone detectors is challenging and, if no special care is taken, the artifacts of the segmentation will make any subsequent analysis and conclusions uncertain. In this paper we demonstrate, using a two phase nickel-base superalloy microstructure as a model system, a new methodology for analysis of precipitate shapes using a segmentation-free approach based on the histogram of oriented gradients feature descriptor, a classic tool in image analysis. The benefits of this methodology for analysis of microstructure in two and three-dimensions are demonstrated.

Virtual unfolding of light sheet fluorescence microscopy dataset for quantitative analysis of the mouse intestine

NASA Astrophysics Data System (ADS)

Candeo, Alessia; Sana, Ilenia; Ferrari, Eleonora; Maiuri, Luigi; D'Andrea, Cosimo; Valentini, Gianluca; Bassi, Andrea

2016-05-01

Light sheet fluorescence microscopy has proven to be a powerful tool to image fixed and chemically cleared samples, providing in depth and high resolution reconstructions of intact mouse organs. We applied light sheet microscopy to image the mouse intestine. We found that large portions of the sample can be readily visualized, assessing the organ status and highlighting the presence of regions with impaired morphology. Yet, three-dimensional (3-D) sectioning of the intestine leads to a large dataset that produces unnecessary storage and processing overload. We developed a routine that extracts the relevant information from a large image stack and provides quantitative analysis of the intestine morphology. This result was achieved by a three step procedure consisting of: (1) virtually unfold the 3-D reconstruction of the intestine; (2) observe it layer-by-layer; and (3) identify distinct villi and statistically analyze multiple samples belonging to different intestinal regions. Even if the procedure has been developed for the murine intestine, most of the underlying concepts have a general applicability.

Three-dimensional murine airway segmentation in micro-CT images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Thiesse, Jacqueline; McLennan, Geoffrey; Hoffman, Eric A.; Reinhardt, Joseph M.

2007-03-01

Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.

Morphological analysis of pore size and connectivity in a thick mixed-culture biofilm.

PubMed

Rosenthal, Alex F; Griffin, James S; Wagner, Michael; Packman, Aaron I; Balogun, Oluwaseyi; Wells, George F

2018-05-19

Morphological parameters are commonly used to predict transport and metabolic kinetics in biofilms. Yet, quantification of biofilm morphology remains challenging due to imaging technology limitations and lack of robust analytical approaches. We present a novel set of imaging and image analysis techniques to estimate internal porosity, pore size distributions, and pore network connectivity to a depth of 1 mm at a resolution of 10 µm in a biofilm exhibiting both heterotrophic and nitrifying activity. Optical coherence tomography (OCT) scans revealed an extensive pore network with diameters as large as 110 µm directly connected to the biofilm surface and surrounding fluid. Thin section fluorescence in situ hybridization microscopy revealed ammonia oxidizing bacteria (AOB) distributed through the entire thickness of the biofilm. AOB were particularly concentrated in the biofilm around internal pores. Areal porosity values estimated from OCT scans were consistently lower than those estimated from multiphoton laser scanning microscopy, though the two imaging modalities showed a statistically significant correlation (r = 0.49, p<0.0001). Estimates of areal porosity were moderately sensitive to grey level threshold selection, though several automated thresholding algorithms yielded similar values to those obtained by manually thresholding performed by a panel of environmental engineering researchers (±25% relative error). These findings advance our ability to quantitatively describe the geometry of biofilm internal pore networks at length scales relevant to engineered biofilm reactors and suggest that internal pore structures provide crucial habitat for nitrifier growth. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The importance of metadata to assess information content in digital reconstructions of neuronal morphology.

PubMed

Parekh, Ruchi; Armañanzas, Rubén; Ascoli, Giorgio A

2015-04-01

Digital reconstructions of axonal and dendritic arbors provide a powerful representation of neuronal morphology in formats amenable to quantitative analysis, computational modeling, and data mining. Reconstructed files, however, require adequate metadata to identify the appropriate animal species, developmental stage, brain region, and neuron type. Moreover, experimental details about tissue processing, neurite visualization and microscopic imaging are essential to assess the information content of digital morphologies. Typical morphological reconstructions only partially capture the underlying biological reality. Tracings are often limited to certain domains (e.g., dendrites and not axons), may be incomplete due to tissue sectioning, imperfect staining, and limited imaging resolution, or can disregard aspects irrelevant to their specific scientific focus (such as branch thickness or depth). Gauging these factors is critical in subsequent data reuse and comparison. NeuroMorpho.Org is a central repository of reconstructions from many laboratories and experimental conditions. Here, we introduce substantial additions to the existing metadata annotation aimed to describe the completeness of the reconstructed neurons in NeuroMorpho.Org. These expanded metadata form a suitable basis for effective description of neuromorphological data.

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

3D spherical-cap fitting procedure for (truncated) sessile nano- and micro-droplets & -bubbles.

PubMed

Tan, Huanshu; Peng, Shuhua; Sun, Chao; Zhang, Xuehua; Lohse, Detlef

2016-11-01

In the study of nanobubbles, nanodroplets or nanolenses immobilised on a substrate, a cross-section of a spherical cap is widely applied to extract geometrical information from atomic force microscopy (AFM) topographic images. In this paper, we have developed a comprehensive 3D spherical-cap fitting procedure (3D-SCFP) to extract morphologic characteristics of complete or truncated spherical caps from AFM images. Our procedure integrates several advanced digital image analysis techniques to construct a 3D spherical-cap model, from which the geometrical parameters of the nanostructures are extracted automatically by a simple algorithm. The procedure takes into account all valid data points in the construction of the 3D spherical-cap model to achieve high fidelity in morphology analysis. We compare our 3D fitting procedure with the commonly used 2D cross-sectional profile fitting method to determine the contact angle of a complete spherical cap and a truncated spherical cap. The results from 3D-SCFP are consistent and accurate, while 2D fitting is unavoidably arbitrary in the selection of the cross-section and has a much lower number of data points on which the fitting can be based, which in addition is biased to the top of the spherical cap. We expect that the developed 3D spherical-cap fitting procedure will find many applications in imaging analysis.

Wavelet analysis of biological tissue's Mueller-matrix images

NASA Astrophysics Data System (ADS)

Tomka, Yu. Ya.

2008-05-01

The interrelations between statistics of the 1st-4th orders of the ensemble of Mueller-matrix images and geometric structure of birefringent architectonic nets of different morphological structure have been analyzed. The sensitivity of asymmetry and excess of statistic distributions of matrix elements Cik to changing of orientation structure of optically anisotropic protein fibrils of physiologically normal and pathologically changed biological tissues architectonics has been shown.

Digital image processing and analysis for activated sludge wastewater treatment.

PubMed

Khan, Muhammad Burhan; Lee, Xue Yong; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Malik, Aamir Saeed

2015-01-01

Activated sludge system is generally used in wastewater treatment plants for processing domestic influent. Conventionally the activated sludge wastewater treatment is monitored by measuring physico-chemical parameters like total suspended solids (TSSol), sludge volume index (SVI) and chemical oxygen demand (COD) etc. For the measurement, tests are conducted in the laboratory, which take many hours to give the final measurement. Digital image processing and analysis offers a better alternative not only to monitor and characterize the current state of activated sludge but also to predict the future state. The characterization by image processing and analysis is done by correlating the time evolution of parameters extracted by image analysis of floc and filaments with the physico-chemical parameters. This chapter briefly reviews the activated sludge wastewater treatment; and, procedures of image acquisition, preprocessing, segmentation and analysis in the specific context of activated sludge wastewater treatment. In the latter part additional procedures like z-stacking, image stitching are introduced for wastewater image preprocessing, which are not previously used in the context of activated sludge. Different preprocessing and segmentation techniques are proposed, along with the survey of imaging procedures reported in the literature. Finally the image analysis based morphological parameters and correlation of the parameters with regard to monitoring and prediction of activated sludge are discussed. Hence it is observed that image analysis can play a very useful role in the monitoring of activated sludge wastewater treatment plants.

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

PubMed Central

Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on 18F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 18F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUVmax (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUVmax. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16). PMID:23431398

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

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

Missert, Nancy; Kotula, Paul G.; Rye, Michael

We used a focused ion beam to obtain cross-sectional specimens from both magnetic multilayer and Nb/Al-AlOx/Nb Josephson junction devices for characterization by scanning transmission electron microscopy (STEM) and energy dispersive X-ray spectroscopy (EDX). An automated multivariate statistical analysis of the EDX spectral images produced chemically unique component images of individual layers within the multilayer structures. STEM imaging elucidated distinct variations in film morphology, interface quality, and/or etch artifacts that could be correlated to magnetic and/or electrical properties measured on the same devices.

MAMA User Guide v2.0.1

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

Gaschen, Brian Keith; Bloch, Jeffrey Joseph; Porter, Reid

Morphological signatures of bulk SNM materials have significant promise, but these potential signatures are not fully utilized. This document describes software tools, collectively called the MAMA (Morphological Analysis for Material Attribution) software that can help provide robust and accurate quantification of morphological features in bulk material microscopy images (Optical, SEM). Although many of the specific tools are not unique to Mama, the software package has been designed specifically for nuclear material morphological analysis, and is at a point where it can be easily adapted (by Los Alamos or by collaborators) in response to new, different, or changing forensics needs. Themore » current release of the MAMA software only includes the image quantification, descriptions, and annotation functionality. Only limited information on a sample, its pedigree, and its chemistry are recorded inside this part of the software. This was decision based on initial feedback and the fact that there are several analytical chemistry databases being developed within the community. Currently MAMA is a standalone program that can export quantification results in a basic text format that can be imported into other programs such as Excel and Access. There is also a basic report generating feature that produces HTML formatted pages of the same information. We will be working with collaborators to provide better integration of MAMA into their particular systems, databases and workflows.« less

Whole Organism High-Content Screening by Label-Free, Image-Based Bayesian Classification for Parasitic Diseases

PubMed Central

Paveley, Ross A.; Mansour, Nuha R.; Hallyburton, Irene; Bleicher, Leo S.; Benn, Alex E.; Mikic, Ivana; Guidi, Alessandra; Gilbert, Ian H.; Hopkins, Andrew L.; Bickle, Quentin D.

2012-01-01

Sole reliance on one drug, Praziquantel, for treatment and control of schistosomiasis raises concerns about development of widespread resistance, prompting renewed interest in the discovery of new anthelmintics. To discover new leads we designed an automated label-free, high content-based, high throughput screen (HTS) to assess drug-induced effects on in vitro cultured larvae (schistosomula) using bright-field imaging. Automatic image analysis and Bayesian prediction models define morphological damage, hit/non-hit prediction and larval phenotype characterization. Motility was also assessed from time-lapse images. In screening a 10,041 compound library the HTS correctly detected 99.8% of the hits scored visually. A proportion of these larval hits were also active in an adult worm ex-vivo screen and are the subject of ongoing studies. The method allows, for the first time, screening of large compound collections against schistosomes and the methods are adaptable to other whole organism and cell-based screening by morphology and motility phenotyping. PMID:22860151

An improved algorithm of laser spot center detection in strong noise background

NASA Astrophysics Data System (ADS)

Zhang, Le; Wang, Qianqian; Cui, Xutai; Zhao, Yu; Peng, Zhong

2018-01-01

Laser spot center detection is demanded in many applications. The common algorithms for laser spot center detection such as centroid and Hough transform method have poor anti-interference ability and low detection accuracy in the condition of strong background noise. In this paper, firstly, the median filtering was used to remove the noise while preserving the edge details of the image. Secondly, the binarization of the laser facula image was carried out to extract target image from background. Then the morphological filtering was performed to eliminate the noise points inside and outside the spot. At last, the edge of pretreated facula image was extracted and the laser spot center was obtained by using the circle fitting method. In the foundation of the circle fitting algorithm, the improved algorithm added median filtering, morphological filtering and other processing methods. This method could effectively filter background noise through theoretical analysis and experimental verification, which enhanced the anti-interference ability of laser spot center detection and also improved the detection accuracy.

Imaging the Effects of Prostaglandin Analogues on Cultured Trabecular Meshwork Cells by Coherent Anti-Stokes Raman Scattering

PubMed Central

Lei, Tim C.; Masihzadeh, Omid; Kahook, Malik Y.; Ammar, David A.

2013-01-01

Purpose. The aim of this study was to nondestructively monitor morphological changes to the lipid membranes of primary cultures of living human trabecular meshwork cells (hTMC) without the application of exogenous label. Methods. Live hTMC were imaged using two nonlinear optical techniques: coherent anti-Stokes Raman scattering (CARS) and two-photon autofluorescence (TPAF). The hTMC were treated with a commercial formulation of latanoprost (0.5 μg/mL) for 24 hours before imaging. Untreated cells and cells treated with vehicle containing the preservative benzalkonium chloride (BAK; 2 μg/mL) were imaged as controls. After CARS/TPAF imaging, hTMC were fixed, stained with the fluorescent lipid dye Nile Red, and imaged by conventional confocal microscopy to verify lipid membrane structures. Results. Analysis of CARS/TPAF images of hTMC treated with latanoprost revealed multiple intracellular lipid membranes absent from untreated or BAK-treated hTMC. Treatment of hTMC with sodium fluoride or ouabain, agents shown to cause morphological changes to hTMC, also did not induce formation of intracellular lipid membranes. Conclusions. CARS microscopy detected changes in living hTMC morphology that were validated by subsequent histological stain. Prostaglandin-induced changes to hTMC involved rearrangement of lipid membranes within these cells. These in vitro results identify a novel biological response to a class of antiglaucoma drugs, and further experiments are needed to establish how this effect is involved in the hypotensive action of prostaglandin analogues in vivo. PMID:23900606

Nuclear proliferomics: A new field of study to identify signatures of nuclear materials as demonstrated on alpha-UO3.

PubMed

Schwerdt, Ian J; Brenkmann, Alexandria; Martinson, Sean; Albrecht, Brent D; Heffernan, Sean; Klosterman, Michael R; Kirkham, Trenton; Tasdizen, Tolga; McDonald Iv, Luther W

2018-08-15

The use of a limited set of signatures in nuclear forensics and nuclear safeguards may reduce the discriminating power for identifying unknown nuclear materials, or for verifying processing at existing facilities. Nuclear proliferomics is a proposed new field of study that advocates for the acquisition of large databases of nuclear material properties from a variety of analytical techniques. As demonstrated on a common uranium trioxide polymorph, α-UO 3 , in this paper, nuclear proliferomics increases the ability to improve confidence in identifying the processing history of nuclear materials. Specifically, α-UO 3 was investigated from the calcination of unwashed uranyl peroxide at 350, 400, 450, 500, and 550 °C in air. Scanning electron microscopy (SEM) images were acquired of the surface morphology, and distinct qualitative differences are presented between unwashed and washed uranyl peroxide, as well as the calcination products from the unwashed uranyl peroxide at the investigated temperatures. Differential scanning calorimetry (DSC), UV-Vis spectrophotometry, powder X-ray diffraction (p-XRD), and thermogravimetric analysis-mass spectrometry (TGA-MS) were used to understand the source of these morphological differences as a function of calcination temperature. Additionally, the SEM images were manually segmented using Morphological Analysis for MAterials (MAMA) software to identify quantifiable differences in morphology for three different surface features present on the unwashed uranyl peroxide calcination products. No single quantifiable signature was sufficient to discern all calcination temperatures with a high degree of confidence; therefore, advanced statistical analysis was performed to allow the combination of a number of quantitative signatures, with their associated uncertainties, to allow for complete discernment by calcination history. Furthermore, machine learning was applied to the acquired SEM images to demonstrate automated discernment with at least 89% accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

A burnout prediction model based around char morphology

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

Tao Wu; Edward Lester; Michael Cloke

Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coalmore » particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.« less

Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

NASA Astrophysics Data System (ADS)

Hoffmann, Sebastian; Shutler, Jamie D.; Lobbes, Marc; Burgeth, Bernhard; Meyer-Bäse, Anke

2013-12-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.

Automated analysis of high-content microscopy data with deep learning.

PubMed

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

[Advances in automatic detection technology for images of thin blood film of malaria parasite].

PubMed

Juan-Sheng, Zhang; Di-Qiang, Zhang; Wei, Wang; Xiao-Guang, Wei; Zeng-Guo, Wang

2017-05-05

This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Nanoscale morphological analysis of soft matter aggregates with fractal dimension ranging from 1 to 3.

PubMed

Valle, Francesco; Brucale, Marco; Chiodini, Stefano; Bystrenova, Eva; Albonetti, Cristiano

2017-09-01

While the widespread emergence of nanoscience and nanotechnology can be dated back to the early eighties, the last decade has witnessed a true coming of age of this research field, with novel nanomaterials constantly finding their way into marketed products. The performance of nanomaterials being dominated by their nanoscale morphology, their quantitative characterization with respect to a number of properties is often crucial. In this context, those imaging techniques able to resolve nanometer scale details are clearly key players. In particular, atomic force microscopy can yield a fully quantitative tridimensional (3D) topography at the nanoscale. Herein, we will review a set of morphological analysis based on the scaling approach, which give access to important quantitative parameters for describing nanomaterial samples. To generalize the use of such morphological analysis on all D-dimensions (1D, 2D and 3D), the review will focus on specific soft matter aggregates with fractal dimension ranging from just above 1 to just below 3. Copyright © 2017 Elsevier Ltd. All rights reserved.

An analytical tool that quantifies cellular morphology changes from three-dimensional fluorescence images.

PubMed

Haass-Koffler, Carolina L; Naeemuddin, Mohammad; Bartlett, Selena E

2012-08-31

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology even in complex tissue sections. Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2016-06-01

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

Kallman syndrome versus idiopathic hypogonadotropic hypogonadism at MR imaging

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

Vogl, T.J.; Stemmler, J.; Bergman, C.

To identify morphologic differences between Kallman syndrome (KS) and idiopathic hypogonadotropic hypogonadism (IHH) and establish a role for magnetic resonance (MR) imaging in these disorders. Twenty-eight patients were compared with 10 eugonal male volunteers. Eighteen patients had KS (hypogonadotropic hypogonadism with anosmia) and 10 had IHH. All participants underwent hormone analysis, a sniff-bottle smell test, and gadolinium-enhanced MR imaging. Changes in the hypothalamic-hypophyseal region and the rhinencephalon were evaluated. MR imaging revealed intracranial morphologic changes in all patients on plain T1-weighted sections. Seventeen patients with KS demonstrated aplasia of an olfactory bulb; one olfactory sulcus was absent in six, rudimentarymore » in four, and normal in eight. Olfactory bulbs were present in all 10 IHH patients and three showed one slightly hypoplastic bulb. Ten patients with KS and three with IHH showed an enlarged paranasal sinus system. Further MR findings were similar. MR imaging demonstrates abnormalities of the rhinencephalon present in KS patients and occasionally absent in IHH patients. 18 refs., 10 figs., 1 tab.« less

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.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

PubMed

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

Repeatability of the Dust and Gas Morphological Structures in the Coma of Comet

NASA Astrophysics Data System (ADS)

Lejoly, Cassandra; Samarasinha, N. H.; Ojha, L.; Schleicher, D. G.

2013-10-01

Comet 1P/Halley is the most famous comet in history and has been observed for over two millennia, making it one of the most extensively studied comets. The morphology in the coma of comet 1P/Halley originates due to the activity at the nucleus and could be used as a probe of the nuclear rotation and the activity. We will present the results from a study summarizing the evolution of coma morphology of comet 1P/Halley observed from ground between October 1985 and June 1986. The results to be presented include analysis of dust features as well as gas (CN) features in the coma and comparisons will be made between their spatial and temporal evolution. About 80 CN images and 300 continuum images from the Small Bodies Node of the NASA Planetary Data System were analyzed using image enhancement techniques that were not available n the 1980s. This enables us to see coma structure never observed before in comet 1P/Halley. Because of the comet's proximity to Earth, most of our best signal-to-noise images were taken in the March-April interval of 1986. Despite the limited coverage of preceding and following months, there is a sufficient number of images to monitor morphological evolution over many months. The initial synodic periods as a function of time used to phase the images together were extrapolated from the lightcurves of the active coma (Schleicher et al. 1990, AJ, 100, 896-912). We will present the periods of repeatability of individual coma features measured using the position angle at different spatial distances from the nucleus in adjacent cycles. Separate features appear to have slightly different periods of repeatability, perhaps depending on the corresponding source regions on the nucleus and/or projection effects. The periods of repeatability of coma morphologies will be presented as a function of time from the perihelion. These results will ultimately be used in detailed modeling of the coma morphologies of comet 1P/Halley over the 1985-1986 apparition in order to characterize the activity of the comet. This work is supported by NASA Planetary Atmospheres grant NNX11AD85G and C.L.'s participation at the meeting is supported by a gift to the Lunar and Planetary Laboratory at the University of Arizona.

A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation.

PubMed

Pelet, S; Previte, M J R; Laiho, L H; So, P T C

2004-10-01

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained analysis. Convergence speed can be greatly accelerated by providing appropriate initial guesses. Realizing that the image morphology often correlates with fluorophore distribution, a global fitting algorithm has been developed to assign initial guesses throughout an image based on a segmentation analysis. This algorithm was tested on both simulated data sets and time-domain lifetime measurements. We have successfully measured fluorophore distribution in fibroblasts stained with Hoechst and calcein. This method further allows second harmonic generation from collagen and elastin autofluorescence to be differentiated in fluorescence lifetime imaging microscopy images of ex vivo human skin. On our experimental measurement, this algorithm increased convergence speed by over two orders of magnitude and achieved significantly better fits. Copyright 2004 Biophysical Society

Bilateral cleft lip and palate: A morphometric analysis of facial skeletal form using cone beam computed tomography.

PubMed

Starbuck, John M; Ghoneima, Ahmed; Kula, Katherine

2015-07-01

Bilateral cleft lip and palate (BCLP) is caused by a lack of merging of maxillary and nasal facial prominences during development and morphogenesis. BCLP is associated with congenital defects of the oronasal facial region that can impair ingestion, mastication, speech, and dentofacial development. Using cone beam computed tomography (CBCT) images, 7- to 18-year old individuals born with BCLP (n = 15) and age- and sex-matched controls (n = 15) were retrospectively assessed. Coordinate values of three-dimensional facial skeletal anatomical landmarks (n = 32) were measured from each CBCT image. Data were evaluated using principal coordinates analysis (PCOORD) and Euclidean Distance Matrix Analysis (EDMA). PCOORD axes 1-3 explain approximately 45% of the morphological variation between samples, and specific patterns of morphological differences were associated with each axis. Approximately, 30% of facial skeletal measures significantly differ by confidence interval testing (α = 0.10) between samples. While significant form differences occur across the facial skeleton, strong patterns of differences are localized to the lateral and superioinferior aspects of the nasal aperture. In conclusion, the BCLP deformity significantly alters facial skeletal morphology of the midface and oronasal regions of the face, but morphological differences were also found in the upper facial skeleton and to a lesser extent, the lower facial skeleton. This pattern of strong differences in the oronasal region of the facial skeleton combined with differences across the rest of the facial complex underscores the idea that bones of the craniofacial skeleton are integrated. © 2015 Wiley Periodicals, Inc.

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.

Resolving power of diffraction imaging with an objective: a numerical study.

PubMed

Wang, Wenjin; Liu, Jing; Lu, Jun Qing; Ding, Junhua; Hu, Xin-Hua

2017-05-01

Diffraction imaging in the far-field can detect 3D morphological features of an object for its coherent nature. We describe methods for accurate calculation and analysis of diffraction images of scatterers of single and double spheres by an imaging unit based on microscope objective at non-conjugate positions. A quantitative study of the calculated diffraction imaging in spectral domain has been performed to assess the resolving power of diffraction imaging. It has been shown numerically that with coherent illumination of 532 nm in wavelength the imaging unit can resolve single spheres of 2 μm or larger in diameters and double spheres separated by less than 300 nm between their centers.

NEEDLE ANATOMY CHANGES WITH INCREASING TREE AGE IN DOUGLAS FIR

EPA Science Inventory

Morphological differences between old growth and sapling (Pseudotsuga menziesii, (Mirb.) Franco) Douglas fir trees may extend to differences in needle anatomy. We used microscopy with image analysis to compare and quantify anatomical parameters in cross-sections of previous year...

Dynamics in the Chromosphere Imaged at Four Second Cadence

NASA Astrophysics Data System (ADS)

Schmit, D.; De Pontieu, B.

2017-12-01

In this work we present analysis of rapid intensity fluctuations that are observed in the chromosphere and transition region using the slit-jaw datasets of IRIS and CLASP. While chromospheric oscillations have been a topic of interest for 30 years, the instrumentation to image those dynamics at high-cadence has only recently been developed. We use filtergraph data from 1215A, 2800A, and 1400A to examine the occurrence rate and morphology of rapid intensity fluctuations in different magnetic environments. There are indications of rapidly propagating disturbances with phase speeds greater than 100 km/s in all passbands although the morphology of the features differs significantly between passbands. The relationship between intensity fluctuations, spicules, and waves is discussed.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

Color and Morphology of Lava Flows on Io

NASA Astrophysics Data System (ADS)

Piatek, Jennifer L.; McElfresh, Sarah B. Z.; Byrnes, Jeffrey M.; Hale, Amy Snyder; Crown, David A.

2000-12-01

Analyses of color and morphologic changes in Voyager images of lava flows on Io were conducted to extend previous flow studies to additional volcanoes in preparation for comparison to Galileo data. Blue and orange filter images of Atar, Daedalus, and Ra Paterae were examined to identify systematic downflow decreases in blue/orange reflectivity suggested in earlier studies as diagnostic of color changes in cooled sulfur flows. Analyses of the color and morphology of 21 lava flows were conducted at these volcanoes, with additional morphologic analysis of lava flows at Agni, Masaaw, Mbali, Shoshu, and Talos Paterae. A total of 66 lava flows of up to 245 km in length were mapped to identify morphologic changes consistent with the rheologic changes expected to occur in sulfur flows. Although downflow color changes are observed, the trends are not consistent, even at the same edifice. Individual flows exhibit a statistically significant increase in blue/orange ratio, decrease in blue/orange ratio, or a lack of progressive downflow color variation. Color changes have similar magnitudes downflow and across flow, and the color ranges observed are similar from volcano to volcano, suggesting that similar processes are controlling color ratios at these edifices. In addition, using flow widening and branching as an indicator of the low viscosity exhibited by sulfur cooling from high temperatures, these flows do not exhibit morphologic changes consistent with the systematic behavior expected from the simple progressive cooling of sulfur.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

Multimodal digital color imaging system for facial skin lesion analysis

NASA Astrophysics Data System (ADS)

Bae, Youngwoo; Lee, Youn-Heum; Jung, Byungjo

2008-02-01

In dermatology, various digital imaging modalities have been used as an important tool to quantitatively evaluate the treatment effect of skin lesions. Cross-polarization color image was used to evaluate skin chromophores (melanin and hemoglobin) information and parallel-polarization image to evaluate skin texture information. In addition, UV-A induced fluorescent image has been widely used to evaluate various skin conditions such as sebum, keratosis, sun damages, and vitiligo. In order to maximize the evaluation efficacy of various skin lesions, it is necessary to integrate various imaging modalities into an imaging system. In this study, we propose a multimodal digital color imaging system, which provides four different digital color images of standard color image, parallel and cross-polarization color image, and UV-A induced fluorescent color image. Herein, we describe the imaging system and present the examples of image analysis. By analyzing the color information and morphological features of facial skin lesions, we are able to comparably and simultaneously evaluate various skin lesions. In conclusion, we are sure that the multimodal color imaging system can be utilized as an important assistant tool in dermatology.

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.

5-ALA induced fluorescent image analysis of actinic keratosis

NASA Astrophysics Data System (ADS)

Cho, Yong-Jin; Bae, Youngwoo; Choi, Eung-Ho; Jung, Byungjo

2010-02-01

In this study, we quantitatively analyzed 5-ALA induced fluorescent images of actinic keratosis using digital fluorescent color and hyperspectral imaging modalities. UV-A was utilized to induce fluorescent images and actinic keratosis (AK) lesions were demarcated from surrounding the normal region with different methods. Eight subjects with AK lesion were participated in this study. In the hyperspectral imaging modality, spectral analysis method was utilized for hyperspectral cube image and AK lesions were demarcated from the normal region. Before image acquisition, we designated biopsy position for histopathology of AK lesion and surrounding normal region. Erythema index (E.I.) values on both regions were calculated from the spectral cube data. Image analysis of subjects resulted in two different groups: the first group with the higher fluorescence signal and E.I. on AK lesion than the normal region; the second group with lower fluorescence signal and without big difference in E.I. between two regions. In fluorescent color image analysis of facial AK, E.I. images were calculated on both normal and AK lesions and compared with the results of hyperspectral imaging modality. The results might indicate that the different intensity of fluorescence and E.I. among the subjects with AK might be interpreted as different phases of morphological and metabolic changes of AK lesions.

Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

PubMed Central

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

2015-01-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

PubMed

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

2016-07-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art.

Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes

NASA Astrophysics Data System (ADS)

Peppa, Maria V.; Mills, Jon P.; Moore, Phil; Miller, Pauline E.; Chambers, Jonathan E.

2017-12-01

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of openness, amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.

Measurements of Cuspal Slope Inclination Angles in Palaeoanthropological Applications

NASA Astrophysics Data System (ADS)

Gaboutchian, A. V.; Knyaz, V. A.; Leybova, N. A.

2017-05-01

Tooth crown morphological features, studied in palaeoanthropology, provide valuable information about human evolution and development of civilization. Tooth crown morphology represents biological and historical data of high taxonomical value as it characterizes genetically conditioned tooth relief features averse to substantial changes under environmental factors during lifetime. Palaeoanthropological studies are still based mainly on descriptive techniques and manual measurements of limited number of morphological parameters. Feature evaluation and measurement result analysis are expert-based. Development of new methods and techniques in 3D imaging creates a background provides for better value of palaeoanthropological data processing, analysis and distribution. The goals of the presented research are to propose new features for automated odontometry and to explore their applicability to paleoanthropological studies. A technique for automated measuring of given morphological tooth parameters needed for anthropological study is developed. It is based on using original photogrammetric system as a teeth 3D models acquisition device and on a set of algorithms for given tooth parameters estimation.

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.

Spectral imaging perspective on cytomics.

PubMed

Levenson, Richard M

2006-07-01

Cytomics involves the analysis of cellular morphology and molecular phenotypes, with reference to tissue architecture and to additional metadata. To this end, a variety of imaging and nonimaging technologies need to be integrated. Spectral imaging is proposed as a tool that can simplify and enrich the extraction of morphological and molecular information. Simple-to-use instrumentation is available that mounts on standard microscopes and can generate spectral image datasets with excellent spatial and spectral resolution; these can be exploited by sophisticated analysis tools. This report focuses on brightfield microscopy-based approaches. Cytological and histological samples were stained using nonspecific standard stains (Giemsa; hematoxylin and eosin (H&E)) or immunohistochemical (IHC) techniques employing three chromogens plus a hematoxylin counterstain. The samples were imaged using the Nuance system, a commercially available, liquid-crystal tunable-filter-based multispectral imaging platform. The resulting data sets were analyzed using spectral unmixing algorithms and/or learn-by-example classification tools. Spectral unmixing of Giemsa-stained guinea-pig blood films readily classified the major blood elements. Machine-learning classifiers were also successful at the same task, as well in distinguishing normal from malignant regions in a colon-cancer example, and in delineating regions of inflammation in an H&E-stained kidney sample. In an example of a multiplexed ICH sample, brown, red, and blue chromogens were isolated into separate images without crosstalk or interference from the (also blue) hematoxylin counterstain. Cytomics requires both accurate architectural segmentation as well as multiplexed molecular imaging to associate molecular phenotypes with relevant cellular and tissue compartments. Multispectral imaging can assist in both these tasks, and conveys new utility to brightfield-based microscopy approaches. Copyright 2006 International Society for Analytical Cytology.

Three-dimensional real-time imaging of bi-phasic flow through porous media

NASA Astrophysics Data System (ADS)

Sharma, Prerna; Aswathi, P.; Sane, Anit; Ghosh, Shankar; Bhattacharya, S.

2011-11-01

We present a scanning laser-sheet video imaging technique to image bi-phasic flow in three-dimensional porous media in real time with pore-scale spatial resolution, i.e., 35 μm and 500 μm for directions parallel and perpendicular to the flow, respectively. The technique is illustrated for the case of viscous fingering. Using suitable image processing protocols, both the morphology and the movement of the two-fluid interface, were quantitatively estimated. Furthermore, a macroscopic parameter such as the displacement efficiency obtained from a microscopic (pore-scale) analysis demonstrates the versatility and usefulness of the method.

Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images

NASA Technical Reports Server (NTRS)

Parsons-Wingerter, Patricia; Vickerman, Mary B.; Keith, Patricia A.

2009-01-01

VESGEN is a newly automated, user-interactive program that maps and quantifies the effects of vascular therapeutics and regulators on microvascular form and function. VESGEN analyzes two-dimensional, black and white vascular images by measuring important vessel morphology parameters. This software guides the user through each required step of the analysis process via a concise graphical user interface (GUI). Primary applications of the VESGEN code are 2D vascular images acquired as clinical diagnostic images of the human retina and as experimental studies of the effects of vascular regulators and therapeutics on vessel remodeling.

Application of image analysis techniques to evaluate the effect of urban residuals fertilization on corn (Zea mays) production

NASA Astrophysics Data System (ADS)

Menesatti, P.; D'Andrea, S.; Socciarelli, S.

2007-09-01

The work focused the application of an image analysis technique to determine corn leaves morphology as objective indicator of the growth performance of corn (Zea mays) resulting from the urban residual fertilization. The analyses were related to six fertilization plots: original soil; chemical fertilizer (160 and 200 kg ha-1 of nitrogen); organic fertilizer (32 t ha-1) and two different doses of urban residues (sewage sludges) (7.5 and 22.5 t ha-1, this last amount corresponds to is the maximum level permitted from the Italian law in three year of fertilization). Those tests were realized by full randomized plots, with two three repetitions for each treatment. Measurements were performed for the first year of the trials in the period proximate to harvest (Rome, Italy - July 2000). Four plants for each plot were harvested and stripped of all leaves, whose RGB images were acquired by a digital photo camera (Kodak Ltd). Image analysis was performed first through the separation of RGB channels into single monochromatic 8-bit distribution, than the blue channel images, the most informative, were then submitted to enhancement, low pass filtering to reduce noise, threshold of binarization (based on statistical parameter affected on Gaussian grey levels distribution), binary morphology and object measurement. For ach single leaf the length, the width, the area were measured. The test results indicated positive and significant responses in relation between the crop growth (leaves area, length and width greater) and the different doses of urban residues (sewage sludges).

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM).

PubMed

Tang, Anson H L; Lai, Queenie T K; Chung, Bob M F; Lee, Kelvin C M; Mok, Aaron T Y; Yip, G K; Shum, Anderson H C; Wong, Kenneth K Y; Tsia, Kevin K

2017-06-28

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture - information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

Morphology of Nano and Micro Fiber Structures in Ultrafine Particles Filtration

NASA Astrophysics Data System (ADS)

Kimmer, Dusan; Vincent, Ivo; Fenyk, Jan; Petras, David; Zatloukal, Martin; Sambaer, Wannes; Zdimal, Vladimir

2011-07-01

Selected procedures permitting to prepare homogeneous nanofibre structures of the desired morphology by employing a suitable combination of variables during the electrospinning process are presented. A comparison (at the same pressure drop) was made of filtration capabilities of planar polyurethane nanostructures formed exclusively by nanofibres, space polycarbonate nanostructures having bead spacers, structures formed by a combination of polymethyl methacrylate micro- and nanofibres and polypropylene meltblown microstructures, through which ultrafine particles of ammonium sulphate 20-400 nm in size were filtered. The structures studied were described using a new digital image analysis technique based on black and white images obtained by scanning electron microscopy. More voluminous structures modified with distance microspheres and having a greater thickness and mass per square area of the material, i.e. structures possessing better mechanical properties, demanded so much in nanostructures, enable preparation of filters having approximately the same free volume fraction as flat nanofibre filters but an increased effective fibre surface area, changed pore size morphology and, consequently, a higher filter quality.

Morphological filtering and multiresolution fusion for mammographic microcalcification detection

NASA Astrophysics Data System (ADS)

Chen, Lulin; Chen, Chang W.; Parker, Kevin J.

1997-04-01

Mammographic images are often of relatively low contrast and poor sharpness with non-stationary background or clutter and are usually corrupted by noise. In this paper, we propose a new method for microcalcification detection using gray scale morphological filtering followed by multiresolution fusion and present a unified general filtering form called the local operating transformation for whitening filtering and adaptive thresholding. The gray scale morphological filters are used to remove all large areas that are considered as non-stationary background or clutter variations, i.e., to prewhiten images. The multiresolution fusion decision is based on matched filter theory. In addition to the normal matched filter, the Laplacian matched filter which is directly related through the wavelet transforms to multiresolution analysis is exploited for microcalcification feature detection. At the multiresolution fusion stage, the region growing techniques are used in each resolution level. The parent-child relations between resolution levels are adopted to make final detection decision. FROC is computed from test on the Nijmegen database.

Novel method for edge detection of retinal vessels based on the model of the retinal vascular network and mathematical morphology

NASA Astrophysics Data System (ADS)

Xu, Lei; Zheng, Xiaoxiang; Zhang, Hengyi; Yu, Yajun

1998-09-01

Accurate edge detection of retinal vessels is a prerequisite for quantitative analysis of subtle morphological changes of retinal vessels under different pathological conditions. A novel method for edge detection of retinal vessels is presented in this paper. Methods: (1) Wavelet-based image preprocessing. (2) The signed edge detection algorithm and mathematical morphological operation are applied to get the approximate regions that contain retinal vessels. (3) By convolving the preprocessed image with a LoG operator only on the detected approximate regions of retinal vessels, followed by edges refining, clear edge maps of the retinal vessels are fast obtained. Results: A detailed performance evaluation together with the existing techniques is given to demonstrate the strong features of our method. Conclusions: True edge locations of retinal vessels can be fast detected with continuous structures of retinal vessels, less non- vessel segments left and insensitivity to noise. The method is also suitable for other application fields such as road edge detection.

Two Algorithms for High-throughput and Multi-parametric Quantification of Drosophila Neuromuscular Junction Morphology.

PubMed

Castells-Nobau, Anna; Nijhof, Bonnie; Eidhof, Ilse; Wolf, Louis; Scheffer-de Gooyert, Jolanda M; Monedero, Ignacio; Torroja, Laura; van der Laak, Jeroen A W M; Schenck, Annette

2017-05-03

Synaptic morphology is tightly related to synaptic efficacy, and in many cases morphological synapse defects ultimately lead to synaptic malfunction. The Drosophila larval neuromuscular junction (NMJ), a well-established model for glutamatergic synapses, has been extensively studied for decades. Identification of mutations causing NMJ morphological defects revealed a repertoire of genes that regulate synapse development and function. Many of these were identified in large-scale studies that focused on qualitative approaches to detect morphological abnormalities of the Drosophila NMJ. A drawback of qualitative analyses is that many subtle players contributing to NMJ morphology likely remain unnoticed. Whereas quantitative analyses are required to detect the subtler morphological differences, such analyses are not yet commonly performed because they are laborious. This protocol describes in detail two image analysis algorithms "Drosophila NMJ Morphometrics" and "Drosophila NMJ Bouton Morphometrics", available as Fiji-compatible macros, for quantitative, accurate and objective morphometric analysis of the Drosophila NMJ. This methodology is developed to analyze NMJ terminals immunolabeled with the commonly used markers Dlg-1 and Brp. Additionally, its wider application to other markers such as Hrp, Csp and Syt is presented in this protocol. The macros are able to assess nine morphological NMJ features: NMJ area, NMJ perimeter, number of boutons, NMJ length, NMJ longest branch length, number of islands, number of branches, number of branching points and number of active zones in the NMJ terminal.

Live imaging of muscles in Drosophila metamorphosis: Towards high-throughput gene identification and function analysis.

PubMed

Puah, Wee Choo; Wasser, Martin

2016-03-01

Time-lapse microscopy in developmental biology is an emerging tool for functional genomics. Phenotypic effects of gene perturbations can be studied non-invasively at multiple time points in chronological order. During metamorphosis of Drosophila melanogaster, time-lapse microscopy using fluorescent reporters allows visualization of alternative fates of larval muscles, which are a model for the study of genes related to muscle wasting. While doomed muscles enter hormone-induced programmed cell death, a smaller population of persistent muscles survives to adulthood and undergoes morphological remodeling that involves atrophy in early, and hypertrophy in late pupation. We developed a method that combines in vivo imaging, targeted gene perturbation and image analysis to identify and characterize genes involved in muscle development. Macrozoom microscopy helps to screen for interesting muscle phenotypes, while confocal microscopy in multiple locations over 4-5 days produces time-lapse images that are used to quantify changes in cell morphology. Performing a similar investigation using fixed pupal tissues would be too time-consuming and therefore impractical. We describe three applications of our pipeline. First, we show how quantitative microscopy can track and measure morphological changes of muscle throughout metamorphosis and analyze genes involved in atrophy. Second, our assay can help to identify genes that either promote or prevent histolysis of abdominal muscles. Third, we apply our approach to test new fluorescent proteins as live markers for muscle development. We describe mKO2 tagged Cysteine proteinase 1 (Cp1) and Troponin-I (TnI) as examples of proteins showing developmental changes in subcellular localization. Finally, we discuss strategies to improve throughput of our pipeline to permit genome-wide screens in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

From Curves to Trees: A Tree-like Shapes Distance Using the Elastic Shape Analysis Framework.

PubMed

Mottini, A; Descombes, X; Besse, F

2015-04-01

Trees are a special type of graph that can be found in various disciplines. In the field of biomedical imaging, trees have been widely studied as they can be used to describe structures such as neurons, blood vessels and lung airways. It has been shown that the morphological characteristics of these structures can provide information on their function aiding the characterization of pathological states. Therefore, it is important to develop methods that analyze their shape and quantify differences between their structures. In this paper, we present a method for the comparison of tree-like shapes that takes into account both topological and geometrical information. This method, which is based on the Elastic Shape Analysis Framework, also computes the mean shape of a population of trees. As a first application, we have considered the comparison of axon morphology. The performance of our method has been evaluated on two sets of images. For the first set of images, we considered four different populations of neurons from different animals and brain sections from the NeuroMorpho.org open database. The second set was composed of a database of 3D confocal microscopy images of three populations of axonal trees (normal and two types of mutations) of the same type of neurons. We have calculated the inter and intra class distances between the populations and embedded the distance in a classification scheme. We have compared the performance of our method against three other state of the art algorithms, and results showed that the proposed method better distinguishes between the populations. Furthermore, we present the mean shape of each population. These shapes present a more complete picture of the morphological characteristics of each population, compared to the average value of certain predefined features.

Image-based quantification and mathematical modeling of spatial heterogeneity in ESC colonies.

PubMed

Herberg, Maria; Zerjatke, Thomas; de Back, Walter; Glauche, Ingmar; Roeder, Ingo

2015-06-01

Pluripotent embryonic stem cells (ESCs) have the potential to differentiate into cells of all three germ layers. This unique property has been extensively studied on the intracellular, transcriptional level. However, ESCs typically form clusters of cells with distinct size and shape, and establish spatial structures that are vital for the maintenance of pluripotency. Even though it is recognized that the cells' arrangement and local interactions play a role in fate decision processes, the relations between transcriptional and spatial patterns have not yet been studied. We present a systems biology approach which combines live-cell imaging, quantitative image analysis, and multiscale, mathematical modeling of ESC growth. In particular, we develop quantitative measures of the morphology and of the spatial clustering of ESCs with different expression levels and apply them to images of both in vitro and in silico cultures. Using the same measures, we are able to compare model scenarios with different assumptions on cell-cell adhesions and intercellular feedback mechanisms directly with experimental data. Applying our methodology to microscopy images of cultured ESCs, we demonstrate that the emerging colonies are highly variable regarding both morphological and spatial fluorescence patterns. Moreover, we can show that most ESC colonies contain only one cluster of cells with high self-renewing capacity. These cells are preferentially located in the interior of a colony structure. The integrated approach combining image analysis with mathematical modeling allows us to reveal potential transcription factor related cellular and intercellular mechanisms behind the emergence of observed patterns that cannot be derived from images directly. © 2015 International Society for Advancement of Cytometry.

FLIM data analysis of NADH and Tryptophan autofluorescence in prostate cancer cells

NASA Astrophysics Data System (ADS)

O'Melia, Meghan J.; Wallrabe, Horst; Svindrych, Zdenek; Rehman, Shagufta; Periasamy, Ammasi

2016-03-01

Fluorescence lifetime imaging microscopy (FLIM) is one of the most sensitive techniques to measure metabolic activity in living cells, tissues and whole animals. We used two- and three-photon fluorescence excitation together with time-correlated single photon counting (TCSPC) to acquire FLIM signals from normal and prostate cancer cell lines. FLIM requires complex data fitting and analysis; we explored different ways to analyze the data to match diverse cellular morphologies. After non-linear least square fitting of the multi-photon TCSPC images by the SPCImage software (Becker & Hickl), all image data are exported and further processed in ImageJ. Photon images provide morphological, NAD(P)H signal-based autofluorescent features, for which regions of interest (ROIs) are created. Applying these ROIs to all image data parameters with a custom ImageJ macro, generates a discrete, ROI specific database. A custom Excel (Microsoft) macro further analyzes the data with charts and statistics. Applying this highly automated assay we compared normal and cancer prostate cell lines with respect to their glycolytic activity by analyzing the NAD(P)H-bound fraction (a2%), NADPH/NADH ratio and efficiency of energy transfer (E%) for Tryptophan (Trp). Our results show that this assay is able to differentiate the effects of glucose stimulation and Doxorubicin in these prostate cell lines by tracking the changes in a2% of NAD(P)H, NADPH/NADH ratio and the changes in Trp E%. The ability to isolate a large, ROI-based data set, reflecting the heterogeneous cellular environment and highlighting even subtle changes -- rather than whole cell averages - makes this assay particularly valuable.

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

New Windows based Color Morphological Operators for Biomedical Image Processing

NASA Astrophysics Data System (ADS)

Pastore, Juan; Bouchet, Agustina; Brun, Marcel; Ballarin, Virginia

2016-04-01

Morphological image processing is well known as an efficient methodology for image processing and computer vision. With the wide use of color in many areas, the interest on the color perception and processing has been growing rapidly. Many models have been proposed to extend morphological operators to the field of color images, dealing with some new problems not present previously in the binary and gray level contexts. These solutions usually deal with the lattice structure of the color space, or provide it with total orders, to be able to define basic operators with required properties. In this work we propose a new locally defined ordering, in the context of window based morphological operators, for the definition of erosions-like and dilation-like operators, which provides the same desired properties expected from color morphology, avoiding some of the drawbacks of the prior approaches. Experimental results show that the proposed color operators can be efficiently used for color image processing.

V-Sipal - a Virtual Laboratory for Satellite Image Processing and Analysis

NASA Astrophysics Data System (ADS)

Buddhiraju, K. M.; Eeti, L.; Tiwari, K. K.

2011-09-01

In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL) being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

RECONSTRUCTION OF A HUMAN LUNG MORPHOLOGY MODEL FROM MAGNETIC RESONANCE IMAGES

EPA Science Inventory

RATIONALE A description of lung morphological structure is necessary for modeling the deposition and fate of inhaled therapeutic aerosols. A morphological model of the lung boundary was generated from magnetic resonance (MR) images with the goal of creating a framework for anato...

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models.

PubMed

Wang, Feng; Wang, Yuxiang; Zhou, Yan; Liu, Congrong; Xie, Lizhi; Zhou, Zhenyu; Liang, Dong; Shen, Yang; Yao, Zhihang; Liu, Jianyu

2017-12-01

To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC). Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded. Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809. © 2017 International Society for Magnetic Resonance in Medicine.

MRI-based analysis of patellofemoral cartilage contact, thickness, and alignment in extension, and during moderate and deep flexion.

PubMed

Freedman, Benjamin R; Sheehan, Frances T; Lerner, Amy L

2015-10-01

Several factors are believed to contribute to patellofemoral joint function throughout knee flexion including patellofemoral (PF) kinematics, contact, and bone morphology. However, data evaluating the PF joint in this highly flexed state have been limited. Therefore, the purpose of this study was to evaluate patellofemoral contact and alignment in low (0°), moderate (60°), and deep (140°) knee flexion, and then correlate these parameters to each other, as well as to femoral morphology. Sagittal magnetic resonance images were acquired on 14 healthy female adult knees (RSRB approved) using a 1.5 T scanner with the knee in full extension, mid-flexion, and deep flexion. The patellofemoral cartilage contact area, lateral contact displacement (LCD), cartilage thickness, and lateral patellar displacement (LPD) throughout flexion were defined. Intra- and inter-rater repeatability measures were determined. Correlations between patellofemoral contact parameters, alignment, and sulcus morphology were calculated. Measurement repeatability ICCs ranged from 0.94 to 0.99. Patellofemoral cartilage contact area and thickness, LCD, and LPD were statistically different throughout all levels of flexion (p<0.001). The cartilage contact area was correlated to LPD, cartilage thickness, sulcus angle, and epicondylar width (r=0.47-0.72, p<0.05). This study provides a comprehensive analysis of the patellofemoral joint throughout its range of motion. This study agrees with past studies that investigated patellofemoral measures at a single flexion angle, and provides new insights into the relationship between patellofemoral contact and alignment at multiple flexion angles. The study provides a detailed analysis of the patellofemoral joint in vivo, and demonstrates the feasibility of using standard clinical magnetic resonance imaging scanners to image the knee joint in deep flexion. Copyright © 2015 Elsevier B.V. All rights reserved.

Unsupervised color normalisation for H and E stained histopathology image analysis

NASA Astrophysics Data System (ADS)

Celis, Raúl; Romero, Eduardo

2015-12-01

In histology, each dye component attempts to specifically characterise different microscopic structures. In the case of the Hematoxylin-Eosin (H&E) stain, universally used for routine examination, quantitative analysis may often require the inspection of different morphological signatures related mainly to nuclei patterns, but also to stroma distribution. Nevertheless, computer systems for automatic diagnosis are often fraught by color variations ranging from the capturing device to the laboratory specific staining protocol and stains. This paper presents a novel colour normalisation method for H&E stained histopathology images. This method is based upon the opponent process theory and blindly estimates the best color basis for the Hematoxylin and Eosin stains without relying on prior knowledge. Stain Normalisation and Color Separation are transversal to any Framework of Histopathology Image Analysis.

3-D characterization of weathered building limestones by high resolution synchrotron X-ray microtomography.

PubMed

Rozenbaum, O

2011-04-15

Understanding the weathering processes of building stones and more generally of their transfer properties requires detailed knowledge of the porosity characteristics. This study aims at analyzing three-dimensional images obtained by X-ray microtomography of building stones. In order to validate these new results a weathered limestone previously characterised (Rozenbaum et al., 2007) by two-dimensional image analysis was selected. The 3-D images were analysed by a set of mathematical tools that enable the description of the pore and solid phase distribution. Results show that 3-D image analysis is a powerful technique to characterise the morphological, structural and topological differences due to weathering. The paper also discusses criteria for mathematically determining whether a stone is weathered or not. Copyright © 2011 Elsevier B.V. All rights reserved.

An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

PubMed

Hennig, Holger; Rees, Paul; Blasi, Thomas; Kamentsky, Lee; Hung, Jane; Dao, David; Carpenter, Anne E; Filby, Andrew

2017-01-01

Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differences among complex, often heterogeneous biological samples. However, data analysis is often performed in a highly manual and subjective manner using very limited image analysis techniques in combination with conventional flow cytometry gating strategies. This approach is not scalable to the hundreds of available image-based features per cell and thus makes use of only a fraction of the spatial and morphometric information. As a result, the quality, reproducibility and rigour of results are limited by the skill, experience and ingenuity of the data analyst. Here, we describe a pipeline using open-source software that leverages the rich information in digital imagery using machine learning algorithms. Compensated and corrected raw image files (.rif) data files from an imaging flow cytometer (the proprietary .cif file format) are imported into the open-source software CellProfiler, where an image processing pipeline identifies cells and subcellular compartments allowing hundreds of morphological features to be measured. This high-dimensional data can then be analysed using cutting-edge machine learning and clustering approaches using "user-friendly" platforms such as CellProfiler Analyst. Researchers can train an automated cell classifier to recognize different cell types, cell cycle phases, drug treatment/control conditions, etc., using supervised machine learning. This workflow should enable the scientific community to leverage the full analytical power of IFC-derived data sets. It will help to reveal otherwise unappreciated populations of cells based on features that may be hidden to the human eye that include subtle measured differences in label free detection channels such as bright-field and dark-field imagery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A novel mesh processing based technique for 3D plant analysis

PubMed Central

2012-01-01

Background In recent years, imaging based, automated, non-invasive, and non-destructive high-throughput plant phenotyping platforms have become popular tools for plant biology, underpinning the field of plant phenomics. Such platforms acquire and record large amounts of raw data that must be accurately and robustly calibrated, reconstructed, and analysed, requiring the development of sophisticated image understanding and quantification algorithms. The raw data can be processed in different ways, and the past few years have seen the emergence of two main approaches: 2D image processing and 3D mesh processing algorithms. Direct image quantification methods (usually 2D) dominate the current literature due to comparative simplicity. However, 3D mesh analysis provides the tremendous potential to accurately estimate specific morphological features cross-sectionally and monitor them over-time. Result In this paper, we present a novel 3D mesh based technique developed for temporal high-throughput plant phenomics and perform initial tests for the analysis of Gossypium hirsutum vegetative growth. Based on plant meshes previously reconstructed from multi-view images, the methodology involves several stages, including morphological mesh segmentation, phenotypic parameters estimation, and plant organs tracking over time. The initial study focuses on presenting and validating the accuracy of the methodology on dicotyledons such as cotton but we believe the approach will be more broadly applicable. This study involved applying our technique to a set of six Gossypium hirsutum (cotton) plants studied over four time-points. Manual measurements, performed for each plant at every time-point, were used to assess the accuracy of our pipeline and quantify the error on the morphological parameters estimated. Conclusion By directly comparing our automated mesh based quantitative data with manual measurements of individual stem height, leaf width and leaf length, we obtained the mean absolute errors of 9.34%, 5.75%, 8.78%, and correlation coefficients 0.88, 0.96, and 0.95 respectively. The temporal matching of leaves was accurate in 95% of the cases and the average execution time required to analyse a plant over four time-points was 4.9 minutes. The mesh processing based methodology is thus considered suitable for quantitative 4D monitoring of plant phenotypic features. PMID:22553969

Altered Calcium Dynamics in Cardiac Cells Grown on Silane-Modified Surfaces

PubMed Central

Ravenscroft-Chang, Melissa S.; Stohlman, Jayna; Molnar, Peter; Natarajan, Anupama; Canavan, Heather E.; Teliska, Maggie; Stancescu, Maria; Krauthamer, Victor; Hickman, J.J.

2013-01-01

Chemically defined surfaces were created using self-assembled monolayers (SAMs) of hydrophobic and hydrophilic silanes as models for implant coatings, and the morphology and physiology of cardiac myocytes plated on these surfaces were studied in vitro. We focused on changes in intracellular Ca2+ because of its essential role in regulating heart cell function. The SAM-modified coverslips were analyzed using X-ray Photoelectron Spectroscopy to verify composition. The morphology and physiology of the cardiac cells were examined using fluorescence microscopy and intracellular Ca2+ imaging. The imaging experiments used the fluorescent ratiometric dye fura-2, AM to establish both the resting Ca2+ concentration and the dynamic responses to electrical stimulation. A significant difference in excitation-induced Ca2+ changes on the different silanated surfaces was observed. However, no significant change was noted based on the morphological analysis. This result implies a difference in internal Ca2+ dynamics, and thus cardiac function, occurs when the composition of the surface is different, and this effect is independent of cellular morphology. This finding has implications for histological examination of tissues surrounding implants, the choice of materials that could be beneficial as implant coatings and understanding of cell-surface interactions in cardiac systems. PMID:19828193

Quantitative morphometric analysis of hepatocellular carcinoma: development of a programmed algorithm and preliminary application.

PubMed

Yap, Felix Y; Bui, James T; Knuttinen, M Grace; Walzer, Natasha M; Cotler, Scott J; Owens, Charles A; Berkes, Jamie L; Gaba, Ron C

2013-01-01

The quantitative relationship between tumor morphology and malignant potential has not been explored in liver tumors. We designed a computer algorithm to analyze shape features of hepatocellular carcinoma (HCC) and tested feasibility of morphologic analysis. Cross-sectional images from 118 patients diagnosed with HCC between 2007 and 2010 were extracted at the widest index tumor diameter. The tumor margins were outlined, and point coordinates were input into a MATLAB (MathWorks Inc., Natick, Massachusetts, USA) algorithm. Twelve shape descriptors were calculated per tumor: the compactness, the mean radial distance (MRD), the RD standard deviation (RDSD), the RD area ratio (RDAR), the zero crossings, entropy, the mean Feret diameter (MFD), the Feret ratio, the convex hull area (CHA) and perimeter (CHP) ratios, the elliptic compactness (EC), and the elliptic irregularity (EI). The parameters were correlated with the levels of alpha-fetoprotein (AFP) as an indicator of tumor aggressiveness. The quantitative morphometric analysis was technically successful in all cases. The mean parameters were as follows: compactness 0.88±0.086, MRD 0.83±0.056, RDSD 0.087±0.037, RDAR 0.045±0.023, zero crossings 6±2.2, entropy 1.43±0.16, MFD 4.40±3.14 cm, Feret ratio 0.78±0.089, CHA 0.98±0.027, CHP 0.98±0.030, EC 0.95±0.043, and EI 0.95±0.023. MFD and RDAR provided the widest value range for the best shape discrimination. The larger tumors were less compact, more concave, and less ellipsoid than the smaller tumors (P < 0.0001). AFP-producing tumors displayed greater morphologic irregularity based on several parameters, including compactness, MRD, RDSD, RDAR, entropy, and EI (P < 0.05 for all). Computerized HCC image analysis using shape descriptors is technically feasible. Aggressively growing tumors have wider diameters and more irregular margins. Future studies will determine further clinical applications for this morphologic analysis.

[Imaging of pelvic organ prolapse].

PubMed

Lapray, Jean-François

2013-01-01

Colpocystodefecography (CCD) and dynamic MRI with defecography (MRId) allow an alternation between filling and emptying the hollow organs and the maximum abdominal strain offered by the defecation. When applied in imaging these two principles reveal the masked or underestimated prolapses at the time of the physical examination. A rigorous application of the technique guarantees almost equivalent results from the two examinations. The CCD provides voiding views and improved analysis of the anorectal pathology (intussusception, anismus) but involves radiation and a more invasive examination. MRId has the advantage of providing continuous visibility of the peritoneal compartment, and a multiplanar representation, enabling an examination of the morphology of the pelvic organs and of the supporting structures, with the disadvantage of still necessitating a supine examination, resulting sometimes in an incomplete or impossible evacuation. The normal and abnormal results (cystoptosis, vaginal vault prolapse, enterocele, anorectal intussuception, rectocele, descending perineum, urinary and fecal incontinence) and the respective advantages and limits of the various imaging methods are detailed. Dynamic perineal and introital ultrasound remains more limited in the appreciation of posterior colpoceles and especially in anorectal disorders, than CCD or MRId. Endoanal ultrasound is the first line morphological evaluation of the anal sphincter. Transvaginal and introital ultrasound can detect some complications of suburethral tapes and meshes. Morphological and dynamic imaging are essential complementary tools to the physical examination, especially when a precise anatomic assessment is required to understand the functional complaint or when a reintervention is needed.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2014-06-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

[Morphological and functional cartilage imaging].

PubMed

Rehnitz, C; Weber, M-A

2015-04-01

Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

Union operation image processing of data cubes separately processed by different objective filters and its application to void analysis in an all-solid-state lithium-ion battery.

PubMed

Yamamoto, Yuta; Iriyama, Yasutoshi; Muto, Shunsuke

2016-04-01

In this article, we propose a smart image-analysis method suitable for extracting target features with hierarchical dimension from original data. The method was applied to three-dimensional volume data of an all-solid lithium-ion battery obtained by the automated sequential sample milling and imaging process using a focused ion beam/scanning electron microscope to investigate the spatial configuration of voids inside the battery. To automatically fully extract the shape and location of the voids, three types of filters were consecutively applied: a median blur filter to extract relatively larger voids, a morphological opening operation filter for small dot-shaped voids and a morphological closing operation filter for small voids with concave contrasts. Three data cubes separately processed by the above-mentioned filters were integrated by a union operation to the final unified volume data, which confirmed the correct extraction of the voids over the entire dimension contained in the original data. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A single cell high content assay detects mitochondrial dysfunction in iPSC-derived neurons with mutations in SNCA.

PubMed

Little, Daniel; Luft, Christin; Mosaku, Olukunbi; Lorvellec, Maëlle; Yao, Zhi; Paillusson, Sébastien; Kriston-Vizi, Janos; Gandhi, Sonia; Abramov, Andrey Y; Ketteler, Robin; Devine, Michael J; Gissen, Paul

2018-06-13

Mitochondrial dysfunction is implicated in many neurodegenerative diseases including Parkinson's disease (PD). Induced pluripotent stem cells (iPSCs) provide a unique cell model for studying neurological diseases. We have established a high-content assay that can simultaneously measure mitochondrial function, morphology and cell viability in iPSC-derived dopaminergic neurons. iPSCs from PD patients with mutations in SNCA and unaffected controls were differentiated into dopaminergic neurons, seeded in 384-well plates and stained with the mitochondrial membrane potential dependent dye TMRM, alongside Hoechst-33342 and Calcein-AM. Images were acquired using an automated confocal screening microscope and single cells were analysed using automated image analysis software. PD neurons displayed reduced mitochondrial membrane potential and altered mitochondrial morphology compared to control neurons. This assay demonstrates that high content screening techniques can be applied to the analysis of mitochondria in iPSC-derived neurons. This technique could form part of a drug discovery platform to test potential new therapeutics for PD and other neurodegenerative diseases.

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.

Ganalyzer: A tool for automatic galaxy image analysis

NASA Astrophysics Data System (ADS)

Shamir, Lior

2011-05-01

Ganalyzer is a model-based tool that automatically analyzes and classifies galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large datasets of galaxy images collected by autonomous sky surveys such as SDSS, LSST or DES.

Dental computed tomographic imaging as age estimation: morphological analysis of the third molar of a group of Turkish population.

PubMed

Cantekin, Kenan; Sekerci, Ahmet Ercan; Buyuk, Suleyman Kutalmis

2013-12-01

Computed tomography (CT) is capable of providing accurate and measurable 3-dimensional images of the third molar. The aims of this study were to analyze the development of the mandibular third molar and its relation to chronological age and to create new reference data for a group of Turkish participants aged 9 to 25 years on the basis of cone-beam CT images. All data were obtained from the patients' records including medical, social, and dental anamnesis and cone-beam CT images of 752 patients. Linear regression analysis was performed to obtain regression formulas for dental age calculation with chronological age and to determine the coefficient of determination (r) for each sex. Statistical analysis showed a strong correlation between age and third-molar development for the males (r2 = 0.80) and the females (r2 = 0.78). Computed tomographic images are clinically useful for accurate and reliable estimation of dental ages of children and youth.

Quantitative Enzymatic and Immunologic Histophotometry of Diseased Human Kid-Ney Tissues Using Tv-Camera and Computer Assisted Image Processing Systems.

NASA Astrophysics Data System (ADS)

Heinert, G.; Mondorf, W.

1982-11-01

High speed image processing was used to analyse morphologic and metabolic characteristics of clinically relevant kidney tissue alterations.Qualitative computer-assisted histophotometry was performed to measure alterations in levels of the enzymes alkaline phosphatase (Ap),alanine aminopeptidase (AAP),g-glutamyltranspepti-dase (GGTP) and A-glucuronidase (B-G1) and AAP and GGTP immunologically determined in prepared renal and cancer tissue sections. A "Mioro-Videomat 2" image analysis system with a "Tessovar" macroscope,a computer-assisted "Axiomat" photomicroscope and an "Interactive Image Analysis System (IBAS)" were employed for analysing changes in enzyme activities determined by changes in absorbance or transmission.Diseased kidney as well as renal neoplastic tissues could be distinguished by significantly (wilcoxon test,p<0,05) decreased enzyme concentrations as compared to those found in normal human kidney tissues.This image analysis techniques might be of potential use in diagnostic and prognostic evaluation of renal cancer and diseased kidney tissues.

Issues in Quantitative Analysis of Ultraviolet Imager (UV) Data: Airglow

NASA Technical Reports Server (NTRS)

Germany, G. A.; Richards, P. G.; Spann, J. F.; Brittnacher, M. J.; Parks, G. K.

1999-01-01

The GGS Ultraviolet Imager (UVI) has proven to be especially valuable in correlative substorm, auroral morphology, and extended statistical studies of the auroral regions. Such studies are based on knowledge of the location, spatial, and temporal behavior of auroral emissions. More quantitative studies, based on absolute radiometric intensities from UVI images, require a more intimate knowledge of the instrument behavior and data processing requirements and are inherently more difficult than studies based on relative knowledge of the oval location. In this study, UVI airglow observations are analyzed and compared with model predictions to illustrate issues that arise in quantitative analysis of UVI images. These issues include instrument calibration, long term changes in sensitivity, and imager flat field response as well as proper background correction. Airglow emissions are chosen for this study because of their relatively straightforward modeling requirements and because of their implications for thermospheric compositional studies. The analysis issues discussed here, however, are identical to those faced in quantitative auroral studies.

Jet Morphology and Coma Analysis of 103P/Hartley 2

NASA Astrophysics Data System (ADS)

Vaughan, Charles; Pierce, D.; Dorman, G.; Cochran, A.

2012-10-01

We have observed comet 103P/Hartley 2 using the George and Cynthia Mitchell Spectrograph (formerly VIRUS-P) on the 2.7 m telescope at McDonald Observatory (Hill et al. 2008). Data for CN, C2, C3, and NH2 were collected over six nights from 2010 July 15 to November 10. The data were processed to form images of the coma for each of the observed species. We have performed azimuthal average division on each of the coma images to examine jet morphology and have investigated the nature of the production of the radical species using our modified vectorial model (Ihalawela et al. 2011). This work enhances the ongoing investigation of the chemistry and outgassing behavior of Hartley 2 as studied by the EPOXI flyby mission.

Observational Tests of the Mars Ocean Hypothesis: Selected MOC and MOLA Results

NASA Technical Reports Server (NTRS)

Parker, T. J.; Banerdt, W. B.

1999-01-01

We have begun a detailed analysis of the evidence for and topography of features identified as potential shorelines that have been im-aged by the Mars Orbiter Camera (MOC) during the Aerobraking Hiatus and Science Phasing Orbit periods of the Mars Global Surveyor (MGS) mission. MOC images, comparable in resolution to high-altitude terrestrial aerial photographs, are particularly well suited to address the morphological expressions of these features at scales comparable to known shore morphologies on Earth. Particularly useful are examples of detailed relationships between potential shore features, such as erosional (and depositional) terraces have been cut into "familiar" pre-existing structures and topography in a fashion that points to a shoreline interpretation as the most likely mechanism for their formation. Additional information is contained in the original extended abstract.

Monitoring of activated sludge settling ability through image analysis: validation on full-scale wastewater treatment plants.

PubMed

Mesquita, D P; Dias, O; Amaral, A L; Ferreira, E C

2009-04-01

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid-liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.

[Comparation on Haversian system between human and animal bones by imaging analysis].

PubMed

Lu, Hui-Ling; Zheng, Jing; Yao, Ya-Nan; Chen, Sen; Wang, Hui-Pin; Chen, Li-Xian; Guo, Jing-Yuan

2006-04-01

To explore the differences in Haversian system between human and animal bones through imaging analysis and morphology description. Thirty-five slices grinding from human being as well as dog, pig, cow and sheep bones were observed to compare their structure, then were analysed with the researchful microscope. Plexiform bone or oeston band was not found in human bones; There were significant differences in the shape, size, location, density of Haversian system, between human and animal bones. The amount of Haversian lamella and diameter of central canal in human were the biggest; Significant differences in the central canal diameter and total area percentage between human and animal bones were shown by imaging analysis. (1) Plexiform bone and osteon band could be the exclusive index in human bone; (2) There were significant differences in the structure of Haversian system between human and animal bones; (3) The percentage of central canals total area was valuable in species identification through imaging analysis.

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

PubMed Central

Karaçalı, Bilge; Vamvakidou, Alexandra P; Tözeren, Aydın

2007-01-01

Background Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Methods Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system. Results Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images. Conclusion Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development. PMID:17822559

What can we tell from particle morphology in Mesozoic charcoal assemblages?

NASA Astrophysics Data System (ADS)

Crawford, Alastair; Belcher, Claire

2015-04-01

Sedimentary charcoal particles provide a valuable record of palaeofire activity on both human and geological timescales. Charcoal is both an unambiguous indicator of wildfire, and a means of preservation of plant material in an inert form; thus it records not only the occurrence and extent of wildfire, but also the species affected. While scanning electron microscopy can be usefully employed for precise taxonomic identification of charcoals, the time and cost associated with this limit the extent to which the technique is employed. Morphometric analysis of mesocharcoal particles (c. 125-1000 µm) potentially provides a simple method for obtaining useful information from optical microscopy images. Grass fires have been shown to produce mesocharcoal particles with a higher length-to-width ratio than woodland fuel sources. In Holocene archives, aspect ratio measurements are thus used to infer the broad taxonomic affinity of the burned vegetation. Since Mesozoic charcoals display similarly heterogeneous morphologies, we investigate whether there is a similar potential to infer the broad botanical affinities of Mesozoic charcoal assemblages from simple morphological metrics. We have used image analysis to analyse a range of Jurassic and Cretaceous sedimentary rocks representing different vegetation communities and depositional environments, and also to determine the range of charcoal particle morphologies which can be produced from different modern taxa under laboratory conditions. We find that modern charcoals break down into mesocharcoal particles of very variable aspect ratio, and this appears to be dependent on taxonomic position. Our analysis of fragmented laboratory-produced charcoals indicates that pteridophytes produce much more elongate particles than either conifers or non-grass angiosperms. We suggest that for charcoal assemblages that predate the evolution of grasses, high average aspect ratios may be a useful indicator of the burning of a pteridophyte-dominated flora.

Morphologic dating of fault scarps using airborne laser swath mapping (ALSM) data

USGS Publications Warehouse

Hilley, G.E.; Delong, S.; Prentice, C.; Blisniuk, K.; Arrowsmith, J.R.

2010-01-01

Models of fault scarp morphology have been previously used to infer the relative age of different fault scarps in a fault zone using labor-intensive ground surveying. We present a method for automatically extracting scarp morphologic ages within high-resolution digital topography. Scarp degradation is modeled as a diffusive mass transport process in the across-scarp direction. The second derivative of the modeled degraded fault scarp was normalized to yield the best-fitting (in a least-squared sense) scarp height at each point, and the signal-to-noise ratio identified those areas containing scarp-like topography. We applied this method to three areas along the San Andreas Fault and found correspondence between the mapped geometry of the fault and that extracted by our analysis. This suggests that the spatial distribution of scarp ages may be revealed by such an analysis, allowing the recent temporal development of a fault zone to be imaged along its length.

Integration of co-localized glandular morphometry and protein biomarker expression in immunofluorescent images for prostate cancer prognosis

NASA Astrophysics Data System (ADS)

Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

2015-03-01

Immunofluorescent (IF) image analysis of tissue pathology has proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. However, while biomarker and glandular morphometric features have been combined as separate predictors in multivariate models, there is a lack of integrative features for biomarkers co-localized within specific morphological sub-types; for example the evaluation of androgen receptor (AR) expression within Gleason 3 glands only. In this work we propose a novel framework employing multiple techniques to generate integrated metrics of morphology and biomarker expression. We demonstrate the utility of the approaches in predicting clinical disease progression in images from 326 prostate biopsies and 373 prostatectomies. Our proposed integrative approaches yield significant improvements over existing IF image feature metrics. This work presents some of the first algorithms for generating innovative characteristics in tissue diagnostics that integrate co-localized morphometry and protein biomarker expression.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images.

PubMed

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Phase imaging microscopy for the diagnostics of plasma-cell interaction

NASA Astrophysics Data System (ADS)

Ohene, Yolanda; Marinov, Ilya; de Laulanié, Lucie; Dupuy, Corinne; Wattelier, Benoit; Starikovskaia, Svetlana

2015-06-01

Phase images of biological specimens were obtained by the method of Quadriwave Lateral Shearing Interferometry (QWLSI). The QWLSI technique produces, at high resolution, phase images of the cells having been exposed to a plasma treatment and enables the quantitative analysis of the changes in the surface area of the cells over time. Morphological changes in the HTori normal thyroid cells were demonstrated using this method. There was a comparison of the cell behaviour between control cells, cells treated by plasma of a nanosecond dielectric barrier discharge, including cells pre-treated by catalase, and cells treated with an equivalent amount of H2O2. The major changes in the cell membrane morphology were observed at only 5 min after the plasma treatment. The primary role of reactive oxygen species (ROS) in this degradation is suggested. Deformation and condensation of the cell nucleus were observed 2-3 h after the treatment and are supposedly related to apoptosis induction. The coupling of the phase QWLSI with immunofluorescence imaging would give a deeper insight into the mechanisms of plasma induced cell death.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images

NASA Astrophysics Data System (ADS)

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Next-generation morphological character discovery and evaluation: an X-ray micro-CT enhanced revision of the ant genus Zasphinctus Wheeler (Hymenoptera, Formicidae, Dorylinae) in the Afrotropics.

PubMed

Garcia, Francisco Hita; Fischer, Georg; Liu, Cong; Audisio, Tracy L; Economo, Evan P

2017-01-01

New technologies for imaging and analysis of morphological characters offer opportunities to enhance revisionary taxonomy and better integrate it with the rest of biology. In this study, we revise the Afrotropical fauna of the ant genus Zasphinctus Wheeler, and use high-resolution X-ray microtomography (micro-CT) to analyse a number of morphological characters of taxonomic and biological interest. We recognise and describe three new species: Z. obamai sp. n. , Z. sarowiwai sp. n. , and Z. wilsoni sp. n. The species delimitations are based on the morphological examination of all physical specimens in combination with 3D scans and volume reconstructions. Based on this approach, we present a new taxonomic discrimination system for the regional fauna that consists of a combination of easily observable morphological characters visible at magnifications of around 80-100 ×, less observable characters that require higher magnifications, as well as characters made visible through virtual dissections that would otherwise require destructive treatment. Zasphinctus are rarely collected ants and the material available to us is comparatively scarce. Consequently, we explore the use of micro-CT as a non-invasive tool for the virtual examination, manipulation, and dissection of such rare material. Furthermore, we delineate the treated species by providing a diagnostic character matrix illustrated by numerous images and supplement that with additional evidence in the form of stacked montage images, 3D PDFs and 3D rotation videos of scans of major body parts and full body (in total we provide 16 stacked montage photographs, 116 images of 3D reconstructions, 15 3D rotation videos, and 13 3D PDFs). In addition to the comparative morphology analyses used for species delimitations, we also apply micro-CT data to examine certain traits, such as mouthparts, cuticle thickness, and thoracic and abdominal muscles in order to assess their taxonomic usefulness or gain insights into the natural history of the genus. The complete datasets comprising the raw micro-CT data, 3D PDFs, 3D rotation videos, still images of 3D models, and coloured montage photos have been made available online as cybertypes (Dryad, http://dx.doi.org/10.5061/dryad.4s3v1).

Next-generation morphological character discovery and evaluation: an X-ray micro-CT enhanced revision of the ant genus Zasphinctus Wheeler (Hymenoptera, Formicidae, Dorylinae) in the Afrotropics

PubMed Central

Garcia, Francisco Hita; Fischer, Georg; Liu, Cong; Audisio, Tracy L.; Economo, Evan P.

2017-01-01

Abstract New technologies for imaging and analysis of morphological characters offer opportunities to enhance revisionary taxonomy and better integrate it with the rest of biology. In this study, we revise the Afrotropical fauna of the ant genus Zasphinctus Wheeler, and use high-resolution X-ray microtomography (micro-CT) to analyse a number of morphological characters of taxonomic and biological interest. We recognise and describe three new species: Z. obamai sp. n., Z. sarowiwai sp. n., and Z. wilsoni sp. n. The species delimitations are based on the morphological examination of all physical specimens in combination with 3D scans and volume reconstructions. Based on this approach, we present a new taxonomic discrimination system for the regional fauna that consists of a combination of easily observable morphological characters visible at magnifications of around 80–100 ×, less observable characters that require higher magnifications, as well as characters made visible through virtual dissections that would otherwise require destructive treatment. Zasphinctus are rarely collected ants and the material available to us is comparatively scarce. Consequently, we explore the use of micro-CT as a non-invasive tool for the virtual examination, manipulation, and dissection of such rare material. Furthermore, we delineate the treated species by providing a diagnostic character matrix illustrated by numerous images and supplement that with additional evidence in the form of stacked montage images, 3D PDFs and 3D rotation videos of scans of major body parts and full body (in total we provide 16 stacked montage photographs, 116 images of 3D reconstructions, 15 3D rotation videos, and 13 3D PDFs). In addition to the comparative morphology analyses used for species delimitations, we also apply micro-CT data to examine certain traits, such as mouthparts, cuticle thickness, and thoracic and abdominal muscles in order to assess their taxonomic usefulness or gain insights into the natural history of the genus. The complete datasets comprising the raw micro-CT data, 3D PDFs, 3D rotation videos, still images of 3D models, and coloured montage photos have been made available online as cybertypes (Dryad, http://dx.doi.org/10.5061/dryad.4s3v1). PMID:29362522

Image analysis of ocular fundus for retinopathy characterization

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

Ushizima, Daniela; Cuadros, Jorge

2010-02-05

Automated analysis of ocular fundus images is a common procedure in countries as England, including both nonemergency examination and retinal screening of patients with diabetes mellitus. This involves digital image capture and transmission of the images to a digital reading center for evaluation and treatment referral. In collaboration with the Optometry Department, University of California, Berkeley, we have tested computer vision algorithms to segment vessels and lesions in ground-truth data (DRIVE database) and hundreds of images of non-macular centric and nonuniform illumination views of the eye fundus from EyePACS program. Methods under investigation involve mathematical morphology (Figure 1) for imagemore » enhancement and pattern matching. Recently, we have focused in more efficient techniques to model the ocular fundus vasculature (Figure 2), using deformable contours. Preliminary results show accurate segmentation of vessels and high level of true-positive microaneurysms.« less

Microscopic image analysis for reticulocyte based on watershed algorithm

NASA Astrophysics Data System (ADS)

Wang, J. Q.; Liu, G. F.; Liu, J. G.; Wang, G.

2007-12-01

We present a watershed-based algorithm in the analysis of light microscopic image for reticulocyte (RET), which will be used in an automated recognition system for RET in peripheral blood. The original images, obtained by micrography, are segmented by modified watershed algorithm and are recognized in term of gray entropy and area of connective area. In the process of watershed algorithm, judgment conditions are controlled according to character of the image, besides, the segmentation is performed by morphological subtraction. The algorithm was simulated with MATLAB software. It is similar for automated and manual scoring and there is good correlation(r=0.956) between the methods, which is resulted from 50 pieces of RET images. The result indicates that the algorithm for peripheral blood RETs is comparable to conventional manual scoring, and it is superior in objectivity. This algorithm avoids time-consuming calculation such as ultra-erosion and region-growth, which will speed up the computation consequentially.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Automated detection of exudates for diabetic retinopathy screening

NASA Astrophysics Data System (ADS)

Fleming, Alan D.; Philip, Sam; Goatman, Keith A.; Williams, Graeme J.; Olson, John A.; Sharp, Peter F.

2007-12-01

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13 219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy.

An overview of state-of-the-art image restoration in electron microscopy.

PubMed

Roels, J; Aelterman, J; Luong, H Q; Lippens, S; Pižurica, A; Saeys, Y; Philips, W

2018-06-08

In Life Science research, electron microscopy (EM) is an essential tool for morphological analysis at the subcellular level as it allows for visualization at nanometer resolution. However, electron micrographs contain image degradations such as noise and blur caused by electromagnetic interference, electron counting errors, magnetic lens imperfections, electron diffraction, etc. These imperfections in raw image quality are inevitable and hamper subsequent image analysis and visualization. In an effort to mitigate these artefacts, many electron microscopy image restoration algorithms have been proposed in the last years. Most of these methods rely on generic assumptions on the image or degradations and are therefore outperformed by advanced methods that are based on more accurate models. Ideally, a method will accurately model the specific degradations that fit the physical acquisition settings. In this overview paper, we discuss different electron microscopy image degradation solutions and demonstrate that dedicated artefact regularisation results in higher quality restoration and is applicable through recently developed probabilistic methods. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Morphologic identification of atypical chronic lymphocytic leukemia by digital microscopy.

PubMed

Marionneaux, S; Maslak, P; Keohane, E M

2014-08-01

Atypical chronic lymphocytic leukemia (aCLL) is a morphologic variant found in approximately 25% of patients with chronic lymphocytic leukemia (CLL). Although aCLL has a more aggressive course compared to typical CLL (tCLL), it is not usually reported. This retrospective study used digital microscopy to morphologically classify CLL patients as aCLL or tCLL, and determined the prevalence of prognostic markers in each group. CellaVision AB (Lund, Sweden) was used to evaluate lymphocyte morphology on archived blood films of 97 CLL patients, and results of their prognostic marker analysis at diagnosis were obtained. The unpaired t-test, Chi-square, or Fisher's Exact test were used for statistical analysis. 27% of CLL cases were morphologically classified as aCLL. The aCLL group had a higher prevalence of trisomy 12, unmutated IgVH, and CD38 expression (markers associated with poor prognosis), and a lower prevalence of 13q14 deletions compared to tCLL; this was statistically significant. Using digital imaging to identify aCLL is feasible, economical, and may provide clinically relevant prognostic information at diagnosis and during periodic monitoring. Further study of a larger number of patients is needed to assess the clinical utility of reporting aCLL morphology. © 2013 John Wiley & Sons Ltd.

Research on tomato seed vigor based on X-ray digital image

NASA Astrophysics Data System (ADS)

Zhao, Xueguan; Gao, Yuanyuan; Wang, Xiu; Li, Cuiling; Wang, Songlin; Feng, Qinghun

2016-10-01

Seed size, interior abnormal and damage of the tomato seeds will affect the germination. The purpose of this paper was to study the relationship between the internal morphology, seed size and seed germination of tomato. The preprocessing algorithm of X-ray image of tomato seeds was studied, and the internal structure characteristics of tomato seeds were extracted by image processing algorithm. By developing the image processing software, the cavity area between embryo and endosperm and the whole seed zone were determined. According to the difference of area of embryo and endosperm and Internal structural condition, seeds were divided into six categories, Respectively for three kinds of tomato seed germination test, the relationship between seed vigor and seed size , internal free cavity was explored through germination experiment. Through seedling evaluation test found that X-ray image analysis provide a perfect view of the inside part of the seed and seed morphology research methods. The larger the area of the endosperm and the embryo, the greater the probability of healthy seedlings sprout from the same size seeds. Mechanical damage adversely effects on seed germination, deterioration of tissue prone to produce week seedlings and abnormal seedlings.

Quantitative nanoscopy: Tackling sampling limitations in (S)TEM imaging of polymers and composites.

PubMed

Gnanasekaran, Karthikeyan; Snel, Roderick; de With, Gijsbertus; Friedrich, Heiner

2016-01-01

Sampling limitations in electron microscopy questions whether the analysis of a bulk material is representative, especially while analyzing hierarchical morphologies that extend over multiple length scales. We tackled this problem by automatically acquiring a large series of partially overlapping (S)TEM images with sufficient resolution, subsequently stitched together to generate a large-area map using an in-house developed acquisition toolbox (TU/e Acquisition ToolBox) and stitching module (TU/e Stitcher). In addition, we show that quantitative image analysis of the large scale maps provides representative information that can be related to the synthesis and process conditions of hierarchical materials, which moves electron microscopy analysis towards becoming a bulk characterization tool. We demonstrate the power of such an analysis by examining two different multi-phase materials that are structured over multiple length scales. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of imaging biomarkers for identification of single cancer cells in blood

NASA Astrophysics Data System (ADS)

Odaka, Masao; Kim, Hyonchol; Girault, Mathias; Hattori, Akihiro; Terazono, Hideyuki; Matsuura, Kenji; Yasuda, Kenji

2015-06-01

A method of discriminating single cancer cells from whole blood cells based on their morphological visual characteristics (i.e., “imaging biomarker”) was examined. Cells in healthy rat blood, a cancer cell line (MAT-LyLu), and cells in cancer-cell-implanted rat blood were chosen as models, and their bright-field (BF, whole-cell morphology) and fluorescence (FL, nucleus morphology) images were taken by an on-chip multi-imaging flow cytometry system and compared. Eight imaging biomarker indices, i.e., cellular area in a BF image, nucleus area in an FL image, area ratio of a whole cell and its nucleus, distance of the mass center between a whole cell and nucleus, cellular and nucleus perimeter, and perimeter ratios were calculated and analyzed using the BF and FL images taken. Results show that cancer cells can be clearly distinguished from healthy blood cells using correlation diagrams for cellular and nucleus areas as two different categories. Moreover, a portion of cancer cells showed a low nucleus perimeter ratio less than 0.9 because of the irregular nucleus morphologies of cancer cells. These results indicate that the measurements of imaging biomarkers are practically applicable to identifying cancer cells in blood.

On the Origins of Starburst and Poststarburst Galaxies in Nearby Clusters

NASA Astrophysics Data System (ADS)

Caldwell, Nelson; Rose, James A.; Dendy, Kristi

1999-01-01

Hubble Space Telescope (HST) Wide Field Planetary Camera 2 images in B (F450W) and I (F814W) have been obtained for three starburst (SB) and two poststarburst (PSB) galaxies in the Coma Cluster and for three such galaxies in the cluster DC 048-52. V (F555W) and I images for an additional PSB galaxy in Coma have been extracted from the HST archive. Six of these galaxies were previously classified as E/S0 on the basis of ground-based images, two as Sa, and the other as an irregular. The HST images reveal these SB/PSB galaxies to be heterogeneous in morphology. Nevertheless, a common theme is that many of them, especially the SB galaxies, tend to have centralized spiral structure that appears simply as a bright ``bulge'' on ground-based images. In addition, while some PSB galaxies exhibit distinct spiral structure, on the whole they have smoother morphologies than the SB galaxies. The morphologies and luminosity profiles are generally consistent with substantial starbursts, in the form of centralized spiral structure (the SB galaxies), that fade into smoother morphologies (the PSB galaxies), with lingering spectroscopic evidence for past central starbursts. An important point is that the PSB galaxies retain disks; i.e., they have not evolved into spheroidal systems. While the morphologies revealed in the HST images are heterogeneous, and thus may not fit well into a single picture, we see evidence in several cases that the morphologies and centralized star formation have been driven by external tidal perturbations. We discuss several physical mechanisms for inducing star formation in cluster galaxies with a view toward explaining the particular morphologies seen in the HST images.

Identification of nodes and internodes of chopped biomass stems by Image analysis

USDA-ARS?s Scientific Manuscript database

Separating the morphological components of biomass leads to better handling, more efficient processing as well as value added product generation, as these components vary in their chemical composition and can be preferentially utilized. Nodes and internodes of biomass stems have distinct chemical co...

Transport Phenomena and Interfacial Kinetics in Multiphase Combustion Systems

DTIC Science & Technology

1993-08-01

morphological analysis using electron microscope images. Aggregate data obtained from CH4 flames seeded with titanium tetra- isopropoxide (TTIP-) vapor are now... Titanium tetra- isopropoxide 6. APPENDICES (Complete Papers Published During 2/15/92-2/14/93 Period; including Form 298 for each) HIGH TEMPERATURE CHEMICAL

Morphological-transformation-based technique of edge detection and skeletonization of an image using a single spatial light modulator

NASA Astrophysics Data System (ADS)

Munshi, Soumika; Datta, A. K.

2003-03-01

A technique of optically detecting the edge and skeleton of an image by defining shift operations for morphological transformation is described. A (2 × 2) source array, which acts as the structuring element of morphological operations, casts four angularly shifted optical projections of the input image. The resulting dilated image, when superimposed with the complementary input image, produces the edge image. For skeletonization, the source array casts four partially overlapped output images of the inverted input image, which is negated, and the resultant image is recorded in a CCD camera. This overlapped eroded image is again eroded and then dilated, producing an opened image. The difference between the eroded and opened image is then computed, resulting in a thinner image. This procedure of obtaining a thinned image is iterated until the difference image becomes zero, maintaining the connectivity conditions. The technique has been optically implemented using a single spatial modulator and has the advantage of single-instruction parallel processing of the image. The techniques have been tested both for binary and grey images.

Automatic registration of multi-modal microscopy images for integrative analysis of prostate tissue sections.

PubMed

Lippolis, Giuseppe; Edsjö, Anders; Helczynski, Leszek; Bjartell, Anders; Overgaard, Niels Chr

2013-09-05

Prostate cancer is one of the leading causes of cancer related deaths. For diagnosis, predicting the outcome of the disease, and for assessing potential new biomarkers, pathologists and researchers routinely analyze histological samples. Morphological and molecular information may be integrated by aligning microscopic histological images in a multiplex fashion. This process is usually time-consuming and results in intra- and inter-user variability. The aim of this study is to investigate the feasibility of using modern image analysis methods for automated alignment of microscopic images from differently stained adjacent paraffin sections from prostatic tissue specimens. Tissue samples, obtained from biopsy or radical prostatectomy, were sectioned and stained with either hematoxylin & eosin (H&E), immunohistochemistry for p63 and AMACR or Time Resolved Fluorescence (TRF) for androgen receptor (AR). Image pairs were aligned allowing for translation, rotation and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale invariant image transform (SIFT), followed by the well-known RANSAC protocol for finding point correspondences and finally aligned by Procrustes fit. The Registration results were evaluated using both visual and quantitative criteria as defined in the text. Three experiments were carried out. First, images of consecutive tissue sections stained with H&E and p63/AMACR were successfully aligned in 85 of 88 cases (96.6%). The failures occurred in 3 out of 13 cores with highly aggressive cancer (Gleason score ≥ 8). Second, TRF and H&E image pairs were aligned correctly in 103 out of 106 cases (97%).The third experiment considered the alignment of image pairs with the same staining (H&E) coming from a stack of 4 sections. The success rate for alignment dropped from 93.8% in adjacent sections to 22% for sections furthest away. The proposed method is both reliable and fast and therefore well suited for automatic segmentation and analysis of specific areas of interest, combining morphological information with protein expression data from three consecutive tissue sections. Finally, the performance of the algorithm seems to be largely unaffected by the Gleason grade of the prostate tissue samples examined, at least up to Gleason score 7.

Analysis of the shapes of hemocytes of Callista brevisiphonata in vitro (Bivalvia, Veneridae).

PubMed

Karetin, Yu A; Pushchin, I I

2015-08-01

Fractal formalism in conjunction with linear methods of image analysis is suitable for the comparative analysis of such "irregular" shapes (from the point of view of classical Euclidean geometry) as flattened amoeboid cells of invertebrates in vitro. Cell morphology of in vitro spreading hemocytes from the bivalve mollusc Callista brevisiphonata was analyzed using correlation, factor and cluster analysis. Four significantly different cell types were identified on the basis of 36 linear and nonlinear parameters. The analysis confirmed the adequacy of the selected methodology for numerical description of the shape and the adequacy of classification of nonlinear shapes of spread hemocytes belonging to the same species. Investigation has practical significance for the description of the morphology of cultured cells, since cell shape is a result of summation of a number of extracellular and intracellular factors. © 2015 International Society for Advancement of Cytometry.

Box-Counting Method of 2D Neuronal Image: Method Modification and Quantitative Analysis Demonstrated on Images from the Monkey and Human Brain.

PubMed

Rajković, Nemanja; Krstonošić, Bojana; Milošević, Nebojša

2017-01-01

This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree) were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum.

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli

PubMed Central

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

ABSTRACT A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells. PMID:26962703

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli.

PubMed

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells.

Fractal morphology, imaging and mass spectrometry of single aerosol particles in flight.

PubMed

Loh, N D; Hampton, C Y; Martin, A V; Starodub, D; Sierra, R G; Barty, A; Aquila, A; Schulz, J; Lomb, L; Steinbrener, J; Shoeman, R L; Kassemeyer, S; Bostedt, C; Bozek, J; Epp, S W; Erk, B; Hartmann, R; Rolles, D; Rudenko, A; Rudek, B; Foucar, L; Kimmel, N; Weidenspointner, G; Hauser, G; Holl, P; Pedersoli, E; Liang, M; Hunter, M S; Hunter, M M; Gumprecht, L; Coppola, N; Wunderer, C; Graafsma, H; Maia, F R N C; Ekeberg, T; Hantke, M; Fleckenstein, H; Hirsemann, H; Nass, K; White, T A; Tobias, H J; Farquar, G R; Benner, W H; Hau-Riege, S P; Reich, C; Hartmann, A; Soltau, H; Marchesini, S; Bajt, S; Barthelmess, M; Bucksbaum, P; Hodgson, K O; Strüder, L; Ullrich, J; Frank, M; Schlichting, I; Chapman, H N; Bogan, M J

2012-06-27

The morphology of micrometre-size particulate matter is of critical importance in fields ranging from toxicology to climate science, yet these properties are surprisingly difficult to measure in the particles' native environment. Electron microscopy requires collection of particles on a substrate; visible light scattering provides insufficient resolution; and X-ray synchrotron studies have been limited to ensembles of particles. Here we demonstrate an in situ method for imaging individual sub-micrometre particles to nanometre resolution in their native environment, using intense, coherent X-ray pulses from the Linac Coherent Light Source free-electron laser. We introduced individual aerosol particles into the pulsed X-ray beam, which is sufficiently intense that diffraction from individual particles can be measured for morphological analysis. At the same time, ion fragments ejected from the beam were analysed using mass spectrometry, to determine the composition of single aerosol particles. Our results show the extent of internal dilation symmetry of individual soot particles subject to non-equilibrium aggregation, and the surprisingly large variability in their fractal dimensions. More broadly, our methods can be extended to resolve both static and dynamic morphology of general ensembles of disordered particles. Such general morphology has implications in topics such as solvent accessibilities in proteins, vibrational energy transfer by the hydrodynamic interaction of amino acids, and large-scale production of nanoscale structures by flame synthesis.

Segmentation and Quantitative Analysis of Apoptosis of Chinese Hamster Ovary Cells from Fluorescence Microscopy Images.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2017-06-01

Accurate and fast quantitative analysis of living cells from fluorescence microscopy images is useful for evaluating experimental outcomes and cell culture protocols. An algorithm is developed in this work to automatically segment and distinguish apoptotic cells from normal cells. The algorithm involves three steps consisting of two segmentation steps and a classification step. The segmentation steps are: (i) a coarse segmentation, combining a range filter with a marching square method, is used as a prefiltering step to provide the approximate positions of cells within a two-dimensional matrix used to store cells' images and the count of the number of cells for a given image; and (ii) a fine segmentation step using the Active Contours Without Edges method is applied to the boundaries of cells identified in the coarse segmentation step. Although this basic two-step approach provides accurate edges when the cells in a given image are sparsely distributed, the occurrence of clusters of cells in high cell density samples requires further processing. Hence, a novel algorithm for clusters is developed to identify the edges of cells within clusters and to approximate their morphological features. Based on the segmentation results, a support vector machine classifier that uses three morphological features: the mean value of pixel intensities in the cellular regions, the variance of pixel intensities in the vicinity of cell boundaries, and the lengths of the boundaries, is developed for distinguishing apoptotic cells from normal cells. The algorithm is shown to be efficient in terms of computational time, quantitative analysis, and differentiation accuracy, as compared with the use of the active contours method without the proposed preliminary coarse segmentation step.

Automated image analysis of placental villi and syncytial knots in histological sections.

PubMed

Kidron, Debora; Vainer, Ifat; Fisher, Yael; Sharony, Reuven

2017-05-01

Delayed villous maturation and accelerated villous maturation diagnosed in histologic sections are morphologic manifestations of pathophysiological conditions. The inter-observer agreement among pathologists in assessing these conditions is moderate at best. We investigated whether automated image analysis of placental villi and syncytial knots could improve standardization in diagnosing these conditions. Placentas of antepartum fetal death at or near term were diagnosed as normal, delayed or accelerated villous maturation. Histologic sections of 5 cases per group were photographed at ×10 magnification. Automated image analysis of villi and syncytial knots was performed, using ImageJ public domain software. Analysis of hundreds of histologic images was carried out within minutes on a personal computer, using macro commands. Compared to normal placentas, villi from delayed maturation were larger and fewer, with fewer and smaller syncytial knots. Villi from accelerated maturation were smaller. The data were further analyzed according to horizontal placental zones and groups of villous size. Normal placentas can be discriminated from placentas of delayed or accelerated villous maturation using automated image analysis. Automated image analysis of villi and syncytial knots is not equivalent to interpretation by the human eye. Each method has advantages and disadvantages in assessing the 2-dimensional histologic sections representing the complex, 3-dimensional villous tree. Image analysis of placentas provides quantitative data that might help in standardizing and grading of placentas for diagnostic and research purposes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

PubMed Central

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to inter-observer variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literatures. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast (DIC), fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation. PMID:26742143

Raman Imaging of Plant Cell Walls in Sections of Cucumis sativus

PubMed Central

Zeise, Ingrid; Heiner, Zsuzsanna; Holz, Sabine; Joester, Maike; Büttner, Carmen

2018-01-01

Raman microspectra combine information on chemical composition of plant tissues with spatial information. The contributions from the building blocks of the cell walls in the Raman spectra of plant tissues can vary in the microscopic sub-structures of the tissue. Here, we discuss the analysis of 55 Raman maps of root, stem, and leaf tissues of Cucumis sativus, using different spectral contributions from cellulose and lignin in both univariate and multivariate imaging methods. Imaging based on hierarchical cluster analysis (HCA) and principal component analysis (PCA) indicates different substructures in the xylem cell walls of the different tissues. Using specific signals from the cell wall spectra, analysis of the whole set of different tissue sections based on the Raman images reveals differences in xylem tissue morphology. Due to the specifics of excitation of the Raman spectra in the visible wavelength range (532 nm), which is, e.g., in resonance with carotenoid species, effects of photobleaching and the possibility of exploiting depletion difference spectra for molecular characterization in Raman imaging of plants are discussed. The reported results provide both, specific information on the molecular composition of cucumber tissue Raman spectra, and general directions for future imaging studies in plant tissues. PMID:29370089

Raman Imaging of Plant Cell Walls in Sections of Cucumis sativus.

PubMed

Zeise, Ingrid; Heiner, Zsuzsanna; Holz, Sabine; Joester, Maike; Büttner, Carmen; Kneipp, Janina

2018-01-25

Raman microspectra combine information on chemical composition of plant tissues with spatial information. The contributions from the building blocks of the cell walls in the Raman spectra of plant tissues can vary in the microscopic sub-structures of the tissue. Here, we discuss the analysis of 55 Raman maps of root, stem, and leaf tissues of Cucumis sativus , using different spectral contributions from cellulose and lignin in both univariate and multivariate imaging methods. Imaging based on hierarchical cluster analysis (HCA) and principal component analysis (PCA) indicates different substructures in the xylem cell walls of the different tissues. Using specific signals from the cell wall spectra, analysis of the whole set of different tissue sections based on the Raman images reveals differences in xylem tissue morphology. Due to the specifics of excitation of the Raman spectra in the visible wavelength range (532 nm), which is, e.g., in resonance with carotenoid species, effects of photobleaching and the possibility of exploiting depletion difference spectra for molecular characterization in Raman imaging of plants are discussed. The reported results provide both, specific information on the molecular composition of cucumber tissue Raman spectra, and general directions for future imaging studies in plant tissues.

Conventional MRI features for predicting the clinical outcome of patients with invasive placenta

PubMed Central

Chen, Ting; Xu, Xiao-Quan; Shi, Hai-Bin; Yang, Zheng-Qiang; Zhou, Xin; Pan, Yi

2017-01-01

PURPOSE We aimed to evaluate whether morphologic magnetic resonance imaging (MRI) features could help to predict the maternal outcome after uterine artery embolization (UAE)-assisted cesarean section (CS) in patients with invasive placenta previa. METHODS We retrospectively reviewed the MRI data of 40 pregnant women who have undergone UAE-assisted cesarean section due to suspected high risk of massive hemorrhage caused by invasive placenta previa. Patients were divided into two groups based on the maternal outcome (good-outcome group: minor hemorrhage and uterus preserved; poor-outcome group: significant hemorrhage or emergency hysterectomy). Morphologic MRI features were compared between the two groups. Multivariate logistic regression analysis was used to identify the most valuable variables, and predictive value of the identified risk factor was determined. RESULTS Low signal intensity bands on T2-weighted imaging (P < 0.001), placenta percreta (P = 0.011), and placental cervical protrusion sign (P = 0.002) were more frequently observed in patients with poor outcome. Low signal intensity bands on T2-weighted imaging was the only significant predictor of poor maternal outcome in multivariate analysis (P = 0.020; odds ratio, 14.79), with 81.3% sensitivity and 84.3% specificity. CONCLUSION Low signal intensity bands on T2-weighted imaging might be a predictor of poor maternal outcome after UAE-assisted cesarean section in patients with invasive placenta previa. PMID:28345524

Present and future in the use of micro-CT scanner 3D analysis for the study of dental and root canal morphology.

PubMed

Grande, Nicola M; Plotino, Gianluca; Gambarini, Gianluca; Testarelli, Luca; D'Ambrosio, Ferdinando; Pecci, Raffaella; Bedini, Rossella

2012-01-01

The goal of the present article is to illustrate and analyze the applications and the potential of microcomputed tomography (micro-CT) in the analysis of tooth anatomy and root canal morphology. The authors performed a micro-CT analysis of the following different teeth: maxillary first molars with a second canal in the mesiobuccal (MB) root, mandibular first molars with complex anatomy in the mesial root, premolars with single and double roots and with complicated apical anatomy. The hardware device used in this study was a desktop X-ray microfocus CT scanner (SkyScan 1072, SkyScan bvba, Aartselaar, Belgium). A specific software ResolveRT Amira (Visage Imaging) was used for the 3D analysis and imaging. The authors obtained three-dimensional images from 15 teeth. It was possible to precisely visualize and analyze external and internal anatomy of teeth, showing the finest details. Among the 5 upper molars analyzed, in three cases, the MB canals joined into one canal, while in the other two molars the two mesial canals were separate. Among the lower molars two of the five samples exhibited a single canal in the mesial root, which had a broad, flat appearance in a mesiodistal dimension. In the five premolar teeth, the canals were independent; however, the apical delta and ramifications of the root canals were quite complex. Micro-CT offers a simple and reproducible technique for 3D noninvasive assessment of the anatomy of root canal systems.

Depth-resolved imaging of colon tumor using optical coherence tomography and fluorescence laminar optical tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tang, Qinggong; Frank, Aaron; Wang, Jianting; Chen, Chao-wei; Jin, Lily; Lin, Jon; Chan, Joanne M.; Chen, Yu

2016-03-01

Early detection of neoplastic changes remains a critical challenge in clinical cancer diagnosis and treatment. Many cancers arise from epithelial layers such as those of the gastrointestinal (GI) tract. Current standard endoscopic technology is unable to detect those subsurface lesions. Since cancer development is associated with both morphological and molecular alterations, imaging technologies that can quantitative image tissue's morphological and molecular biomarkers and assess the depth extent of a lesion in real time, without the need for tissue excision, would be a major advance in GI cancer diagnostics and therapy. In this research, we investigated the feasibility of multi-modal optical imaging including high-resolution optical coherence tomography (OCT) and depth-resolved high-sensitivity fluorescence laminar optical tomography (FLOT) for structural and molecular imaging. APC (adenomatous polyposis coli) mice model were imaged using OCT and FLOT and the correlated histopathological diagnosis was obtained. Quantitative structural (the scattering coefficient) and molecular imaging parameters (fluorescence intensity) from OCT and FLOT images were developed for multi-parametric analysis. This multi-modal imaging method has demonstrated the feasibility for more accurate diagnosis with 87.4% (87.3%) for sensitivity (specificity) which gives the most optimal diagnosis (the largest area under receiver operating characteristic (ROC) curve). This project results in a new non-invasive multi-modal imaging platform for improved GI cancer detection, which is expected to have a major impact on detection, diagnosis, and characterization of GI cancers, as well as a wide range of epithelial cancers.

High content analysis of phagocytic activity and cell morphology with PuntoMorph.

PubMed

Al-Ali, Hassan; Gao, Han; Dalby-Hansen, Camilla; Peters, Vanessa Ann; Shi, Yan; Brambilla, Roberta

2017-11-01

Phagocytosis is essential for maintenance of normal homeostasis and healthy tissue. As such, it is a therapeutic target for a wide range of clinical applications. The development of phenotypic screens targeting phagocytosis has lagged behind, however, due to the difficulties associated with image-based quantification of phagocytic activity. We present a robust algorithm and cell-based assay system for high content analysis of phagocytic activity. The method utilizes fluorescently labeled beads as a phagocytic substrate with defined physical properties. The algorithm employs statistical modeling to determine the mean fluorescence of individual beads within each image, and uses the information to conduct an accurate count of phagocytosed beads. In addition, the algorithm conducts detailed and sophisticated analysis of cellular morphology, making it a standalone tool for high content screening. We tested our assay system using microglial cultures. Our results recapitulated previous findings on the effects of microglial stimulation on cell morphology and phagocytic activity. Moreover, our cell-level analysis revealed that the two phenotypes associated with microglial activation, specifically cell body hypertrophy and increased phagocytic activity, are not highly correlated. This novel finding suggests the two phenotypes may be under the control of distinct signaling pathways. We demonstrate that our assay system outperforms preexisting methods for quantifying phagocytic activity in multiple dimensions including speed, accuracy, and resolution. We provide a framework to facilitate the development of high content assays suitable for drug screening. For convenience, we implemented our algorithm in a standalone software package, PuntoMorph. Copyright © 2017 Elsevier B.V. All rights reserved.

Oufti: An integrated software package for high-accuracy, high-throughput quantitative microscopy analysis

PubMed Central

Paintdakhi, Ahmad; Parry, Bradley; Campos, Manuel; Irnov, Irnov; Elf, Johan; Surovtsev, Ivan; Jacobs-Wagner, Christine

2016-01-01

Summary With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today’s single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals, and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis, and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills. PMID:26538279

Mapping spatial patterns with morphological image processing

Treesearch

Peter Vogt; Kurt H. Riitters; Christine Estreguil; Jacek Kozak; Timothy G. Wade; James D. Wickham

2006-01-01

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as 'perforated,' 'edge,' 'patch,' and 'core' with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the...

Morphological spot counting from stacked images for automated analysis of gene copy numbers by fluorescence in situ hybridization.

PubMed

Grigoryan, Artyom M; Dougherty, Edward R; Kononen, Juha; Bubendorf, Lukas; Hostetter, Galen; Kallioniemi, Olli

2002-01-01

Fluorescence in situ hybridization (FISH) is a molecular diagnostic technique in which a fluorescent labeled probe hybridizes to a target nucleotide sequence of deoxyribose nucleic acid. Upon excitation, each chromosome containing the target sequence produces a fluorescent signal (spot). Because fluorescent spot counting is tedious and often subjective, automated digital algorithms to count spots are desirable. New technology provides a stack of images on multiple focal planes throughout a tissue sample. Multiple-focal-plane imaging helps overcome the biases and imprecision inherent in single-focal-plane methods. This paper proposes an algorithm for global spot counting in stacked three-dimensional slice FISH images without the necessity of nuclei segmentation. It is designed to work in complex backgrounds, when there are agglomerated nuclei, and in the presence of illumination gradients. It is based on the morphological top-hat transform, which locates intensity spikes on irregular backgrounds. After finding signals in the slice images, the algorithm groups these together to form three-dimensional spots. Filters are employed to separate legitimate spots from fluorescent noise. The algorithm is set in a comprehensive toolbox that provides visualization and analytic facilities. It includes simulation software that allows examination of algorithm performance for various image and algorithm parameter settings, including signal size, signal density, and the number of slices.

BEMOVI, software for extracting behavior and morphology from videos, illustrated with analyses of microbes.

PubMed

Pennekamp, Frank; Schtickzelle, Nicolas; Petchey, Owen L

2015-07-01

Microbes are critical components of ecosystems and provide vital services (e.g., photosynthesis, decomposition, nutrient recycling). From the diverse roles microbes play in natural ecosystems, high levels of functional diversity result. Quantifying this diversity is challenging, because it is weakly associated with morphological differentiation. In addition, the small size of microbes hinders morphological and behavioral measurements at the individual level, as well as interactions between individuals. Advances in microbial community genetics and genomics, flow cytometry and digital analysis of still images are promising approaches. They miss out, however, on a very important aspect of populations and communities: the behavior of individuals. Video analysis complements these methods by providing in addition to abundance and trait measurements, detailed behavioral information, capturing dynamic processes such as movement, and hence has the potential to describe the interactions between individuals. We introduce BEMOVI, a package using the R and ImageJ software, to extract abundance, morphology, and movement data for tens to thousands of individuals in a video. Through a set of functions BEMOVI identifies individuals present in a video, reconstructs their movement trajectories through space and time, and merges this information into a single database. BEMOVI is a modular set of functions, which can be customized to allow for peculiarities of the videos to be analyzed, in terms of organisms features (e.g., morphology or movement) and how they can be distinguished from the background. We illustrate the validity and accuracy of the method with an example on experimental multispecies communities of aquatic protists. We show high correspondence between manual and automatic counts and illustrate how simultaneous time series of abundance, morphology, and behavior are obtained from BEMOVI. We further demonstrate how the trait data can be used with machine learning to automatically classify individuals into species and that information on movement behavior improves the predictive ability.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

PubMed

Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

2016-04-01

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost. Copyright © 2016 Elsevier Ltd. All rights reserved.

IFDOTMETER: A New Software Application for Automated Immunofluorescence Analysis.

PubMed

Rodríguez-Arribas, Mario; Pizarro-Estrella, Elisa; Gómez-Sánchez, Rubén; Yakhine-Diop, S M S; Gragera-Hidalgo, Antonio; Cristo, Alejandro; Bravo-San Pedro, Jose M; González-Polo, Rosa A; Fuentes, José M

2016-04-01

Most laboratories interested in autophagy use different imaging software for managing and analyzing heterogeneous parameters in immunofluorescence experiments (e.g., LC3-puncta quantification and determination of the number and size of lysosomes). One solution would be software that works on a user's laptop or workstation that can access all image settings and provide quick and easy-to-use analysis of data. Thus, we have designed and implemented an application called IFDOTMETER, which can run on all major operating systems because it has been programmed using JAVA (Sun Microsystems). Briefly, IFDOTMETER software has been created to quantify a variety of biological hallmarks, including mitochondrial morphology and nuclear condensation. The program interface is intuitive and user-friendly, making it useful for users not familiar with computer handling. By setting previously defined parameters, the software can automatically analyze a large number of images without the supervision of the researcher. Once analysis is complete, the results are stored in a spreadsheet. Using software for high-throughput cell image analysis offers researchers the possibility of performing comprehensive and precise analysis of a high number of images in an automated manner, making this routine task easier. © 2015 Society for Laboratory Automation and Screening.

Single-particle coherent diffractive imaging with a soft x-ray free electron laser: towards soot aerosol morphology

NASA Astrophysics Data System (ADS)

Bogan, Michael J.; Starodub, Dmitri; Hampton, Christina Y.; Sierra, Raymond G.

2010-10-01

The first of its kind, the Free electron LASer facility in Hamburg, FLASH, produces soft x-ray pulses with unprecedented properties (10 fs, 6.8-47 nm, 1012 photons per pulse, 20 µm diameter). One of the seminal FLASH experiments is single-pulse coherent x-ray diffractive imaging (CXDI). CXDI utilizes the ultrafast and ultrabright pulses to overcome resolution limitations in x-ray microscopy imposed by x-ray-induced damage to the sample by 'diffracting before destroying' the sample on sub-picosecond timescales. For many lensless imaging algorithms used for CXDI it is convenient when the data satisfy an oversampling constraint that requires the sample to be an isolated object, i.e. an individual 'free-standing' portion of disordered matter delivered to the centre of the x-ray focus. By definition, this type of matter is an aerosol. This paper will describe the role of aerosol science methodologies used for the validation of the 'diffract before destroy' hypothesis and the execution of the first single-particle CXDI experiments being developed for biological imaging. FLASH CXDI now enables the highest resolution imaging of single micron-sized or smaller airborne particulate matter to date while preserving the native substrate-free state of the aerosol. Electron microscopy offers higher resolution for single-particle analysis but the aerosol must be captured on a substrate, potentially modifying the particle morphology. Thus, FLASH is poised to contribute significant advancements in our knowledge of aerosol morphology and dynamics. As an example, we simulate CXDI of combustion particle (soot) morphology and introduce the concept of extracting radius of gyration of fractal aggregates from single-pulse x-ray diffraction data. Future upgrades to FLASH will enable higher spatially and temporally resolved single-particle aerosol dynamics studies, filling a critical technological need in aerosol science and nanotechnology. Many of the methodologies described for FLASH will directly translate to use at hard x-ray free electron lasers.

Automated Glacier Mapping using Object Based Image Analysis. Case Studies from Nepal, the European Alps and Norway

NASA Astrophysics Data System (ADS)

Vatle, S. S.

2015-12-01

Frequent and up-to-date glacier outlines are needed for many applications of glaciology, not only glacier area change analysis, but also for masks in volume or velocity analysis, for the estimation of water resources and as model input data. Remote sensing offers a good option for creating glacier outlines over large areas, but manual correction is frequently necessary, especially in areas containing supraglacial debris. We show three different workflows for mapping clean ice and debris-covered ice within Object Based Image Analysis (OBIA). By working at the object level as opposed to the pixel level, OBIA facilitates using contextual, spatial and hierarchical information when assigning classes, and additionally permits the handling of multiple data sources. Our first example shows mapping debris-covered ice in the Manaslu Himalaya, Nepal. SAR Coherence data is used in combination with optical and topographic data to classify debris-covered ice, obtaining an accuracy of 91%. Our second example shows using a high-resolution LiDAR derived DEM over the Hohe Tauern National Park in Austria. Breaks in surface morphology are used in creating image objects; debris-covered ice is then classified using a combination of spectral, thermal and topographic properties. Lastly, we show a completely automated workflow for mapping glacier ice in Norway. The NDSI and NIR/SWIR band ratio are used to map clean ice over the entire country but the thresholds are calculated automatically based on a histogram of each image subset. This means that in theory any Landsat scene can be inputted and the clean ice can be automatically extracted. Debris-covered ice can be included semi-automatically using contextual and morphological information.

Can Signal Abnormalities Detected with MR Imaging in Knee Articular Cartilage Be Used to Predict Development of Morphologic Cartilage Defects? 48-Month Data from the Osteoarthritis Initiative

PubMed Central

Gersing, Alexandra S.; Mbapte Wamba, John; Nevitt, Michael C.; McCulloch, Charles E.; Link, Thomas M.

2016-01-01

Purpose To determine the incidence with which morphologic articular cartilage defects develop over 48 months in cartilage with signal abnormalities at baseline magnetic resonance (MR) imaging in comparison with the incidence in articular cartilage without signal abnormalities at baseline. Materials and Methods The institutional review boards of all participating centers approved this HIPAA-compliant study. Right knees of 90 subjects from the Osteoarthritis Initiative (mean age, 55 years ± 8 [standard deviation]; 51% women) with cartilage signal abnormalities but without morphologic cartilage defects at 3.0-T MR imaging and without radiographic osteoarthritis (Kellgren-Lawrence score, 0–1) were frequency matched for age, sex, Kellgren-Lawrence score, and body mass index with right knees in 90 subjects without any signal abnormalities or morphologic defects in the articular cartilage (mean age, 54 years ± 5; 51% women). Individual signal abnormalities (n = 126) on intermediate-weighted fast spin-echo MR images were categorized into four subgrades: subgrade A, hypointense; subgrade B, inhomogeneous; subgrade C, hyperintense; and subgrade D, hyperintense with swelling. The development of morphologic articular cartilage defects (Whole-Organ MR Imaging Score ≥2) at 48 months was analyzed on a compartment level and was compared between groups by using generalized estimating equation logistic regression models. Results Cartilage signal abnormalities were more frequent in the patellofemoral joint than in the tibiofemoral joint (59.5% vs 39.5%). Subgrade A was seen more frequently than were subgrades C and D (36% vs 22%). Incidence of morphologic cartilage defects at 48 months was 57% in cartilage with baseline signal abnormalities, while only 4% of compartments without baseline signal abnormalities developed morphologic defects at 48 months (all compartments combined and each compartment separately, P < .01). The development of morphologic defects was not significantly more likely in any of the subgrades (P = .98) and was significantly associated with progression of bone marrow abnormalities (P = .002). Conclusion Knee cartilage signal abnormalities detected with MR imaging are precursors of morphologic defects with osteoarthritis and may serve as imaging biomarkers with which to assess risk for cartilage degeneration. © RSNA, 2016 PMID:27135833

Quantitative assessment of neurite outgrowth in human embryonic stem cell derived hN2 cells using automated high-content image analysis

EPA Science Inventory

Throughout development neurons undergo a number of morphological changes including neurite outgrowth from the cell body. Exposure to neurotoxic chemicals that interfere with this process may result in permanent deficits in nervous system function. Traditionally, rodent primary ne...

Quantitative assessment of neurite outgrowth in human embryonic stem-cell derived neurons using automated high-content image analysis

EPA Science Inventory

During development neurons undergo a number of morphological changes including neurite outgrowth from the cell body. Exposure to neurotoxicants that interfere with this process may cause in permanent deficits in nervous system function. While many studies have used rodent primary...

Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2009-01-01

Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue) the minimum, maximum, average, and standard deviation within the particle are tracked. These metrics can be used for autonomous analysis of color images from a microscope, video camera, or digital, still image. It can also automatically identify tumor morphology of stained images and has been used to detect stained cell phenomena (see figure).

Morphometric analysis of stab wounds by MSCT and MRI after the instillation of contrast medium.

PubMed

Fais, Paolo; Cecchetto, Giovanni; Boscolo-Berto, Rafael; Toniolo, Matteo; Viel, Guido; Miotto, Diego; Montisci, Massimo; Tagliaro, Franco; Giraudo, Chiara

2016-06-01

To analyze the morphology and depth of stab wounds experimentally produced on human legs amputated for medical reasons using multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) after the instillation of a single contrast medium solution (CMS). For morphological analysis, MSCT and MRI scans were performed before and after the instillation of CMS into the wound cavity. Depth measurements were performed on the sagittal view only after CMS instillation. Subsequently, each wound was dissected using the layer-by-layer technique and the depth was measured by a ruler. One-way between-groups pairwise analysis of variance (ANOVA) and Bland-Altman plot analysis were used for comparing radiological and anatomical measurements. Unenhanced MSCT images did not identify the wound channels, whereas unenhanced MRI evidenced the wound cavity in 50 % of cases. After the instillation of CMS, both MSCT and MRI depicted the wound channel in all the investigated stabbings, although the morphology of the cavity was irregular and did not resemble the shape of the blade. The radiological measurements of the wounds' depth, after the application of CMS, exhibited a high level of agreement (about 95 % at Bland-Altman plot analysis) with the anatomical measurements at dissection. A similar systematic underestimation, however, has been evidenced for MSCT (average 11.4 %; 95 % CI 7-17) and MRI (average 9.6 %; 95 % CI 6-13) data after the instillation of CMS with respect to wound dissection measurements. MSCT and MRI after the instillation of CMS can be used for depicting the morphometric features of stab wounds, although depth measurements are affected by a slight systematic underestimation compared to layer-by-layer dissection.

Interventional Molecular Imaging.

PubMed

Solomon, Stephen B; Cornelis, Francois

2016-04-01

Although molecular imaging has had a dramatic impact on diagnostic imaging, it has only recently begun to be integrated into interventional procedures. Its significant impact is attributed to its ability to provide noninvasive, physiologic information that supplements conventional morphologic imaging. The four major interventional opportunities for molecular imaging are, first, to provide guidance to localize a target; second, to provide tissue analysis to confirm that the target has been reached; third, to provide in-room, posttherapy assessment; and fourth, to deliver targeted therapeutics. With improved understanding and application of(18)F-FDG, as well as the addition of new molecular probes beyond(18)F-FDG, the future holds significant promise for the expansion of molecular imaging into the realm of interventional procedures. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Quantitative imaging of fibrotic and morphological changes in liver of non-alcoholic steatohepatitis (NASH) model mice by second harmonic generation (SHG) and auto-fluorescence (AF) imaging using two-photon excitation microscopy (TPEM).

PubMed

Yamamoto, Shin; Oshima, Yusuke; Saitou, Takashi; Watanabe, Takao; Miyake, Teruki; Yoshida, Osamu; Tokumoto, Yoshio; Abe, Masanori; Matsuura, Bunzo; Hiasa, Yoichi; Imamura, Takeshi

2016-12-01

Non-alcoholic steatohepatitis (NASH) is a common liver disorder caused by fatty liver. Because NASH is associated with fibrotic and morphological changes in liver tissue, a direct imaging technique is required for accurate staging of liver tissue. For this purpose, in this study we took advantage of two label-free optical imaging techniques, second harmonic generation (SHG) and auto-fluorescence (AF), using two-photon excitation microscopy (TPEM). Three-dimensional ex vivo imaging of tissues from NASH model mice, followed by image processing, revealed that SHG and AF are sufficient to quantitatively characterize the hepatic capsule at an early stage and parenchymal morphologies associated with liver disease progression, respectively.

Confocal imaging of whole vertebrate embryos reveals novel insights into molecular and cellular mechanisms of organ development

NASA Astrophysics Data System (ADS)

Hadel, Diana M.; Keller, Bradley B.; Sandell, Lisa L.

2014-03-01

Confocal microscopy has been an invaluable tool for studying cellular or sub-cellular biological processes. The study of vertebrate embryology is based largely on examination of whole embryos and organs. The application of confocal microscopy to immunostained whole mount embryos, combined with three dimensional (3D) image reconstruction technologies, opens new avenues for synthesizing molecular, cellular and anatomical analysis of vertebrate development. Optical cropping of the region of interest enables visualization of structures that are morphologically complex or obscured, and solid surface rendering of fluorescent signal facilitates understanding of 3D structures. We have applied these technologies to whole mount immunostained mouse embryos to visualize developmental morphogenesis of the mammalian inner ear and heart. Using molecular markers of neuron development and transgenic reporters of neural crest cell lineage we have examined development of inner ear neurons that originate from the otic vesicle, along with the supporting glial cells that derive from the neural crest. The image analysis reveals a previously unrecognized coordinated spatial organization between migratory neural crest cells and neurons of the cochleovestibular nerve. The images also enable visualization of early cochlear spiral nerve morphogenesis relative to the developing cochlea, demonstrating a heretofore unknown association of neural crest cells with extending peripheral neurite projections. We performed similar analysis of embryonic hearts in mouse and chick, documenting the distribution of adhesion molecules during septation of the outflow tract and remodeling of aortic arches. Surface rendering of lumen space defines the morphology in a manner similar to resin injection casting and micro-CT.

Imaging of the human choroid with a 1.7 MHz A-scan rate FDML swept source OCT system

NASA Astrophysics Data System (ADS)

Gorczynska, I.; Migacz, J. V.; Jonnal, R.; Zawadzki, R. J.; Poddar, R.; Werner, J. S.

2017-02-01

We demonstrate OCT angiography (OCTA) and Doppler OCT imaging of the choroid in the eyes of two healthy volunteers and in a geographic atrophy case. We show that visualization of specific choroidal layers requires selection of appropriate OCTA methods. We investigate how imaging speed, B-scan averaging and scanning density influence visualization of various choroidal vessels. We introduce spatial power spectrum analysis of OCT en face angiographic projections as a method of quantitative analysis of choroicapillaris morphology. We explore the possibility of Doppler OCT imaging to provide information about directionality of blood flow in choroidal vessels. To achieve these goals, we have developed OCT systems utilizing an FDML laser operating at 1.7 MHz sweep rate, at 1060 nm center wavelength, and with 7.5 μm axial imaging resolution. A correlation mapping OCA method was implemented for visualization of the vessels. Joint Spectral and Time domain OCT (STdOCT) technique was used for Doppler OCT imaging.

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.

Multistage morphological segmentation of bright-field and fluorescent microscopy images

NASA Astrophysics Data System (ADS)

Korzyńska, A.; Iwanowski, M.

2012-06-01

This paper describes the multistage morphological segmentation method (MSMA) for microscopic cell images. The proposed method enables us to study the cell behaviour by using a sequence of two types of microscopic images: bright field images and/or fluorescent images. The proposed method is based on two types of information: the cell texture coming from the bright field images and intensity of light emission, done by fluorescent markers. The method is dedicated to the image sequences segmentation and it is based on mathematical morphology methods supported by other image processing techniques. The method allows for detecting cells in image independently from a degree of their flattening and from presenting structures which produce the texture. It makes use of some synergic information from the fluorescent light emission image as the support information. The MSMA method has been applied to images acquired during the experiments on neural stem cells as well as to artificial images. In order to validate the method, two types of errors have been considered: the error of cell area detection and the error of cell position using artificial images as the "gold standard".

Benefits of utilizing CellProfiler as a characterization tool for U-10Mo nuclear fuel

DOE PAGES

Collette, R.; Douglas, J.; Patterson, L.; ...

2015-05-01

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium-molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellularmore » measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries.« less

Evidences of early aqueous Mars: Implications on the origin of branched valleys in the Ius Chasma, Mars

NASA Astrophysics Data System (ADS)

Martha, Tapas R.; Jain, Nirmala; Vamshi, Gasiganti T.; Vinod Kumar, K.

2017-11-01

This study shows results of morphological and spectroscopic analyses of Ius Chasma and its southern branched valleys using Orbiter datasets such as Mars Reconnaissance Orbiter (MRO)-Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), High Resolution Imaging Science Experiment (MRO-HiRISE) and digital terrain model (HRSC-DTM). Result of the spectral analysis reveals presence of hydrated minerals such as opal, nontronite and vermiculite in the floor and wall rock areas Ius Chasma indicating alteration of parent rock in an water rich environment of early Mars. Topographic gradient and morphological evidences such as V-shaped valleys with theatre shaped stubby channels, dendritic drainage and river piracy indicate that these valleys were initially developed by surface runoff due to episodic floods and further expanded due to groundwater sapping controlled by faults and fractures. Minerals formed by aqueous alteration during valley formation and their intricate association with different morphological domains suggest that surface runoff played a key role in the development of branched valleys south of Ius Chasma on Mars.

Longitudinal study of arteriogenesis with swept source optical coherence tomography and hyperspectral imaging

NASA Astrophysics Data System (ADS)

Poole, Kristin M.; Patil, Chetan A.; Nelson, Christopher E.; McCormack, Devin R.; Madonna, Megan C.; Duvall, Craig L.; Skala, Melissa C.

2014-03-01

Peripheral arterial disease (PAD) is an atherosclerotic disease of the extremities that leads to high rates of myocardial infarction and stroke, increased mortality, and reduced quality of life. PAD is especially prevalent in diabetic patients, and is commonly modeled by hind limb ischemia in mice to study collateral vessel development and test novel therapies. Current techniques used to assess recovery cannot obtain quantitative, physiological data non-invasively. Here, we have applied hyperspectral imaging and swept source optical coherence tomography (OCT) to study longitudinal changes in blood oxygenation and vascular morphology, respectively, intravitally in the diabetic mouse hind limb ischemia model. Additionally, recommended ranges for controlling physiological variability in blood oxygenation with respect to respiration rate and body core temperature were determined from a control animal experiment. In the longitudinal study with diabetic mice, hyperspectral imaging data revealed the dynamics of blood oxygenation recovery distally in the ischemic footpad. In diabetic mice, there is an early increase in oxygenation that is not sustained in the long term. Quantitative analysis of vascular morphology obtained from Hessian-filtered speckle variance OCT volumes revealed temporal dynamics in vascular density, total vessel length, and vessel diameter distribution in the adductor muscle of the ischemic limb. The combination of hyperspectral imaging and speckle variance OCT enabled acquisition of novel functional and morphological endpoints from individual animals, and provides a more robust platform for future preclinical evaluations of novel therapies for PAD.

Manifold learning for automatically predicting articular cartilage morphology in the knee with data from the osteoarthritis initiative (OAI)

NASA Astrophysics Data System (ADS)

Donoghue, C.; Rao, A.; Bull, A. M. J.; Rueckert, D.

2011-03-01

Osteoarthritis (OA) is a degenerative, debilitating disease with a large socio-economic impact. This study looks to manifold learning as an automatic approach to harness the plethora of data provided by the Osteoarthritis Initiative (OAI). We construct several Laplacian Eigenmap embeddings of articular cartilage appearance from MR images of the knee using multiple MR sequences. A region of interest (ROI) defined as the weight bearing medial femur is automatically located in all images through non-rigid registration. A pairwise intensity based similarity measure is computed between all images, resulting in a fully connected graph, where each vertex represents an image and the weight of edges is the similarity measure. Spectral analysis is then applied to these pairwise similarities, which acts to reduce the dimensionality non-linearly and embeds these images in a manifold representation. In the manifold space, images that are close to each other are considered to be more "similar" than those far away. In the experiment presented here we use manifold learning to automatically predict the morphological changes in the articular cartilage by using the co-ordinates of the images in the manifold as independent variables for multiple linear regression. In the study presented here five manifolds are generated from five sequences of 390 distinct knees. We find statistically significant correlations (up to R2 = 0.75), between our predictors and the results presented in the literature.

Association Between Vascular Anatomy and Posterior Communicating Artery Aneurysms.

PubMed

Can, Anil; Ho, Allen L; Emmer, Bart J; Dammers, Ruben; Dirven, Clemens M F; Du, Rose

2015-11-01

Hemodynamic stress, conditioned by the geometry and morphology of the vessel trees, plays an important role in the formation of intracranial aneurysms. The aim of this study was to identify image-based location-specific morphologic parameters that are associated with posterior communicating artery (PCoA) aneurysms. Morphologic parameters obtained from computed tomography angiography of 56 patients with PCoA aneurysms and 23 control patients were evaluated with 3D Slicer, an open-source image analysis software, to generate 3-dimensional models of the aneurysms and surrounding vasculature. Segment lengths, diameters, and vessel-to-vessel angles were examined. To control for genetic and clinical risk factors, the unaffected contralateral side of patients with unilateral PCoA aneurysms was used as a control group for internal carotid artery (ICA)-related parameters. A separate control group with visible PCoAs and aneurysms elsewhere was used as a control group for PCoA-related parameters. Internal carotid artery-related parameters were not statistically different between the PCoA aneurysm and control groups. Univariate and multivariate subgroup analysis for patients with visualized PCoAs demonstrated that a larger PCoA diameter was significantly associated with the presence of a PCoA aneurysm (odds ratio = 12.1, 95% confidence interval = 1.3-17.1, P = 0.04) after adjusting for other morphologic parameters. Larger PCoA diameters are associated with the presence of PCoA aneurysms. These parameters may provide objective metrics to assess aneurysm formation and growth risk stratification in high-risk patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Biomass particle models with realistic morphology and resolved microstructure for simulations of intraparticle transport phenomena

DOE PAGES

Ciesielski, Peter N.; Crowley, Michael F.; Nimlos, Mark R.; ...

2014-12-09

Biomass exhibits a complex microstructure of directional pores that impact how heat and mass are transferred within biomass particles during conversion processes. However, models of biomass particles used in simulations of conversion processes typically employ oversimplified geometries such as spheres and cylinders and neglect intraparticle microstructure. In this study, we develop 3D models of biomass particles with size, morphology, and microstructure based on parameters obtained from quantitative image analysis. We obtain measurements of particle size and morphology by analyzing large ensembles of particles that result from typical size reduction methods, and we delineate several representative size classes. Microstructural parameters, includingmore » cell wall thickness and cell lumen dimensions, are measured directly from micrographs of sectioned biomass. A general constructive solid geometry algorithm is presented that produces models of biomass particles based on these measurements. Next, we employ the parameters obtained from image analysis to construct models of three different particle size classes from two different feedstocks representing a hardwood poplar species ( Populus tremuloides, quaking aspen) and a softwood pine ( Pinus taeda, loblolly pine). Finally, we demonstrate the utility of the models and the effects explicit microstructure by performing finite-element simulations of intraparticle heat and mass transfer, and the results are compared to similar simulations using traditional simplified geometries. In conclusion, we show how the behavior of particle models with more realistic morphology and explicit microstructure departs from that of spherical models in simulations of transport phenomena and that species-dependent differences in microstructure impact simulation results in some cases.« less

Measurements of morphology and refractive indexes on human downy hairs using three-dimensional quantitative phase imaging.

PubMed

Lee, SangYun; Kim, Kyoohyun; Lee, Yuhyun; Park, Sungjin; Shin, Heejae; Yang, Jongwon; Ko, Kwanhong; Park, HyunJoo; Park, YongKeun

2015-01-01

We present optical measurements of morphology and refractive indexes (RIs) of human downy arm hairs using three-dimensional (3-D) quantitative phase imaging techniques. 3-D RI tomograms and high-resolution two-dimensional synthetic aperture images of individual downy arm hairs were measured using a Mach–Zehnder laser interferometric microscopy equipped with a two-axis galvanometer mirror. From the measured quantitative images, the RIs and morphological parameters of downy hairs were noninvasively quantified including the mean RI, volume, cylinder, and effective radius of individual hairs. In addition, the effects of hydrogen peroxide on individual downy hairs were investigated.

[Application of text mining approach to pre-education prior to clinical practice].

PubMed

Koinuma, Masayoshi; Koike, Katsuya; Nakamura, Hitoshi

2008-06-01

We developed a new survey analysis technique to understand students' actual aims for effective pretraining prior to clinical practice. We asked third-year undergraduate students to write fixed-style complete and free sentences on "preparation of drug dispensing." Then, we converted their sentence data in to text style and performed Japanese-language morphologic analysis on the data using language analysis software. We classified key words, which were created on the basis of the word class information of the Japanese language morphologic analysis, into categories based on causes and characteristics. In addition to this, we classified the characteristics into six categories consisting of those concepts including "knowledge," "skill and attitude," "image," etc. with the KJ method technique. The results showed that the awareness of students of "preparation of drug dispensing" tended to be approximately three-fold more frequent in "skill and attitude," "risk," etc. than in "knowledge." Regarding the characteristics in the category of the "image," words like "hard," "challenging," "responsibility," "life," etc. frequently occurred. The results of corresponding analysis showed that the characteristics of the words "knowledge" and "skills and attitude" were independent. As the result of developing a cause-and-effect diagram, it was demonstrated that the phase "hanging tough" described most of the various factors. We thus could understand students' actual feelings by applying text-mining as a new survey analysis technique.

Investigation of the operating conditions to morphology evolution of β-L-glutamic acid during seeded cooling crystallization

NASA Astrophysics Data System (ADS)

Zhang, Fangkun; Liu, Tao; Huo, Yan; Guan, Runduo; Wang, Xue Z.

2017-07-01

In this paper the effects of operating conditions including cooling rate, initial supersaturation, and seeding temperature were investigated on the morphology evolution of β-L-glutamic acid (β-LGA) during seeded cooling crystallization. Based on the results of in-situ image acquisition of the crystal morphology evolution during the crystallization process, it was found that the crystal products tend to be plate-like or short rod-like under a slow cooling rate, low initial supersaturation, and low seeding temperature. In the opposite, the operating conditions of a faster cooling rate, higher initial supersaturation, and higher seeding temperature tend to produce long rod-like or needle-like crystals, and meanwhile, the length and width of crystal products will be increased together with a wider crystal size distribution (CSD). The aspect ratio of crystals, defined by the crystal length over width measured from in-situ or sample images, was taken as a shape index to analyze the crystal morphologies. Based on comparative analysis of the experimental results, guidelines on these operating conditions were given for obtaining the desired crystal shapes, along with the strategies for obtaining a narrower CSD for better product quality. Experimental verifications were performed to illustrate the proposed guidelines on the operating conditions for seeded cooling crystallization of LGA solution.

An image-processing method to detect sub-optical features based on understanding noise in intensity measurements.

PubMed

Bhatia, Tripta

2018-07-01

Accurate quantitative analysis of image data requires that we distinguish between fluorescence intensity (true signal) and the noise inherent to its measurements to the extent possible. We image multilamellar membrane tubes and beads that grow from defects in the fluid lamellar phase of the lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine dissolved in water and water-glycerol mixtures by using fluorescence confocal polarizing microscope. We quantify image noise and determine the noise statistics. Understanding the nature of image noise also helps in optimizing image processing to detect sub-optical features, which would otherwise remain hidden. We use an image-processing technique "optimum smoothening" to improve the signal-to-noise ratio of features of interest without smearing their structural details. A high SNR renders desired positional accuracy with which it is possible to resolve features of interest with width below optical resolution. Using optimum smoothening, the smallest and the largest core diameter detected is of width [Formula: see text] and [Formula: see text] nm, respectively, discussed in this paper. The image-processing and analysis techniques and the noise modeling discussed in this paper can be used for detailed morphological analysis of features down to sub-optical length scales that are obtained by any kind of fluorescence intensity imaging in the raster mode.

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

A robust human face detection algorithm

NASA Astrophysics Data System (ADS)

Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.

2012-01-01

Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.

Automatic single-image-based rain streaks removal via image decomposition.

PubMed

Kang, Li-Wei; Lin, Chia-Wen; Fu, Yu-Hsiang

2012-04-01

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.

Image analysis of pubic bone for age estimation in a computed tomography sample.

PubMed

López-Alcaraz, Manuel; González, Pedro Manuel Garamendi; Aguilera, Inmaculada Alemán; López, Miguel Botella

2015-03-01

Radiology has demonstrated great utility for age estimation, but most of the studies are based on metrical and morphological methods in order to perform an identification profile. A simple image analysis-based method is presented, aimed to correlate the bony tissue ultrastructure with several variables obtained from the grey-level histogram (GLH) of computed tomography (CT) sagittal sections of the pubic symphysis surface and the pubic body, and relating them with age. The CT sample consisted of 169 hospital Digital Imaging and Communications in Medicine (DICOM) archives of known sex and age. The calculated multiple regression models showed a maximum R (2) of 0.533 for females and 0.726 for males, with a high intra- and inter-observer agreement. The method suggested is considered not only useful for performing an identification profile during virtopsy, but also for application in further studies in order to attach a quantitative correlation for tissue ultrastructure characteristics, without complex and expensive methods beyond image analysis.

3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation.

PubMed

Wörz, Stefan; Schenk, Jens-Peter; Alrajab, Abdulsattar; von Tengg-Kobligk, Hendrik; Rohr, Karl; Arnold, Raoul

2016-10-17

Coarctation of the aorta is one of the most common congenital heart diseases. Despite different treatment opportunities, long-term outcome after surgical or interventional therapy is diverse. Serial morphologic follow-up of vessel growth is necessary, because vessel growth cannot be predicted by primer morphology or a therapeutic option. For the analysis of the long-term outcome after therapy of congenital diseases such as aortic coarctation, accurate 3D geometric analysis of the aorta from follow-up 3D medical image data such as magnetic resonance angiography (MRA) is important. However, for an objective, fast, and accurate 3D geometric analysis, an automatic approach for 3D segmentation and quantification of the aorta from pediatric images is required. We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model that requires only relatively few model parameters. Moreover, we include a novel adaptive background-masking scheme used for least-squares model fitting, we use a spatial normalization scheme to align the segmentation results from follow-up examinations, and we determine relevant 3D geometric parameters of the aortic arch. We have evaluated our proposed approach using different 3D synthetic images. Moreover, we have successfully applied the approach to follow-up pediatric 3D MRA image data, we have normalized the 3D segmentation results of follow-up images of individual patients, and we have combined the results of all patients. We also present a quantitative evaluation of our approach for four follow-up 3D MRA images of a patient, which confirms that our approach yields accurate 3D segmentation results. An experimental comparison with two previous approaches demonstrates that our approach yields superior results. From the results, we found that our approach is well suited for the quantification of the 3D geometry of the aortic arch from follow-up pediatric 3D MRA image data. In future work, this will enable to investigate the long-term outcome of different surgical and interventional therapies for aortic coarctation.

Coma Morphology of Recent Comets: C/ISON (2012 S1), C/Pan-STARRS (2012 K1), C/Jacques (2014 E2), and C/Siding Spring (2013 A1)

NASA Astrophysics Data System (ADS)

Knight, Matthew M.; Schleicher, David G.

2014-11-01

We will present preliminary results from recent and upcoming imaging campaigns of four comets using Lowell Observatory’s 4.3-m Discovery Channel Telescope, 42-in Hall Telescope, and/or 31-in telescope: 1. Observations of C/ISON (2012 S1) were carried out from January through November 2013. A small, sunward fan was detected in dust images acquired in March, April, May, and September. Two faint CN features approximately orthogonal to the tail appeared on November 1 and were visible until our final night of data on November 12. This significantly predates their first reported appearance in broadband images on November 14 (Boehnhard et al., CBET 3715; Ye et al., CBET 3718) and suggests that the features were not caused by a catastrophic disruption of the nucleus at that time.2. We observed C/Pan-STARRS (2012 K1) regularly from October 2013 through June 2014 when it entered solar conjunction. Enhanced CN images in May and June 2014 exhibited a side-on pinwheel morphology that varied from night to night; similar morphology was not seen in concurrent dust images. Analysis of the rotation period is underway. 3. C/Jacques (2014 E2) was observed in April, May, and August 2014, and additional observations are scheduled through September 2014. After enhancement of the August images, Jacques exhibited two side-on CN corkscrews roughly orthogonal to the tail. The CN morphology was different from night to night but did not vary noticeably during ~1 hr of observations on a given night. Jacques also exhibited a smaller sunward dust feature in August that did not appear to vary during the observations. We will combine these data with our scheduled observations to investigate periodicity and compare the spatial distribution of multiple gas species. 4. Observations of C/Siding Spring (2013 A1) are scheduled around its close approach to Mars on October 19, 2014. This work is supported by NASA’s Planetary Astronomy Program grants NNX09AB51G and NNX11AD95G.

Magnetic Resonance Imaging (MRI) Analysis of Fibroid Location in Women Achieving Pregnancy After Uterine Artery Embolization

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

Walker, Woodruff J.; Bratby, Mark John

The purpose of this study was to evaluate the fibroid morphology in a cohort of women achieving pregnancy following treatment with uterine artery embolization (UAE) for symptomatic uterine fibroids. A retrospective review of magnetic resonance imaging (MRI) of the uterus was performed to assess pre-embolization fibroid morphology. Data were collected on fibroid size, type, and number and included analysis of follow-up imaging to assess response. There have been 67 pregnancies in 51 women, with 40 live births. Intramural fibroids were seen in 62.7% of the women (32/48). Of these the fibroids were multiple in 16. A further 12 women hadmore » submucosal fibroids, with equal numbers of types 1 and 2. Two of these women had coexistent intramural fibroids. In six women the fibroids could not be individually delineated and formed a complex mass. All subtypes of fibroid were represented in those subgroups of women achieving a live birth versus those who did not. These results demonstrate that the location of uterine fibroids did not adversely affect subsequent pregnancy in the patient population investigated. Although this is only a small qualitative study, it does suggest that all types of fibroids treated with UAE have the potential for future fertility.« less

Indirect Reconstruction of Pore Morphology for Parametric Computational Characterization of Unidirectional Porous Iron.

PubMed

Kovačič, Aljaž; Borovinšek, Matej; Vesenjak, Matej; Ren, Zoran

2018-01-26

This paper addresses the problem of reconstructing realistic, irregular pore geometries of lotus-type porous iron for computer models that allow for simple porosity and pore size variation in computational characterization of their mechanical properties. The presented methodology uses image-recognition algorithms for the statistical analysis of pore morphology in real material specimens, from which a unique fingerprint of pore morphology at a certain porosity level is derived. The representative morphology parameter is introduced and used for the indirect reconstruction of realistic and statistically representative pore morphologies, which can be used for the generation of computational models with an arbitrary porosity. Such models were subjected to parametric computer simulations to characterize the dependence of engineering elastic modulus on the porosity of lotus-type porous iron. The computational results are in excellent agreement with experimental observations, which confirms the suitability of the presented methodology of indirect pore geometry reconstruction for computational simulations of similar porous materials.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

NASA Astrophysics Data System (ADS)

Felix, Simon; Bolzern, Roman; Battaglia, Marina

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

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

Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation ofmore » quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.« less

Label-Free Imaging and Biochemical Characterization of Bovine Sperm Cells

PubMed Central

Ferrara, Maria Antonietta; Di Caprio, Giuseppe; Managò, Stefano; De Angelis, Annalisa; Sirleto, Luigi; Coppola, Giuseppe; De Luca, Anna Chiara

2015-01-01

A full label-free morphological and biochemical characterization is desirable to select spermatozoa during preparation for artificial insemination. In order to study these fundamental parameters, we take advantage of two attractive techniques: digital holography (DH) and Raman spectroscopy (RS). DH presents new opportunities for studying morphological aspect of cells and tissues non-invasively, quantitatively and without the need for staining or tagging, while RS is a very specific technique allowing the biochemical analysis of cellular components with a spatial resolution in the sub-micrometer range. In this paper, morphological and biochemical bovine sperm cell alterations were studied using these techniques. In addition, a complementary DH and RS study was performed to identify X- and Y-chromosome-bearing sperm cells. We demonstrate that the two techniques together are a powerful and highly efficient tool elucidating some important criterions for sperm morphological selection and sex-identification, overcoming many of the limitations associated with existing protocols. PMID:25836358

Opportunities and challenges for digital morphology

PubMed Central

2010-01-01

Advances in digital data acquisition, analysis, and storage have revolutionized the work in many biological disciplines such as genomics, molecular phylogenetics, and structural biology, but have not yet found satisfactory acceptance in morphology. Improvements in non-invasive imaging and three-dimensional visualization techniques, however, permit high-throughput analyses also of whole biological specimens, including museum material. These developments pave the way towards a digital era in morphology. Using sea urchins (Echinodermata: Echinoidea), we provide examples illustrating the power of these techniques. However, remote visualization, the creation of a specialized database, and the implementation of standardized, world-wide accepted data deposition practices prior to publication are essential to cope with the foreseeable exponential increase in digital morphological data. Reviewers This article was reviewed by Marc D. Sutton (nominated by Stephan Beck), Gonzalo Giribet (nominated by Lutz Walter), and Lennart Olsson (nominated by Purificación López-García). PMID:20604956

Lava Morphology Classification of a Fast-Spreading Ridge Using Deep-Towed Sonar Data: East Pacific Rise

NASA Astrophysics Data System (ADS)

Meyer, J.; White, S.

2005-05-01

Classification of lava morphology on a regional scale contributes to the understanding of the distribution and extent of lava flows at a mid-ocean ridge. Seafloor classification is essential to understand the regional undersea environment at midocean ridges. In this study, the development of a classification scheme is found to identify and extract textural patterns of different lava morphologies along the East Pacific Rise using DSL-120 side-scan and ARGO camera imagery. Application of an accurate image classification technique to side-scan sonar allows us to expand upon the locally available visual ground reference data to make the first comprehensive regional maps of small-scale lava morphology present at a mid-ocean ridge. The submarine lava morphologies focused upon in this study; sheet flows, lobate flows, and pillow flows; have unique textures. Several algorithms were applied to the sonar backscatter intensity images to produce multiple textural image layers useful in distinguishing the different lava morphologies. The intensity and spatially enhanced images were then combined and applied to a hybrid classification technique. The hybrid classification involves two integrated classifiers, a rule-based expert system classifier and a machine learning classifier. The complementary capabilities of the two integrated classifiers provided a higher accuracy of regional seafloor classification compared to using either classifier alone. Once trained, the hybrid classifier can then be applied to classify neighboring images with relative ease. This classification technique has been used to map the lava morphology distribution and infer spatial variability of lava effusion rates along two segments of the East Pacific Rise, 17 deg S and 9 deg N. Future use of this technique may also be useful for attaining temporal information. Repeated documentation of morphology classification in this dynamic environment can be compared to detect regional seafloor change.

Cardiac morphology after conditions of microgravity during Cosmos 2044

NASA Technical Reports Server (NTRS)

Goldstein, Margaret A.; Edwards, Robert J.; Schroeter, John P.

1992-01-01

Light- and electron-microscopic studies were performed on cardiac muscle from rats flown on Cosmos 2044 and from four control groups. Average cross-sectional area of myofibers was measured by video analysis of the light-microscopic images of papillary and ventricular muscle samples from all animals. This cross-sectional area was significantly decreased in flight rats (P = 0.03) compared with synchronous controls. Additional findings at the electron microscopic level consistent with this atrophy were obtained by stereological analysis and optical diffraction analysis of papillary muscle samples. Slightly higher mitochondrial volume density values and mitochondria-to-myofibril ratios as well as normal A-band spacings (d1,0) and Z-band spacings of myofibrils were observed in the tail-suspension and flight groups. General morphological features similar to those in ventricular samples from the previous Cosmos 1887 flight were observed.

In vivo automated quantification of quality of apples during storage using optical coherence tomography images

NASA Astrophysics Data System (ADS)

Srivastava, Vishal; Dalal, Devjyoti; Kumar, Anuj; Prakash, Surya; Dalal, Krishna

2018-06-01

Moisture content is an important feature of fruits and vegetables. As 80% of apple content is water, so decreasing the moisture content will degrade the quality of apples (Golden Delicious). The computational and texture features of the apples were extracted from optical coherence tomography (OCT) images. A support vector machine with a Gaussian kernel model was used to perform automated classification. To evaluate the quality of wax coated apples during storage in vivo, our proposed method opens up the possibility of fully automated quantitative analysis based on the morphological features of apples. Our results demonstrate that the analysis of the computational and texture features of OCT images may be a good non-destructive method for the assessment of the quality of apples.

Measurement of Galactic Logarithmic Spiral Arm Pitch Angle Using Two-dimensional Fast Fourier Transform Decomposition

NASA Astrophysics Data System (ADS)

Davis, Benjamin L.; Berrier, Joel C.; Shields, Douglas W.; Kennefick, Julia; Kennefick, Daniel; Seigar, Marc S.; Lacy, Claud H. S.; Puerari, Ivânio

2012-04-01

A logarithmic spiral is a prominent feature appearing in a majority of observed galaxies. This feature has long been associated with the traditional Hubble classification scheme, but historical quotes of pitch angle of spiral galaxies have been almost exclusively qualitative. We have developed a methodology, utilizing two-dimensional fast Fourier transformations of images of spiral galaxies, in order to isolate and measure the pitch angles of their spiral arms. Our technique provides a quantitative way to measure this morphological feature. This will allow comparison of spiral galaxy pitch angle to other galactic parameters and test spiral arm genesis theories. In this work, we detail our image processing and analysis of spiral galaxy images and discuss the robustness of our analysis techniques.

Distinct roles of cell wall biogenesis in yeast morphogenesis as revealed by multivariate analysis of high-dimensional morphometric data

PubMed Central

Okada, Hiroki; Ohnuki, Shinsuke; Roncero, Cesar; Konopka, James B.; Ohya, Yoshikazu

2014-01-01

The cell wall of budding yeast is a rigid structure composed of multiple components. To thoroughly understand its involvement in morphogenesis, we used the image analysis software CalMorph to quantitatively analyze cell morphology after treatment with drugs that inhibit different processes during cell wall synthesis. Cells treated with cell wall–affecting drugs exhibited broader necks and increased morphological variation. Tunicamycin, which inhibits the initial step of N-glycosylation of cell wall mannoproteins, induced morphologies similar to those of strains defective in α-mannosylation. The chitin synthase inhibitor nikkomycin Z induced morphological changes similar to those of mutants defective in chitin transglycosylase, possibly due to the critical role of chitin in anchoring the β-glucan network. To define the mode of action of echinocandin B, a 1,3-β-glucan synthase inhibitor, we compared the morphology it induced with mutants of Fks1 that contains the catalytic domain for 1,3-β-glucan synthesis. Echinocandin B exerted morphological effects similar to those observed in some fks1 mutants, with defects in cell polarity and reduced glucan synthesis activity, suggesting that echinocandin B affects not only 1,3-β-glucan synthesis, but also another functional domain. Thus our multivariate analyses reveal discrete functions of cell wall components and increase our understanding of the pharmacology of antifungal drugs. PMID:24258022

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

A modeling analysis program for the JPL Table Mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1986-01-01

Progress and achievements in the second year are discussed in three main areas: (1) data quality review of the 1981 Region B/C images; (2) data processing activities; and (3) modeling activities. The data quality review revealed that almost all 1981 Region B/C images are of sufficient quality to be valuable in the analyses of the JPL data set. In the second area, the major milestone reached was the successful development and application of complex image-processing software required to render the original image data suitable for modeling analysis studies. In the third area, the lifetime description of sodium atoms in the planet magnetosphere was improved in the model to include the offset dipole nature of the magnetic field as well as an east-west electric field. These improvements are important in properly representing the basic morphology as well as the east-west asymmetries of the sodium cloud.

Automated Dispersion and Orientation Analysis for Carbon Nanotube Reinforced Polymer Composites

PubMed Central

Gao, Yi; Li, Zhuo; Lin, Ziyin; Zhu, Liangjia; Tannenbaum, Allen; Bouix, Sylvain; Wong, C.P.

2012-01-01

The properties of carbon nanotube (CNT)/polymer composites are strongly dependent on the dispersion and orientation of CNTs in the host matrix. Quantification of the dispersion and orientation of CNTs by microstructure observation and image analysis has been demonstrated as a useful way to understand the structure-property relationship of CNT/polymer composites. However, due to the various morphologies and large amount of CNTs in one image, automatic and accurate identification of CNTs has become the bottleneck for dispersion/orientation analysis. To solve this problem, shape identification is performed for each pixel in the filler identification step, so that individual CNT can be exacted from images automatically. The improved filler identification enables more accurate analysis of CNT dispersion and orientation. The obtained dispersion index and orientation index of both synthetic and real images from model compounds correspond well with the observations. Moreover, these indices help to explain the electrical properties of CNT/Silicone composite, which is used as a model compound. This method can also be extended to other polymer composites with high aspect ratio fillers. PMID:23060008

The challenge of cerebral magnetic resonance imaging in neonates: A new method using mathematical morphology for the segmentation of structures including diffuse excessive high signal intensities.

PubMed

Xu, Yongchao; Morel, Baptiste; Dahdouh, Sonia; Puybareau, Élodie; Virzì, Alessio; Urien, Héléne; Géraud, Thierry; Adamsbaum, Catherine; Bloch, Isabelle

2018-05-17

Preterm birth is a multifactorial condition associated with increased morbidity and mortality. Diffuse excessive high signal intensity (DEHSI) has been recently described on T2-weighted MR sequences in this population and thought to be associated with neuropathologies. To date, no robust and reproducible method to assess the presence of white matter hyperintensities has been developed, perhaps explaining the current controversy over their prognostic value. The aim of this paper is to propose a new semi-automated framework to detect DEHSI on neonatal brain MR images having a particular pattern due to the physiological lack of complete myelination of the white matter. A novel method for semi- automatic segmentation of neonatal brain structures and DEHSI, based on mathematical morphology and on max-tree representations of the images is thus described. It is a mandatory first step to identify and clinically assess homogeneous cohorts of neonates for DEHSI and/or volume of any other segmented structures. Implemented in a user-friendly interface, the method makes it straightforward to select relevant markers of structures to be segmented, and if needed, apply eventually manual corrections. This method responds to the increasing need for providing medical experts with semi-automatic tools for image analysis, and overcomes the limitations of visual analysis alone, prone to subjectivity and variability. Experimental results demonstrate that the method is accurate, with excellent reproducibility and with very few manual corrections needed. Although the method was intended initially for images acquired at 1.5T, which corresponds to the usual clinical practice, preliminary results on images acquired at 3T suggest that the proposed approach can be generalized. Copyright © 2018 Elsevier B.V. All rights reserved.

RBCs as microlenses: wavefront analysis and applications

NASA Astrophysics Data System (ADS)

Merola, Francesco; Barroso, Álvaro; Miccio, Lisa; Memmolo, Pasquale; Mugnano, Martina; Ferraro, Pietro; Denz, Cornelia

2017-06-01

Developing the recently discovered concept of RBCs as microlenses, we demonstrate further applications in wavefront analysis and diagnostics. Correlation between RBC's morphology and its behavior as a refractive optical element has been established. In fact, any deviation from the healthy RBC morphology can be seen as additional aberration in the optical wavefront passing through the cell. By this concept, accurate localization of focal spots of RBCs can become very useful in blood disorders identification. Moreover, By modelling RBC as bio-lenses through Zernike polynomials it is possible to identify a series of orthogonal parameters able to recognise RBC shapes. The main improvement concerns the possibility to combine such parameters because of their independence conversely to standard image-based analysis where morphological factors are dependent each-others. We investigate the three-dimensional positioning of such focal spots over time for samples with two different osmolarity conditions, i.e. discocytes and spherocytes. Finally, Zernike polynomials wavefront analysis allows us to study the optical behavior of RBCs under an optically-induced mechanical stress. Detailed wavefront analysis provides comprehensive information about the aberrations induced by the deformation obtained using optical tweezers. This could open new routes for analyzing cell elasticity by examining optical parameters instead of direct but with low resolution strain analysis, thanks to the high sensitivity of the interferometric tool.

Identification of nodes and internodes of chopped biomass stems by Image analysis using profile curvature and slope

USDA-ARS?s Scientific Manuscript database

Morphological components of biomass stems vary in their chemical composition and they can be better utilized when processed after segregation. Within the stem, nodes and internodes have significantly different compositions. The internodes have low ash content and are a better feedstock for bioenergy...

Fractal morphology, imaging and mass spectrometry of single aerosol particles in flight (CXIDB ID 16)

DOE Data Explorer

Loh, N. Duane

2012-06-20

This deposition includes the aerosol diffraction images used for phasing, fractal morphology, and time-of-flight mass spectrometry. Files in this deposition are ordered in subdirectories that reflect the specifics.

Quantifying Three-Dimensional Morphology and RNA from Individual Embryos

PubMed Central

Green, Rebecca M.; Leach, Courtney L.; Hoehn, Natasha; Marcucio, Ralph S.; Hallgrímsson, Benedikt

2017-01-01

Quantitative analysis of morphogenesis aids our understanding of developmental processes by providing a method to link changes in shape with cellular and molecular processes. Over the last decade many methods have been developed for 3D imaging of embryos using microCT scanning to quantify the shape of embryos during development. These methods generally involve a powerful, cross-linking fixative such as paraformaldehyde to limit shrinkage during the CT scan. However, the extended time frames that these embryos are incubated in such fixatives prevent use of the tissues for molecular analysis after microCT scanning. This is a significant problem because it limits the ability to correlate variation in molecular data with morphology at the level of individual embryos. Here, we outline a novel method that allows RNA, DNA or protein isolation following CT scan while also allowing imaging of different tissue layers within the developing embryo. We show shape differences early in craniofacial development (E11.5) between common mouse genetic backgrounds, and demonstrate that we are able to generate RNA from these embryos after CT scanning that is suitable for downstream RT-PCR and RNAseq analyses. PMID:28152580

Synthesis and In vitro Evaluation of Electrodeposited Barium Titanate Coating on Ti6Al4V

PubMed Central

Rahmati, Shahram; Basiriani, Mohammad Basir; Rafienia, Mohammad; Yaghini, Jaber; Raeisi, Keyvan

2016-01-01

Osseointegration has been the concern of implantology for many years. Researchers have used various ceramic coatings for this purpose; however, piezoelectric ceramics (e.g., barium titanate [BTO]) are a novel field of interest. In this regard, BTO (BaTiO3) coating was fabricated by electrophoretic deposition on Ti6Al4V medical alloy, using sol-gel-synthesized nanometer BTO powder. Structure and morphologies were studied using X-ray diffraction and scanning electron microscopy (SEM), respectively. Bioactivity response of coated samples was evaluated by SEM and inductively coupled plasma (ICP) analysis after immersion in simulated body fluid (SBF). Cell compatibility was also studied via MTT assay and SEM imaging. Results showed homogenous coating with cubic structure and crystallite size of about 41 nm. SEM images indicated apatite formation on the coating after 7 days of SBF immersion, and ICP analysis approved ions concentration decrement in SBF. Cells showed flattened morphology in intimate contact with coating after 7 days of culture. Altogether, coated samples demonstrated appropriate bioactivity and biocompatibility. PMID:27186538

Cartilage magnetic resonance imaging techniques at 3 T: current status and future directions.

PubMed

Thakkar, Rashmi S; Subhawong, Ty; Carrino, John A; Chhabra, Avneesh

2011-04-01

Magnetic resonance imaging (MRI) remains the imaging modality of choice for morphological and compositional evaluation of the articular cartilage. Accurate detection and characterization of cartilage lesions are necessary to guide the medical and surgical therapy and are also critical for longitudinal studies of the cartilage. Recent work using 3.0-T MRI systems shows promise in improving detection and characterization of the cartilage lesions, particularly with increasing use of high-resolution and high-contrast 3-dimensional sequences, which allow detailed morphological assessment of cartilage in arbitrary imaging planes. In addition, implementation of biochemical sequences in clinically feasible scan times has a potential in the early detection of cartilage lesions before they become morphologically apparent. This article discusses relative advantages and disadvantages of various commonly used as well as experimental MRI techniques to directly assess the morphology and indirectly evaluate the biochemical composition of the articular cartilage.

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation.

PubMed

Oetjen, Janina; Aichler, Michaela; Trede, Dennis; Strehlow, Jan; Berger, Judith; Heldmann, Stefan; Becker, Michael; Gottschalk, Michael; Kobarg, Jan Hendrik; Wirtz, Stefan; Schiffler, Stefan; Thiele, Herbert; Walch, Axel; Maass, Peter; Alexandrov, Theodore

2013-09-02

MALDI imaging mass spectrometry (MALDI-imaging) has emerged as a spatially-resolved label-free bioanalytical technique for direct analysis of biological samples and was recently introduced for analysis of 3D tissue specimens. We present a new experimental and computational pipeline for molecular analysis of tissue specimens which integrates 3D MALDI-imaging, magnetic resonance imaging (MRI), and histological staining and microscopy, and evaluate the pipeline by applying it to analysis of a mouse kidney. To ensure sample integrity and reproducible sectioning, we utilized the PAXgene fixation and paraffin embedding and proved its compatibility with MRI. Altogether, 122 serial sections of the kidney were analyzed using MALDI-imaging, resulting in a 3D dataset of 200GB comprised of 2million spectra. We show that elastic image registration better compensates for local distortions of tissue sections. The computational analysis of 3D MALDI-imaging data was performed using our spatial segmentation pipeline which determines regions of distinct molecular composition and finds m/z-values co-localized with these regions. For facilitated interpretation of 3D distribution of ions, we evaluated isosurfaces providing simplified visualization. We present the data in a multimodal fashion combining 3D MALDI-imaging with the MRI volume rendering and with light microscopic images of histologically stained sections. Our novel experimental and computational pipeline for 3D MALDI-imaging can be applied to address clinical questions such as proteomic analysis of the tumor morphologic heterogeneity. Examining the protein distribution as well as the drug distribution throughout an entire tumor using our pipeline will facilitate understanding of the molecular mechanisms of carcinogenesis. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterizing Microbial Mat Morphology with Structure from Motion Techniques in Ice-Covered Lake Joyce, McMurdo Dry Valleys, Antarctica

NASA Astrophysics Data System (ADS)

Mackey, T. J.; Leidman, S. Z.; Allen, B.; Hawes, I.; Lawrence, J.; Jungblut, A. D.; Krusor, M.; Coleman, L.; Sumner, D. Y.

2015-12-01

Structure from Motion (SFM) techniques can provide quantitative morphological documentation of otherwise inaccessible benthic ecosystems such as microbial mats in Lake Joyce, a perennially ice-covered lake of the Antarctic McMurdo Dry Valleys (MDV). Microbial mats are a key ecosystem of MDV lakes, and diverse mat morphologies like pinnacles emerge from interactions among microbial behavior, mineralization, and environmental conditions. Environmental gradients can be isolated to test mat growth models, but assessment of mat morphology along these gradients is complicated by their inaccessibility: the Lake Joyce ice cover is 4-5 m thick, water depths containing diverse pinnacle morphologies are 9-14 m, and relevant mat features are cm-scale. In order to map mat pinnacle morphology in different sedimentary settings, we deployed drop cameras (SeaViewer and GoPro) through 29 GPS referenced drill holes clustered into six stations along a transect spanning 880 m. Once under the ice cover, a boom containing a second GoPro camera was unfurled and rotated to collect oblique images of the benthic mats within dm of the mat-water interface. This setup allowed imaging from all sides over a ~1.5 m diameter area of the lake bottom. Underwater lens parameters were determined for each camera in Agisoft Lens; images were reconstructed and oriented in space with the SFM software Agisoft Photoscan, using the drop camera axis of rotation as up. The reconstructions were compared to downward facing images to assess accuracy, and similar images of an object with known geometry provided a test for expected error in reconstructions. Downward facing images identify decreasing pinnacle abundance in higher sedimentation settings, and quantitative measurements of 3D reconstructions in KeckCAVES LidarViewer supplement these mat morphological facies with measurements of pinnacle height and orientation. Reconstructions also help isolate confounding variables for mat facies trends with measurements of lake bottom slope and underlying relief that could influence pinnacle growth. Comparison of 3D reconstructions to downward-facing drop camera images demonstrate that SFM is a powerful tool for documenting diverse mat morphologies across environmental gradients in ice-covered lakes.

To 3D or Not to 3D, That Is the Question: Do 3D Surface Analyses Improve the Ecomorphological Power of the Distal Femur in Placental Mammals?

PubMed Central

Gould, Francois D. H.

2014-01-01

Improvements in three-dimensional imaging technologies have renewed interest in the study of functional and ecological morphology. Quantitative approaches to shape analysis are used increasingly to study form-function relationships. These methods are computationally intensive, technically demanding, and time-consuming, which may limit sampling potential. There have been few side-by-side comparisons of the effectiveness of such approaches relative to more traditional analyses using linear measurements and ratios. Morphological variation in the distal femur of mammals has been shown to reflect differences in locomotor modes across clades. Thus I tested whether a geometric morphometric analysis of surface shape was superior to a multivariate analysis of ratios for describing ecomorphological patterns in distal femoral variation. A sample of 164 mammalian specimens from 44 genera was assembled. Each genus was assigned to one of six locomotor categories. The same hypotheses were tested using two methods. Six linear measurements of the distal femur were taken with calipers, from which four ratios were calculated. A 3D model was generated with a laser scanner, and analyzed using three dimensional geometric morphometrics. Locomotor category significantly predicted variation in distal femoral morphology in both analyses. Effect size was larger in the geometric morphometric analysis than in the analysis of ratios. Ordination reveals a similar pattern with arboreal and cursorial taxa as extremes on a continuum of morphologies in both analyses. Discriminant functions calculated from the geometric morphometric analysis were more accurate than those calculated from ratios. Both analysis of ratios and geometric morphometric surface analysis reveal similar, biologically meaningful relationships between distal femoral shape and locomotor mode. The functional signal from the morphology is slightly higher in the geometric morphometric analysis. The practical costs of conducting these sorts of analyses should be weighed against potentially slight increases in power when designing protocols for ecomorphological studies. PMID:24633081

Pathological Gleason prediction through gland ring morphometry in immunofluorescent prostate cancer images

NASA Astrophysics Data System (ADS)

Scott, Richard; Khan, Faisal M.; Zeineh, Jack; Donovan, Michael; Fernandez, Gerardo

2016-03-01

The Gleason score is the most common architectural and morphological assessment of prostate cancer severity and prognosis. There have been numerous quantitative techniques developed to approximate and duplicate the Gleason scoring system. Most of these approaches have been developed in standard H and E brightfield microscopy. Immunofluorescence (IF) image analysis of tissue pathology has recently been proven to be extremely valuable and robust in developing prognostic assessments of disease, particularly in prostate cancer. There have been significant advances in the literature in quantitative biomarker expression as well as characterization of glandular architectures in discrete gland rings. In this work we leverage a new method of segmenting gland rings in IF images for predicting the pathological Gleason; both the clinical and the image specific grade, which may not necessarily be the same. We combine these measures with nuclear specific characteristics as assessed by the MST algorithm. Our individual features correlate well univariately with the Gleason grades, and in a multivariate setting have an accuracy of 85% in predicting the Gleason grade. Additionally, these features correlate strongly with clinical progression outcomes (CI of 0.89), significantly outperforming the clinical Gleason grades (CI of 0.78). This work presents the first assessment of morphological gland unit features from IF images for predicting the Gleason grade.

Myocardial Iron Loading Assessment by Automatic Left Ventricle Segmentation with Morphological Operations and Geodesic Active Contour on T2* images

NASA Astrophysics Data System (ADS)

Luo, Yun-Gang; Ko, Jacky Kl; Shi, Lin; Guan, Yuefeng; Li, Linong; Qin, Jing; Heng, Pheng-Ann; Chu, Winnie Cw; Wang, Defeng

2015-07-01

Myocardial iron loading thalassemia patients could be identified using T2* magnetic resonance images (MRI). To quantitatively assess cardiac iron loading, we proposed an effective algorithm to segment aligned free induction decay sequential myocardium images based on morphological operations and geodesic active contour (GAC). Nine patients with thalassemia major were recruited (10 male and 16 female) to undergo a thoracic MRI scan in the short axis view. Free induction decay images were registered for T2* mapping. The GAC were utilized to segment aligned MR images with a robust initialization. Segmented myocardium regions were divided into sectors for a region-based quantification of cardiac iron loading. Our proposed automatic segmentation approach achieve a true positive rate at 84.6% and false positive rate at 53.8%. The area difference between manual and automatic segmentation was 25.5% after 1000 iterations. Results from T2* analysis indicated that regions with intensity lower than 20 ms were suffered from heavy iron loading in thalassemia major patients. The proposed method benefited from abundant edge information of the free induction decay sequential MRI. Experiment results demonstrated that the proposed method is feasible in myocardium segmentation and was clinically applicable to measure myocardium iron loading.

Comparison of parameter-adapted segmentation methods for fluorescence micrographs.

PubMed

Held, Christian; Palmisano, Ralf; Häberle, Lothar; Hensel, Michael; Wittenberg, Thomas

2011-11-01

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells. Copyright © 2011 International Society for Advancement of Cytometry.

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.

Automated kidney morphology measurements from ultrasound images using texture and edge analysis

NASA Astrophysics Data System (ADS)

Ravishankar, Hariharan; Annangi, Pavan; Washburn, Michael; Lanning, Justin

2016-04-01

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.

Noninvasive three-dimensional live imaging methodology for the spindles at meiosis and mitosis

NASA Astrophysics Data System (ADS)

Zheng, Jing-gao; Huo, Tiancheng; Tian, Ning; Chen, Tianyuan; Wang, Chengming; Zhang, Ning; Zhao, Fengying; Lu, Danyu; Chen, Dieyan; Ma, Wanyun; Sun, Jia-lin; Xue, Ping

2013-05-01

The spindle plays a crucial role in normal chromosome alignment and segregation during meiosis and mitosis. Studying spindles in living cells noninvasively is of great value in assisted reproduction technology (ART). Here, we present a novel spindle imaging methodology, full-field optical coherence tomography (FF-OCT). Without any dye labeling and fixation, we demonstrate the first successful application of FF-OCT to noninvasive three-dimensional (3-D) live imaging of the meiotic spindles within the mouse living oocytes at metaphase II as well as the mitotic spindles in the living zygotes at metaphase and telophase. By post-processing of the 3-D dataset obtained with FF-OCT, the important morphological and spatial parameters of the spindles, such as short and long axes, spatial localization, and the angle of meiotic spindle deviation from the first polar body in the oocyte were precisely measured with the spatial resolution of 0.7 μm. Our results reveal the potential of FF-OCT as an imaging tool capable of noninvasive 3-D live morphological analysis for spindles, which might be useful to ART related procedures and many other spindle related studies.

Image-based query-by-example for big databases of galaxy images

NASA Astrophysics Data System (ADS)

Shamir, Lior; Kuminski, Evan

2017-01-01

Very large astronomical databases containing millions or even billions of galaxy images have been becoming increasingly important tools in astronomy research. However, in many cases the very large size makes it more difficult to analyze these data manually, reinforcing the need for computer algorithms that can automate the data analysis process. An example of such task is the identification of galaxies of a certain morphology of interest. For instance, if a rare galaxy is identified it is reasonable to expect that more galaxies of similar morphology exist in the database, but it is virtually impossible to manually search these databases to identify such galaxies. Here we describe computer vision and pattern recognition methodology that receives a galaxy image as an input, and searches automatically a large dataset of galaxies to return a list of galaxies that are visually similar to the query galaxy. The returned list is not necessarily complete or clean, but it provides a substantial reduction of the original database into a smaller dataset, in which the frequency of objects visually similar to the query galaxy is much higher. Experimental results show that the algorithm can identify rare galaxies such as ring galaxies among datasets of 10,000 astronomical objects.

New insights on ion track morphology in pyrochlores by aberration corrected scanning transmission electron microscopy

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

Sachan, Ritesh; Zhang, Yanwen; Ou, Xin

Here we demonstrate the enhanced imaging capabilities of an aberration corrected scanning transmission electron microscope to advance the understanding of ion track structure in pyrochlore structured materials (i.e., Gd 2Ti 2O 7 and Gd 2TiZrO 7). Track formation occurs due to the inelastic transfer of energy from incident ions to electrons, and atomic-level details of track morphology as a function of energy-loss are revealed in the present work. A comparison of imaging details obtained by varying collection angles of detectors is discussed in the present work. A quantitative analysis of phase identification using high-angle annular dark field imaging is performedmore » on the ion tracks. Finally, a novel 3-dimensional track reconstruction method is provided that is based on depth dependent imaging of the ion tracks. The technique is used in extracting the atomic-level details of nanoscale features, such as the disordered ion tracks, which are embedded in relatively thicker matrix. Another relevance of the method is shown by measuring the tilt of the ion tracks relative to the electron beam incidence that helps in knowing the structure and geometry of ion tracks quantitatively.« less

New insights on ion track morphology in pyrochlores by aberration corrected scanning transmission electron microscopy

DOE PAGES

Sachan, Ritesh; Zhang, Yanwen; Ou, Xin; ...

2016-12-13

Here we demonstrate the enhanced imaging capabilities of an aberration corrected scanning transmission electron microscope to advance the understanding of ion track structure in pyrochlore structured materials (i.e., Gd 2Ti 2O 7 and Gd 2TiZrO 7). Track formation occurs due to the inelastic transfer of energy from incident ions to electrons, and atomic-level details of track morphology as a function of energy-loss are revealed in the present work. A comparison of imaging details obtained by varying collection angles of detectors is discussed in the present work. A quantitative analysis of phase identification using high-angle annular dark field imaging is performedmore » on the ion tracks. Finally, a novel 3-dimensional track reconstruction method is provided that is based on depth dependent imaging of the ion tracks. The technique is used in extracting the atomic-level details of nanoscale features, such as the disordered ion tracks, which are embedded in relatively thicker matrix. Another relevance of the method is shown by measuring the tilt of the ion tracks relative to the electron beam incidence that helps in knowing the structure and geometry of ion tracks quantitatively.« less

Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images.

PubMed

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-03-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Comparison of Filters Dedicated to Speckle Suppression in SAR Images

NASA Astrophysics Data System (ADS)

Kupidura, P.

2016-06-01

This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images - a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling "salt and pepper" noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction). The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection

PubMed Central

Wilkins, Ruth; Flegal, Farrah; Knoll, Joan H.M.; Rogan, Peter K.

2017-01-01

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs arising primarily from sister chromatid separation, chromosome fragmentation, and cellular debris. This reduced FPs by an average of 55% and was highly specific to these abnormal structures (≥97.7%) in three samples. Additional filters selectively removed images with incomplete, highly overlapped, or missing metaphase cells, or with poor overall chromosome morphologies that increased FP rates. Image selection is optimized and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same image segmentation filtering procedures to both calibration and test samples reduced the average dose estimation error from 0.4 Gy to <0.2 Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing for multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations. PMID:29026522

Automated Method for the Rapid and Precise Estimation of Adherent Cell Culture Characteristics from Phase Contrast Microscopy Images

PubMed Central

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-01-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. Biotechnol. Bioeng. 2014;111: 504–517. © 2013 Wiley Periodicals, Inc. PMID:24037521

Defining new dental phenotypes using 3-D image analysis to enhance discrimination and insights into biological processes

PubMed Central

Smith, Richard; Zaitoun, Halla; Coxon, Tom; Karmo, Mayada; Kaur, Gurpreet; Townsend, Grant; Harris, Edward F.; Brook, Alan

2009-01-01

Aims In studying aetiological interactions of genetic, epigenetic and environmental factors in normal and abnormal developments of the dentition, methods of measurement have often been limited to maximum mesio-distal and bucco-lingual crown diameters, obtained with hand-held calipers. While this approach has led to many important findings, there are potentially many other informative measurements that can be made to describe dental crown morphology. Advances in digital imaging and computer technology now offer the opportunity to define and measure new dental phenotypes in 3-D that have the potential to provide better anatomical discrimination and clearer insights into the underlying biological processes in dental development. Over recent years, image analysis in 2-D has proved to be a valuable addition to hand-measurement methods but a reliable and rapid 3-D method would increase greatly the morphological information obtainable from natural teeth and dental models. Additional measurements such as crown heights, surface contours, actual surface perimeters and areas, and tooth volumes would maximise our ability to discriminate between samples and to explore more deeply genetic and environmental contributions to observed variation. The research objectives were to investigate the limitations of existing methodologies and to develop and validate new methods for obtaining true 3-D measurements, including curvatures and volumes, in order to enhance discrimination to allow increased differentiation in studies of dental morphology and development. The validity of a new methodology for the 3-D measurement of teeth is compared against an established 2-D system. The intra- and inter-observer reliability of some additional measurements, made possible with a 3-D approach, are also tested. Methods and results From each of 20 study models, the permanent upper right lateral and upper left central incisors were separated and imaged independently by two operators using 2-D image analysis and a 3-D image analysis system. The mesio-distal (MD), labio-lingual (LL) and inciso-gingival (IG) dimensions were recorded using our 2-D system and the same projected variables were also recorded using a newly developed 3-D system for comparison. Values of Pearson's correlation coefficient between measurements obtained using the two techniques were significant at the 0.01 probability level for variables mesio-distal and incisal-gingival with labio-lingual significant at the 0.05 level for the upper left side only, confirming their comparability. For both 2-D and 3-D systems the intra- and inter-operator reliability was substantial or excellent for variables mesio-distal, labio-lingual, incisal-gingival actual and projected and actual surface area. The reliability was good for inter-operator reliability measurement of the labio-lingual dimension using 3-D. Conclusions We have developed a new 3-D laser scanning system that enables additional dental phenotypes to be defined. It has been validated against an established 2-D system and shown to provide measurements with excellent reliability, both within and between operators. This new approach provides exciting possibilities for exploring normal and abnormal variations in dental morphology and development applicable to research on genetic and environmental factors. PMID:18644585

A comparative study of corneal incisions induced by diamond and steel knives and two ultraviolet radiations from an excimer laser.

PubMed Central

Marshall, J; Trokel, S; Rothery, S; Krueger, R R

1986-01-01

This paper reviews the potential role of excimer lasers in corneal surgery. The morphology of incisions induced by two wavelengths of excimer laser radiation, 193 nm and 248 nm, are compared with the morphology of incisions produced by diamond and steel knives. Analysis suggests that ablation induced by excimer laser results from highly localised photochemical reactions and that 193 nm is the optimal wavelength for surgery. The only significant complication of laser surgery is loss of endothelial cells when incisions are within 40 micron of Descemet's membrane. Images PMID:3013283

Measuring the Symmetry of Supernova Remnants in the Radio

NASA Astrophysics Data System (ADS)

Stafford, Jennifer; Lopez, Laura A.

2017-01-01

Nearly 300 supernova remnants (SNRs) are known in the MIlky Way galaxy, and they offer an important means to study the explosions and interactions of supernovae at sub-pc scales. In this poster, we present analysis of the morphology of Galactic SNRs at radio wavelengths. Specifically, we measure the symmetry of several tens of SNRs in 6- and 20-cm Very Large Array images using a multipole expansion technique, the power-ratio method. We explore how the SNRs' morphology changes as a function of their size and estimated dynamical ages, with the aim of probing how SNR shapes evolve with time.

Computerized image analysis for acetic acid induced intraepithelial lesions

NASA Astrophysics Data System (ADS)

Li, Wenjing; Ferris, Daron G.; Lieberman, Rich W.

2008-03-01

Cervical Intraepithelial Neoplasia (CIN) exhibits certain morphologic features that can be identified during a visual inspection exam. Immature and dysphasic cervical squamous epithelium turns white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively discriminates between dysphasic and normal tissue. Digital imaging technologies allow us to assist the physician analyzing the acetic acid induced lesions (acetowhite region) in a fully automatic way. This paper reports a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post acetic acid image; the temporal change is extracted from the intensity and color changes between the post acetic acid and pre acetic acid images with an automatic alignment. The imaging and data analysis system has been evaluated with a total of 99 human subjects and demonstrate its potential to screening underserved women where access to skilled colposcopists is limited.

Morphological classification and microanalysis of tire tread particles worn by abrasion or corrosion

NASA Astrophysics Data System (ADS)

Crosta, Giovanni F.

2011-06-01

Two types of tread wear particles are investigated: tread wear particles from a steel brush abrader (TrBP) and particles produced during a steering pad run (TrSP). A leaching experiment in water at pH = 7.5 for 24 and 48h was carried out on TrBP to simulate environmental degradation. Images of all materials were collected by a scanning electron microscope (SEM) together with element microanalytical (EDX) data. Surface morphology is described by a function of wave number (the "enhanced spectrum") obtained from SEM image analysis and non-linear filtering. A surface roughness index, ρ, is derived from the enhanced spectrum. The innovative contribution of this work is the representation of morphology by means of ρ, which, together with EDX data, allows the quantitative characterization of the materials. In particular, the surface roughness of leached TrBP is shown to decay in time and is related to the corresponding microanalytical data for the first time. The morphology of steering pad TrSP, affected by included mineral particles, is shown to be more heterogeneous. Differences in morphology (enhanced spectra and ρ), elemental composition and surface chemistry of TrBP and TrSP are discussed. All methods described and implemented herewith can be immediately applied to other types of tread wear material. The arguments put forward herewith should help in the proper design of those experiments aimed at assessing the impact of tread wear materials on the environment and on human health.

Astronomical image data compression by morphological skeleton transformation

NASA Astrophysics Data System (ADS)

Huang, L.; Bijaoui, A.

A compression method adapted for exact restoring of the detected objects and based on the morphological skeleton transformation is presented. The morphological skeleton provides a complete and compact description of an object and gives an efficient compression rate. The flexibility of choosing a structuring element adapted to different images and the simplicity of the implementation are considered to be advantages of the method. The experiment was carried out on three typical astronomical images. The first two images were obtained by digitizing a Palomar Schmidt photographic plate in a coma field with the PDS microdensitometer at Nice Observatory. The third image was obtained by CCD camera at the Pic du Midi Observatory. Each pixel was coded by 16 bits and stored at a computer system (VAX785) with STII format. Each image is characterized by 256 x 256 pixels. It is found that first image represents a stellar field, the second represents a set of galaxies in the Coma, and the third image contains an elliptical galaxy.

Facile one step synthesis of novel TiO2 nanocoral by sol-gel method using Aloe vera plant extract

NASA Astrophysics Data System (ADS)

Venkatesh, K. S.; Krishnamoorthi, S. R.; Palani, N. S.; Thirumal, V.; Jose, Sujin P.; Wang, Fu-Ming; Ilangovan, R.

2015-05-01

Titanium oxide (TiO2) nanoparticles (NPs) were synthesized by sol gel method using Aloe vera plant extract as a biological capping agent and a cauliflower-nanocoral morphology was observed in this technique. The assynthesized TiO2 nanopowder was calcined at a range of temperatures (300-600 °C) for 1 h. The influence of A. vera plant extract on the thermal, structural and morphological properties of TiO2 nanopowder was evaluated. Thermogravimetric analysis/differential thermal analysis was employed to study the thermal properties of the assynthesized TiO2 nanopowder. The crystallinity, phase transformation and the crystallite size of the calcined samples were studied by X-ray diffraction technique. XRD result confirmed the presence of TiO2 with anatase phase. FT Raman spectra showed the Raman active modes pertaining to the TiO2 anatase phase and Raman band shift was also observed with respect to particle size variation. The different functional group vibrations of as dried pure A. vera plant extract were compared with the mixture of TiO2 and A. vera plant extract by FT-IR analysis. The scanning electron microscopy images apparently showed the formation of spherical shaped NPs and also it demonstrated the effect of A. vera plant extract on the reduction of particles size. The surface area of the TiO2 NPs was measured through Brunauer-Emmett-Teller analysis. Transmission electron microscopy images ascertained that the spherical shaped TiO2 NPs were formed with cauliflower-nanocoral morphology decorated with nanopolyps with the size range between 15 and 30 nm.

Characterization of rock populations on planetary surfaces - Techniques and a preliminary analysis of Mars and Venus

NASA Technical Reports Server (NTRS)

Garvin, J. B.; Mouginis-Mark, P. J.; Head, J. W.

1981-01-01

A data collection and analysis scheme developed for the interpretation of rock morphology from lander images is reviewed with emphasis on rock population characterization techniques. Data analysis techniques are also discussed in the context of identifying key characteristics of a rock that place it in a single category with similar rocks. Actual rock characteristics observed from Viking and Venera lander imagery are summarized. Finally, some speculations regarding the block fields on Mars and Venus are presented.

Quantitative analysis of thyroid tumors vascularity: A comparison between 3-D contrast-enhanced ultrasound and 3-D Power Doppler on benign and malignant thyroid nodules.

PubMed

Caresio, Cristina; Caballo, Marco; Deandrea, Maurilio; Garberoglio, Roberto; Mormile, Alberto; Rossetto, Ruth; Limone, Paolo; Molinari, Filippo

2018-05-15

To perform a comparative quantitative analysis of Power Doppler ultrasound (PDUS) and Contrast-Enhancement ultrasound (CEUS) for the quantification of thyroid nodules vascularity patterns, with the goal of identifying biomarkers correlated with the malignancy of the nodule with both imaging techniques. We propose a novel method to reconstruct the vascular architecture from 3-D PDUS and CEUS images of thyroid nodules, and to automatically extract seven quantitative features related to the morphology and distribution of vascular network. Features include three tortuosity metrics, the number of vascular trees and branches, the vascular volume density, and the main spatial vascularity pattern. Feature extraction was performed on 20 thyroid lesions (ten benign and ten malignant), of which we acquired both PDUS and CEUS. MANOVA (multivariate analysis of variance) was used to differentiate benign and malignant lesions based on the most significant features. The analysis of the extracted features showed a significant difference between the benign and malignant nodules for both PDUS and CEUS techniques for all the features. Furthermore, by using a linear classifier on the significant features identified by the MANOVA, benign nodules could be entirely separated from the malignant ones. Our early results confirm the correlation between the morphology and distribution of blood vessels and the malignancy of the lesion, and also show (at least for the dataset used in this study) a considerable similarity in terms of findings of PDUS and CEUS imaging for thyroid nodules diagnosis and classification. © 2018 American Association of Physicists in Medicine.

Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

NASA Astrophysics Data System (ADS)

Bucht, Curry; Söderberg, Per; Manneberg, Göran

2009-02-01

The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor. Morphometry of the corneal endothelium is presently done by semi-automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development of fully automated analysis of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images. The digitally enhanced images of the corneal endothelium were transformed, using the fast Fourier transform (FFT). Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.

Breast cancer evaluation by fluorescent dot detection using combined mathematical morphology and multifractal techniques

PubMed Central

2011-01-01

Background Fluorescence in situ hybridization (FISH) is very accurate method for measuring HER2 gene copies, as a sign of potential breast cancer. This method requires small tissue samples, and has a high sensitivity to detect abnormalities from a histological section. By using multiple colors, this method allows the detection of multiple targets simultaneously. The target parts in the cells become visible as colored dots. The HER-2 probes are visible as orange stained spots under a fluorescent microscope while probes for centromere 17 (CEP-17), the chromosome on which the gene HER-2/neu is located, are visible as green spots. Methods The conventional analysis involves the scoring of the ratio of HER-2/neu over CEP 17 dots within each cell nucleus and then averaging the scores for a number of 60 cells. A ratio of 2.0 of HER-2/neu to CEP 17 copy number denotes amplification. Several methods have been proposed for the detection and automated evaluation (dot counting) of FISH signals. In this paper the combined method based on the mathematical morphology (MM) and inverse multifractal (IMF) analysis is suggested. Similar method was applied recently in detection of microcalcifications in digital mammograms, and was very successful. Results The combined MM using top-hat and bottom-hat filters, and the IMF method was applied to FISH images from Molecular Biology Lab, Department of Pathology, Wielkoposka Cancer Center, Poznan. Initial results indicate that this method can be applied to FISH images for the evaluation of HER2/neu status. Conclusions Mathematical morphology and multifractal approach are used for colored dot detection and counting in FISH images. Initial results derived on clinical cases are promising. Note that the overlapping of colored dots, particularly red/orange dots, needs additional improvements in post-processing. PMID:21489192

Ganalyzer: A Tool for Automatic Galaxy Image Analysis

NASA Astrophysics Data System (ADS)

Shamir, Lior

2011-08-01

We describe Ganalyzer, a model-based tool that can automatically analyze and classify galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large data sets of galaxy images collected by autonomous sky surveys such as SDSS, LSST, or DES. The software is available for free download at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer, and the data used in the experiment are available at http://vfacstaff.ltu.edu/lshamir/downloads/ganalyzer/GalaxyImages.zip.

A survey of MRI-based medical image analysis for brain tumor studies

NASA Astrophysics Data System (ADS)

Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

Morphology and Topography of Retinal Pericytes in the Living Mouse Retina Using In Vivo Adaptive Optics Imaging and Ex Vivo Characterization

PubMed Central

Schallek, Jesse; Geng, Ying; Nguyen, HoanVu; Williams, David R.

2013-01-01

Purpose. To noninvasively image retinal pericytes in the living eye and characterize NG2-positive cell topography and morphology in the adult mouse retina. Methods. Transgenic mice expressing fluorescent pericytes (NG2, DsRed) were imaged using a two-channel, adaptive optics scanning laser ophthalmoscope (AOSLO). One channel imaged vascular perfusion with near infrared light. A second channel simultaneously imaged fluorescent retinal pericytes. Mice were also imaged using wide-field ophthalmoscopy. To confirm in vivo imaging, five eyes were enucleated and imaged in flat mount with conventional fluorescent microscopy. Cell topography was quantified relative to the optic disc. Results. We observed strong DsRed fluorescence from NG2-positive cells. AOSLO revealed fluorescent vascular mural cells enveloping all vessels in the living retina. Cells were stellate on larger venules, and showed banded morphology on arterioles. NG2-positive cells indicative of pericytes were found on the smallest capillaries of the retinal circulation. Wide-field SLO enabled quick assessment of NG2-positive distribution, but provided insufficient resolution for cell counts. Ex vivo microscopy showed relatively even topography of NG2-positive capillary pericytes at eccentricities more than 0.3 mm from the optic disc (515 ± 94 cells/mm2 of retinal area). Conclusions. We provide the first high-resolution images of retinal pericytes in the living animal. Subcellular resolution enabled morphological identification of NG2-positive cells on capillaries showing classic features and topography of retinal pericytes. This report provides foundational basis for future studies that will track and quantify pericyte topography, morphology, and function in the living retina over time, especially in the progression of microvascular disease. PMID:24150762

Morphology of Dbx1 respiratory neurons in the preBötzinger complex and reticular formation of neonatal mice.

PubMed

Akins, Victoria T; Weragalaarachchi, Krishanthi; Picardo, Maria Cristina D; Revill, Ann L; Del Negro, Christopher A

2017-08-01

The relationship between neuron morphology and function is a perennial issue in neuroscience. Information about synaptic integration, network connectivity, and the specific roles of neuronal subpopulations can be obtained through morphological analysis of key neurons within a microcircuit. Here we present morphologies of two classes of brainstem respiratory neurons. First, interneurons derived from Dbx1-expressing precursors (Dbx1 neurons) in the preBötzinger complex (preBötC) of the ventral medulla that generate the rhythm for inspiratory breathing movements. Second, Dbx1 neurons of the intermediate reticular formation that influence the motor pattern of pharyngeal and lingual movements during the inspiratory phase of the breathing cycle. We describe the image acquisition and subsequent digitization of morphologies of respiratory Dbx1 neurons from the preBötC and the intermediate reticular formation that were first recorded in vitro. These data can be analyzed comparatively to examine how morphology influences the roles of Dbx1 preBötC and Dbx1 reticular interneurons in respiration and can also be utilized to create morphologically accurate compartmental models for simulation and modeling of respiratory circuits.

Advanced imaging as a novel approach to the characterization of membranes for microfiltration applications

NASA Astrophysics Data System (ADS)

Marroquin, Milagro

The primary objectives of my dissertation were to design, develop and implement novel confocal microscopy imaging protocols for the characterization of membranes and highlight opportunities to obtain reliable and cutting-edge information of microfiltration membrane morphology and fouling processes. After a comprehensive introduction and review of confocal microscopy in membrane applications (Chapter 1), the first part of this dissertation (Chapter 2) details my work on membrane morphology characterization by confocal laser scanning microscopy (CLSM) and the implementation of my newly developed CLSM cross-sectional imaging protocol. Depth-of-penetration limits were identified to be approximately 24 microns and 7-8 microns for mixed cellulose ester and polyethersulfone membranes, respectively, making it impossible to image about 70% of the membrane bulk. The development and implementation of my cross-sectional CLSM method enabled the imaging of the entire membrane cross-section. Porosities of symmetric and asymmetric membranes with nominal pore sizes in the range 0.65-8.0 microns were quantified at different depths and yielded porosity values in the 50-60% range. It is my hope and expectation that the characterization strategy developed in this part of the work will enable future studies of different membrane materials and applications by confocal microscopy. After demonstrating how cross-sectional CLSM could be used to fully characterize membrane morphologies and porosities, I applied it to the characterization of fouling occurring in polyethersulfone microfiltration membranes during the processing of solutions containing proteins and polysaccharides (Chapter 3). Through CLSM imaging, it was determined where proteins and polysaccharides deposit throughout polymeric microfiltration membranes when a fluid containing these materials is filtered. CLSM enabled evaluation of the location and extent of fouling by individual components (protein: casein and polysaccharide: dextran) within wet, asymmetric polyethersulfone microfiltration membranes. Information from filtration flux profiles and cross-sectional CLSM images of the membranes that processed single-component solutions and mixtures agreed with each other. Concentration profiles versus depth for each individual component present in the feed solution were developed from the analysis of the CLSM images at different levels of fouling for single-component solutions and mixtures. CLSM provided visual information that helped elucidate the role of each component on membrane fouling and provided a better understanding of how component interactions impact the fouling profiles. Finally, Chapter 4 extends the application of my cross-sectional CLSM imaging protocol to study the fouling of asymmetric polyethersulfone membranes during the microfiltration of protein, polyphenol, and polysaccharide mixtures to better understand the solute-solute and solute-membrane interactions leading to fouling in beverage clarification processes. Again, cross-sectional CLSM imaging provided information on the location and extent of fouling throughout the entire thickness of the PES membrane. Quantitative analysis of the cross-sectional CLSM images provided a measurement of the masses of foulants deposited throughout the membrane. Moreover, flux decline data collected for different mixtures of casein, tannic acid and beta-cyclodextrin were analyzed with standard fouling models to determine the fouling mechanisms at play when processing different combinations of foulants. Results from model analysis of flux data were compared with the quantitative visual analysis of the correspondent CLSM images. This approach, which couples visual and performance measurements, is expected to provide a better understanding of the causes of fouling that, in turn, is expected to aid in the design of new membranes with tailored structure or surface chemistry that prevents the deposition of the foulants in "prone to foul" regions. (Abstract shortened by UMI.)

Variable Threshold Method for Determining the Boundaries of Imaged Subvisible Particles.

PubMed

Cavicchi, Richard E; Collett, Cayla; Telikepalli, Srivalli; Hu, Zhishang; Carrier, Michael; Ripple, Dean C

2017-06-01

An accurate assessment of particle characteristics and concentrations in pharmaceutical products by flow imaging requires accurate particle sizing and morphological analysis. Analysis of images begins with the definition of particle boundaries. Commonly a single threshold defines the level for a pixel in the image to be included in the detection of particles, but depending on the threshold level, this results in either missing translucent particles or oversizing of less transparent particles due to the halos and gradients in intensity near the particle boundaries. We have developed an imaging analysis algorithm that sets the threshold for a particle based on the maximum gray value of the particle. We show that this results in tighter boundaries for particles with high contrast, while conserving the number of highly translucent particles detected. The method is implemented as a plugin for FIJI, an open-source image analysis software. The method is tested for calibration beads in water and glycerol/water solutions, a suspension of microfabricated rods, and stir-stressed aggregates made from IgG. The result is that appropriate thresholds are automatically set for solutions with a range of particle properties, and that improved boundaries will allow for more accurate sizing results and potentially improved particle classification studies. Published by Elsevier Inc.

Influence of Processing Conditions on the Mechanical Behavior and Morphology of Injection Molded Poly(lactic-co-glycolic acid) 85:15

PubMed Central

Fancello, Eduardo Alberto

2017-01-01

Two groups of PLGA specimens with different geometries (notched and unnotched) were injection molded under two melting temperatures and flow rates. The mechanical properties, morphology at the fracture surface, and residual stresses were evaluated for both processing conditions. The morphology of the fractured surfaces for both specimens showed brittle and smooth fracture features for the majority of the specimens. Fracture images of the notched specimens suggest that the surface failure mechanisms are different from the core failure. Polarized light techniques indicated birefringence in all specimens, especially those molded with lower temperature, which suggests residual stress due to rapid solidification. DSC analysis confirmed the existence of residual stress in all PLGA specimens. The specimens molded using the lower injection temperature and the low flow rate presented lower loss tangent values according to the DMA and higher residual stress as shown by DSC, and the photoelastic analysis showed extensive birefringence. PMID:28848605

Effect of Eu3+ doping on the structural, morphological and luminescence properties ZnO nanostructures

NASA Astrophysics Data System (ADS)

Vinoditha, U.; Balakrishna, K. M.; Sarojini, B. K.; Narayana, B.; Kumara, K.

2018-05-01

Pure and Eu3+ ions (1, 3, 5 atomic wt%) doped ZnO nanostructures are synthesized by a surfactant assisted hydrothermal method. The effect of doping concentrations on structural, morphological and optical properties of ZnO nanostructures is studied. The XRD analysis shows good crystallinity and the phase purity of the ZnO nanostructures. A shift in the standard Zn-O stretching mode after Eu3+ doping is observed in the FTIR spectra. The images of FESEM demonstrate the morphological variations from hexagonal nanorods to nanoflowers on varying the dopant concentrations. Substitution of Eu3+ ions into Zn2+ sites is confirmed by EDX analysis. The dominance of particle shape over the UV-Visible absorption properties of the prepared samples is noticed. The photoluminescence (PL) emission of undoped and doped ZnO nanostructures show dominant near band edge emission (NBE) in the UV region and minor defect induced deep level emissions in the visible region.

Neuroanatomical correlates of negative emotionality-related traits: A systematic review and meta-analysis.

PubMed

Mincic, Adina M

2015-10-01

Two central traits present in the most influential models of personality characterize the response to positive and, respectively, negative emotional events. Negative emotionality (NE)-related traits are linked to vulnerability to mood and anxiety disorders; this has fuelled a special interest in examining stable differences in brain morphology associated to these traits. Structural imaging methods including voxel-based morphometry, cortical thickness analysis and diffusion tensor imaging (DTI) have yielded inconclusive and sometimes contradictory results. This review summarizes the findings reported to date through these methods and discusses them in relation to the functional imaging results. To detect topographic convergence between studies showing positive and, respectively, negative grey matter associations with NE-traits, activation likelihood estimation (ALE) meta-analyses of VBM studies were performed. Individuals scoring high on NE-related traits show consistent morphological differences in a left-lateralized circuit: higher grey matter volume (GMV) in amygdala and anterior parahippocampal gyrus and lower GMV in the orbitofrontal cortex extending into perigenual anterior cingulate cortex. Most DTI studies indicate reduced white matter integrity in various brain regions and tracts, particularly in the uncinate fasciculus and in cingulum bundle. These results show that the behavioural phenotype associated to NE traits is reflected in structural differences within the cortico-limbic system, suggesting alterations in information processing and transmission. The results are discussed from the perspective of neuron-glia interactions. Future directions are outlined based on recent developments in structural imaging techniques. Copyright © 2015 Elsevier Ltd. All rights reserved.

From microscopy to whole slide digital images: a century and a half of image analysis.

PubMed

Taylor, Clive R

2011-12-01

In the year 1850, microscopes had evolved in quality to the point that the "first pathologists emerged from the treacherous swamps of medieval practice onto the relatively firm ground that histopathology seemed to offer." These early pathologists began to practice the art of image analysis, and diagnostic surgical pathology was born. Today the traditional microscope, in the hands of an experienced pathologist, is established as the gold standard for diagnosis of cancer and other diseases. Nonetheless, it is a tool and a technology that is more than 150 years old. Rapid advances in the capabilities of digital imaging hardware and software now offer the real possibility of moving to a new level of practice, using whole slide digital images for diagnosis, education, and research in morphologic pathology. Potential efficiencies in work flow and diagnostic integration, coupled with the use of powerful new analytic methods, promise radically to change the future shape of surgical pathology.

High-resolution measurements of the multilayer ultra-structure of articular cartilage and their translational potential

PubMed Central

2014-01-01

Current musculoskeletal imaging techniques usually target the macro-morphology of articular cartilage or use histological analysis. These techniques are able to reveal advanced osteoarthritic changes in articular cartilage but fail to give detailed information to distinguish early osteoarthritis from healthy cartilage, and this necessitates high-resolution imaging techniques measuring cells and the extracellular matrix within the multilayer structure of articular cartilage. This review provides a comprehensive exploration of the cellular components and extracellular matrix of articular cartilage as well as high-resolution imaging techniques, including magnetic resonance image, electron microscopy, confocal laser scanning microscopy, second harmonic generation microscopy, and laser scanning confocal arthroscopy, in the measurement of multilayer ultra-structures of articular cartilage. This review also provides an overview for micro-structural analysis of the main components of normal or osteoarthritic cartilage and discusses the potential and challenges associated with developing non-invasive high-resolution imaging techniques for both research and clinical diagnosis of early to late osteoarthritis. PMID:24946278

Failure Analysis of Batteries Using Synchrotron-based Hard X-ray Microtomography

PubMed Central

Harry, Katherine J.; Parkinson, Dilworth Y.; Balsara, Nitash P.

2015-01-01

Imaging morphological changes that occur during the lifetime of rechargeable batteries is necessary to understand how these devices fail. Since the advent of lithium-ion batteries, researchers have known that the lithium metal anode has the highest theoretical energy density of any anode material. However, rechargeable batteries containing a lithium metal anode are not widely used in consumer products because the growth of lithium dendrites from the anode upon charging of the battery causes premature cell failure by short circuit. Lithium dendrites can also form in commercial lithium-ion batteries with graphite anodes if they are improperly charged. We demonstrate that lithium dendrite growth can be studied using synchrotron-based hard X-ray microtomography. This non-destructive imaging technique allows researchers to study the growth of lithium dendrites, in addition to other morphological changes inside batteries, and subsequently develop methods to extend battery life. PMID:26382323

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.

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.

Constraint factor graph cut-based active contour method for automated cellular image segmentation in RNAi screening.

PubMed

Chen, C; Li, H; Zhou, X; Wong, S T C

2008-05-01

Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Simultaneous imaging of cellular morphology and multiple biomarkers using an acousto-optic tunable filter-based bright field microscope.

PubMed

Wachman, Elliot S; Geyer, Stanley J; Recht, Joel M; Ward, Jon; Zhang, Bill; Reed, Murray; Pannell, Chris

2014-05-01

An acousto-optic tunable filter (AOTF)-based multispectral imaging microscope system allows the combination of cellular morphology and multiple biomarker stainings on a single microscope slide. We describe advances in AOTF technology that have greatly improved spectral purity, field uniformity, and image quality. A multispectral imaging bright field microscope using these advances demonstrates pathology results that have great potential for clinical use.

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.

Association between trochlear morphology and chondromalacia patella: an MRI study.

PubMed

Duran, Semra; Cavusoglu, Mehtap; Kocadal, Onur; Sakman, Bulent

This study aimed to compare trochlear morphology seen in magnetic resonance imaging between patients with chondromalacia patella and age-matched control patients without cartilage lesion. Trochlear morphology was evaluated using the lateral trochlear inclination, medial trochlear inclination, sulcus angle and trochlear angle on the axial magnetic resonance images. Consequently, an association between abnormal trochlear morphology and chondromalacia patella was identified in women. In particular, women with flattened lateral trochlea are at an increased risk of patellar cartilage structural damage. Copyright © 2016 Elsevier Inc. All rights reserved.

Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology

DTIC Science & Technology

2005-04-01

Harvey N., Szymanski J.J., Bloch J.J., Mitchell M. investigation of image feature extraction by a genetic algorithm. Proc. SPIE 1999;3812:24-31. 11...automated feature extraction using multiple data sources. Proc. SPIE 2003;5099:190-200. 15 4 Spectral-Spatial Analysis of Urine Cytology Angeletti et al...Appendix Contents: 1. Harvey, N.R., Levenson, R.M., Rimm, D.L. (2003) Investigation of Automated Feature Extraction Techniques for Applications in

Three-dimensional Imaging Methods for Quantitative Analysis of Facial Soft Tissues and Skeletal Morphology in Patients with Orofacial Clefts: A Systematic Review

PubMed Central

Kuijpers, Mette A. R.; Chiu, Yu-Ting; Nada, Rania M.; Carels, Carine E. L.; Fudalej, Piotr S.

2014-01-01

Background Current guidelines for evaluating cleft palate treatments are mostly based on two-dimensional (2D) evaluation, but three-dimensional (3D) imaging methods to assess treatment outcome are steadily rising. Objective To identify 3D imaging methods for quantitative assessment of soft tissue and skeletal morphology in patients with cleft lip and palate. Data sources Literature was searched using PubMed (1948–2012), EMBASE (1980–2012), Scopus (2004–2012), Web of Science (1945–2012), and the Cochrane Library. The last search was performed September 30, 2012. Reference lists were hand searched for potentially eligible studies. There was no language restriction. Study selection We included publications using 3D imaging techniques to assess facial soft tissue or skeletal morphology in patients older than 5 years with a cleft lip with/or without cleft palate. We reviewed studies involving the facial region when at least 10 subjects in the sample size had at least one cleft type. Only primary publications were included. Data extraction Independent extraction of data and quality assessments were performed by two observers. Results Five hundred full text publications were retrieved, 144 met the inclusion criteria, with 63 high quality studies. There were differences in study designs, topics studied, patient characteristics, and success measurements; therefore, only a systematic review could be conducted. Main 3D-techniques that are used in cleft lip and palate patients are CT, CBCT, MRI, stereophotogrammetry, and laser surface scanning. These techniques are mainly used for soft tissue analysis, evaluation of bone grafting, and changes in the craniofacial skeleton. Digital dental casts are used to evaluate treatment and changes over time. Conclusion Available evidence implies that 3D imaging methods can be used for documentation of CLP patients. No data are available yet showing that 3D methods are more informative than conventional 2D methods. Further research is warranted to elucidate it. Systematic review registration International Prospective Register of Systematic Reviews, PROSPERO CRD42012002041 PMID:24710215

Image processing for safety assessment in civil engineering.

PubMed

Ferrer, Belen; Pomares, Juan C; Irles, Ramon; Espinosa, Julian; Mas, David

2013-06-20

Behavior analysis of construction safety systems is of fundamental importance to avoid accidental injuries. Traditionally, measurements of dynamic actions in civil engineering have been done through accelerometers, but high-speed cameras and image processing techniques can play an important role in this area. Here, we propose using morphological image filtering and Hough transform on high-speed video sequence as tools for dynamic measurements on that field. The presented method is applied to obtain the trajectory and acceleration of a cylindrical ballast falling from a building and trapped by a thread net. Results show that safety recommendations given in construction codes can be potentially dangerous for workers.