Generation of an Atlas of the Proximal Femur and Its Application to Trabecular Bone Analysis
Carballido-Gamio, Julio; Folkesson, Jenny; Karampinos, Dimitrios C.; Baum, Thomas; Link, Thomas M.; Majumdar, Sharmila; Krug, Roland
2013-01-01
Automatic placement of anatomically corresponding volumes of interest and comparison of parameters against a standard of reference are essential components in studies of trabecular bone. Only recently, in vivo MR images of the proximal femur, an important fracture site, could be acquired with high-spatial resolution. The purpose of this MRI trabecular bone study was two-fold: (1) to generate an atlas of the proximal femur to automatically place anatomically corresponding volumes of interest in a population study and (2) to demonstrate how mean models of geodesic topological analysis parameters can be generated to be used as potential standard of reference. Ten females were used to generate the atlas and geodesic topological analysis models, and 10 females were used to demonstrate the atlas-based trabecular bone analysis. All alignments were based on three-dimensional (3D) multiresolution affine transformations followed by 3D multiresolution free-form deformations. Mean distances less than 1 mm between aligned femora, and sharp edges in the atlas and in fused gray-level images of registered femora indicated that the anatomical variability was well accommodated and explained by the free-form deformations. PMID:21432904
Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long
2016-01-01
We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229
Musculoskeletal Simulation Model Generation from MRI Data Sets and Motion Capture Data
NASA Astrophysics Data System (ADS)
Schmid, Jérôme; Sandholm, Anders; Chung, François; Thalmann, Daniel; Delingette, Hervé; Magnenat-Thalmann, Nadia
Today computer models and computer simulations of the musculoskeletal system are widely used to study the mechanisms behind human gait and its disorders. The common way of creating musculoskeletal models is to use a generic musculoskeletal model based on data derived from anatomical and biomechanical studies of cadaverous specimens. To adapt this generic model to a specific subject, the usual approach is to scale it. This scaling has been reported to introduce several errors because it does not always account for subject-specific anatomical differences. As a result, a novel semi-automatic workflow is proposed that creates subject-specific musculoskeletal models from magnetic resonance imaging (MRI) data sets and motion capture data. Based on subject-specific medical data and a model-based automatic segmentation approach, an accurate modeling of the anatomy can be produced while avoiding the scaling operation. This anatomical model coupled with motion capture data, joint kinematics information, and muscle-tendon actuators is finally used to create a subject-specific musculoskeletal model.
Scholtz, Jan-Erik; Wichmann, Julian L; Kaup, Moritz; Fischer, Sebastian; Kerl, J Matthias; Lehnert, Thomas; Vogl, Thomas J; Bauer, Ralf W
2015-03-01
To evaluate software for automatic segmentation, labeling and reformation of anatomical aligned axial images of the thoracolumbar spine on CT in terms of accuracy, potential for time savings and workflow improvement. 77 patients (28 women, 49 men, mean age 65.3±14.4 years) with known or suspected spinal disorders (degenerative spine disease n=32; disc herniation n=36; traumatic vertebral fractures n=9) underwent 64-slice MDCT with thin-slab reconstruction. Time for automatic labeling of the thoracolumbar spine and reconstruction of double-angulated axial images of the pathological vertebrae was compared with manually performed reconstruction of anatomical aligned axial images. Reformatted images of both reconstruction methods were assessed by two observers regarding accuracy of symmetric depiction of anatomical structures. In 33 cases double-angulated axial images were created in 1 vertebra, in 28 cases in 2 vertebrae and in 16 cases in 3 vertebrae. Correct automatic labeling was achieved in 72 of 77 patients (93.5%). Errors could be manually corrected in 4 cases. Automatic labeling required 1min in average. In cases where anatomical aligned axial images of 1 vertebra were created, reconstructions made by hand were significantly faster (p<0.05). Automatic reconstruction was time-saving in cases of 2 and more vertebrae (p<0.05). Both reconstruction methods revealed good image quality with excellent inter-observer agreement. The evaluated software for automatic labeling and anatomically aligned, double-angulated axial image reconstruction of the thoracolumbar spine on CT is time-saving when reconstructions of 2 and more vertebrae are performed. Checking results of automatic labeling is necessary to prevent errors in labeling. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Ghaffari, Mahsa; Tangen, Kevin; Alaraj, Ali; Du, Xinjian; Charbel, Fady T; Linninger, Andreas A
2017-12-01
In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications. Copyright © 2017 Elsevier Ltd. All rights reserved.
Jimenez-Del-Toro, Oscar; Muller, Henning; Krenn, Markus; Gruenberg, Katharina; Taha, Abdel Aziz; Winterstein, Marianne; Eggel, Ivan; Foncubierta-Rodriguez, Antonio; Goksel, Orcun; Jakab, Andras; Kontokotsios, Georgios; Langs, Georg; Menze, Bjoern H; Salas Fernandez, Tomas; Schaer, Roger; Walleyo, Anna; Weber, Marc-Andre; Dicente Cid, Yashin; Gass, Tobias; Heinrich, Mattias; Jia, Fucang; Kahl, Fredrik; Kechichian, Razmig; Mai, Dominic; Spanier, Assaf B; Vincent, Graham; Wang, Chunliang; Wyeth, Daniel; Hanbury, Allan
2016-11-01
Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for anatomical structure segmentation and landmark detection: the VISCERAL Anatomy benchmarks. The algorithms are implemented in virtual machines in the cloud where participants can only access the training data and can be run privately by the benchmark administrators to objectively compare their performance in an unseen common test set. Overall, 120 computed tomography and magnetic resonance patient volumes were manually annotated to create a standard Gold Corpus containing a total of 1295 structures and 1760 landmarks. Ten participants contributed with automatic algorithms for the organ segmentation task, and three for the landmark localization task. Different algorithms obtained the best scores in the four available imaging modalities and for subsets of anatomical structures. The annotation framework, resulting data set, evaluation setup, results and performance analysis from the three VISCERAL Anatomy benchmarks are presented in this article. Both the VISCERAL data set and Silver Corpus generated with the fusion of the participant algorithms on a larger set of non-manually-annotated medical images are available to the research community.
2D image classification for 3D anatomy localization: employing deep convolutional neural networks
NASA Astrophysics Data System (ADS)
de Vos, Bob D.; Wolterink, Jelmer M.; de Jong, Pim A.; Viergever, Max A.; Išgum, Ivana
2016-03-01
Localization of anatomical regions of interest (ROIs) is a preprocessing step in many medical image analysis tasks. While trivial for humans, it is complex for automatic methods. Classic machine learning approaches require the challenge of hand crafting features to describe differences between ROIs and background. Deep convolutional neural networks (CNNs) alleviate this by automatically finding hierarchical feature representations from raw images. We employ this trait to detect anatomical ROIs in 2D image slices in order to localize them in 3D. In 100 low-dose non-contrast enhanced non-ECG synchronized screening chest CT scans, a reference standard was defined by manually delineating rectangular bounding boxes around three anatomical ROIs -- heart, aortic arch, and descending aorta. Every anatomical ROI was automatically identified using a combination of three CNNs, each analyzing one orthogonal image plane. While single CNNs predicted presence or absence of a specific ROI in the given plane, the combination of their results provided a 3D bounding box around it. Classification performance of each CNN, expressed in area under the receiver operating characteristic curve, was >=0.988. Additionally, the performance of ROI localization was evaluated. Median Dice scores for automatically determined bounding boxes around the heart, aortic arch, and descending aorta were 0.89, 0.70, and 0.85 respectively. The results demonstrate that accurate automatic 3D localization of anatomical structures by CNN-based 2D image classification is feasible.
Generating Neuron Geometries for Detailed Three-Dimensional Simulations Using AnaMorph.
Mörschel, Konstantin; Breit, Markus; Queisser, Gillian
2017-07-01
Generating realistic and complex computational domains for numerical simulations is often a challenging task. In neuroscientific research, more and more one-dimensional morphology data is becoming publicly available through databases. This data, however, only contains point and diameter information not suitable for detailed three-dimensional simulations. In this paper, we present a novel framework, AnaMorph, that automatically generates water-tight surface meshes from one-dimensional point-diameter files. These surface triangulations can be used to simulate the electrical and biochemical behavior of the underlying cell. In addition to morphology generation, AnaMorph also performs quality control of the semi-automatically reconstructed cells coming from anatomical reconstructions. This toolset allows an extension from the classical dimension-reduced modeling and simulation of cellular processes to a full three-dimensional and morphology-including method, leading to novel structure-function interplay studies in the medical field. The developed numerical methods can further be employed in other areas where complex geometries are an essential component of numerical simulations.
COMICS: Cartoon Visualization of Omics Data in Spatial Context Using Anatomical Ontologies
2017-01-01
COMICS is an interactive and open-access web platform for integration and visualization of molecular expression data in anatomograms of zebrafish, carp, and mouse model systems. Anatomical ontologies are used to map omics data across experiments and between an experiment and a particular visualization in a data-dependent manner. COMICS is built on top of several existing resources. Zebrafish and mouse anatomical ontologies with their controlled vocabulary (CV) and defined hierarchy are used with the ontoCAT R package to aggregate data for comparison and visualization. Libraries from the QGIS geographical information system are used with the R packages “maps” and “maptools” to visualize and interact with molecular expression data in anatomical drawings of the model systems. COMICS allows users to upload their own data from omics experiments, using any gene or protein nomenclature they wish, as long as CV terms are used to define anatomical regions or developmental stages. Common nomenclatures such as the ZFIN gene names and UniProt accessions are provided additional support. COMICS can be used to generate publication-quality visualizations of gene and protein expression across experiments. Unlike previous tools that have used anatomical ontologies to interpret imaging data in several animal models, including zebrafish, COMICS is designed to take spatially resolved data generated by dissection or fractionation and display this data in visually clear anatomical representations rather than large data tables. COMICS is optimized for ease-of-use, with a minimalistic web interface and automatic selection of the appropriate visual representation depending on the input data. PMID:29083911
COMICS: Cartoon Visualization of Omics Data in Spatial Context Using Anatomical Ontologies.
Travin, Dmitrii; Popov, Iaroslav; Guler, Arzu Tugce; Medvedev, Dmitry; van der Plas-Duivesteijn, Suzanne; Varela, Monica; Kolder, Iris C R M; Meijer, Annemarie H; Spaink, Herman P; Palmblad, Magnus
2018-01-05
COMICS is an interactive and open-access web platform for integration and visualization of molecular expression data in anatomograms of zebrafish, carp, and mouse model systems. Anatomical ontologies are used to map omics data across experiments and between an experiment and a particular visualization in a data-dependent manner. COMICS is built on top of several existing resources. Zebrafish and mouse anatomical ontologies with their controlled vocabulary (CV) and defined hierarchy are used with the ontoCAT R package to aggregate data for comparison and visualization. Libraries from the QGIS geographical information system are used with the R packages "maps" and "maptools" to visualize and interact with molecular expression data in anatomical drawings of the model systems. COMICS allows users to upload their own data from omics experiments, using any gene or protein nomenclature they wish, as long as CV terms are used to define anatomical regions or developmental stages. Common nomenclatures such as the ZFIN gene names and UniProt accessions are provided additional support. COMICS can be used to generate publication-quality visualizations of gene and protein expression across experiments. Unlike previous tools that have used anatomical ontologies to interpret imaging data in several animal models, including zebrafish, COMICS is designed to take spatially resolved data generated by dissection or fractionation and display this data in visually clear anatomical representations rather than large data tables. COMICS is optimized for ease-of-use, with a minimalistic web interface and automatic selection of the appropriate visual representation depending on the input data.
Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation
NASA Astrophysics Data System (ADS)
Kneser, Reinhard; Lehmann, Helko; Geller, Dieter; Qian, Yue-Chen; Weese, Jürgen
2009-02-01
To make accurate decisions based on imaging data, radiologists must associate the viewed imaging data with the corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or ambiguous findings are present, external knowledge sources such as medical encyclopedias are consulted. These sources are accessed using keywords typically describing anatomical structures, image findings, pathologies. In this paper we present our vision of how a patient's imaging data can be automatically enhanced with anatomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to access anatomical descriptions, information about pathologies and image findings. On the other hand we envision encyclopedias to contain links to region- and finding-specific image processing algorithms. Then a finding is evaluated on an image by applying the respective algorithm in the associated anatomical region. Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain images. Thereby we develop a complex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We demonstrate the validity by analyzing the results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.
NASA Astrophysics Data System (ADS)
Wasserthal, Christian; Engel, Karin; Rink, Karsten; Brechmann, Andr'e.
We propose an automatic procedure for the correct segmentation of grey and white matter in MR data sets of the human brain. Our method exploits general anatomical knowledge for the initial segmentation and for the subsequent refinement of the estimation of the cortical grey matter. Our results are comparable to manual segmentations.
Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT
NASA Astrophysics Data System (ADS)
Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi
2017-05-01
Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.
An automatic dose verification system for adaptive radiotherapy for helical tomotherapy
NASA Astrophysics Data System (ADS)
Mo, Xiaohu; Chen, Mingli; Parnell, Donald; Olivera, Gustavo; Galmarini, Daniel; Lu, Weiguo
2014-03-01
Purpose: During a typical 5-7 week treatment of external beam radiotherapy, there are potential differences between planned patient's anatomy and positioning, such as patient weight loss, or treatment setup. The discrepancies between planned and delivered doses resulting from these differences could be significant, especially in IMRT where dose distributions tightly conforms to target volumes while avoiding organs-at-risk. We developed an automatic system to monitor delivered dose using daily imaging. Methods: For each treatment, a merged image is generated by registering the daily pre-treatment setup image and planning CT using treatment position information extracted from the Tomotherapy archive. The treatment dose is then computed on this merged image using our in-house convolution-superposition based dose calculator implemented on GPU. The deformation field between merged and planning CT is computed using the Morphon algorithm. The planning structures and treatment doses are subsequently warped for analysis and dose accumulation. All results are saved in DICOM format with private tags and organized in a database. Due to the overwhelming amount of information generated, a customizable tolerance system is used to flag potential treatment errors or significant anatomical changes. A web-based system and a DICOM-RT viewer were developed for reporting and reviewing the results. Results: More than 30 patients were analysed retrospectively. Our in-house dose calculator passed 97% gamma test evaluated with 2% dose difference and 2mm distance-to-agreement compared with Tomotherapy calculated dose, which is considered sufficient for adaptive radiotherapy purposes. Evaluation of the deformable registration through visual inspection showed acceptable and consistent results, except for cases with large or unrealistic deformation. Our automatic flagging system was able to catch significant patient setup errors or anatomical changes. Conclusions: We developed an automatic dose verification system that quantifies treatment doses, and provides necessary information for adaptive planning without impeding clinical workflows.
Nowinski, Wieslaw L; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G; Marchenko, Yevgen; Volkau, Ihar
2009-10-01
Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to Terminologia Anatomica. Because the cerebral models are fully segmented and labeled, our approach enables automatic and random atlas-derived generation of questions to test location and naming of cerebral structures. This is done in four steps: test individualization by the instructor, test taking by the students at their convenience, automatic student assessment by the application, and communication of the individual assessment to the instructor. A computer-based application with an interactive 3D atlas and a preliminary mobile-based application were developed to realize this approach. The application works in two test modes: instructor and student. In the instructor mode, the instructor customizes the test by setting the scope of testing and student performance criteria, which takes a few seconds. In the student mode, the student is tested and automatically assessed. Self-testing is also feasible at any time and pace. Our approach is automatic both with respect to test generation and student assessment. It is also objective, rapid, and customizable. We believe that this approach is novel from computer-based, mobile-based, and atlas-assisted standpoints.
Virgincar, Rohan S.; Cleveland, Zackary I.; Kaushik, S. Sivaram; Freeman, Matthew S.; Nouls, John; Cofer, Gary P.; Martinez-Jimenez, Santiago; He, Mu; Kraft, Monica; Wolber, Jan; McAdams, H. Page; Driehuys, Bastiaan
2013-01-01
In this study, hyperpolarized (HP) 129Xe MR ventilation and 1H anatomical images were obtained from 3 subject groups: young healthy volunteers (HV), subjects with chronic obstructive pulmonary disease (COPD), and age-matched control subjects (AMC). Ventilation images were quantified by 2 methods: an expert reader-based ventilation defect score percentage (VDS%) and a semi-automatic segmentation-based ventilation defect percentage (VDP). Reader-based values were assigned by two experienced radiologists and resolved by consensus. In the semi-automatic analysis, 1H anatomical images and 129Xe ventilation images were both segmented following registration, to obtain the thoracic cavity volume (TCV) and ventilated volume (VV), respectively, which were then expressed as a ratio to obtain the VDP. Ventilation images were also characterized by generating signal intensity histograms from voxels within the TCV, and heterogeneity was analyzed using the coefficient of variation (CV). The reader-based VDS% correlated strongly with the semi-automatically generated VDP (r = 0.97, p < 0.0001), and with CV (r = 0.82, p < 0.0001). Both 129Xe ventilation defect scoring metrics readily separated the 3 groups from one another and correlated significantly with FEV1 (VDS%: r = -0.78, p = 0.0002; VDP: r = -0.79, p = 0.0003; CV: r = -0.66, p = 0.0059) and other pulmonary function tests. In the healthy subject groups (HV and AMC), the prevalence of ventilation defects also increased with age (VDS%: r = 0.61, p = 0.0002; VDP: r = 0.63, p = 0.0002). Moreover, ventilation histograms and their associated CVs distinguished between COPD subjects with similar ventilation defect scores but visibly different ventilation patterns. PMID:23065808
Automatic anatomical segmentation of the liver by separation planes
NASA Astrophysics Data System (ADS)
Boltcheva, Dobrina; Passat, Nicolas; Agnus, Vincent; Jacob-Da, Marie-Andrée, , Col; Ronse, Christian; Soler, Luc
2006-03-01
Surgical planning in oncological liver surgery is based on the location of the 8 anatomical segments according to Couinaud's definition and tumors inside these structures. The detection of the boundaries between the segments is then the first step of the preoperative planning. The proposed method, devoted to binary images of livers segmented from CT-scans, has been designed to delineate these segments. It automatically detects a set of landmarks using a priori anatomical knowledge and differential geometry criteria. These landmarks are then used to position the Couinaud's segments. Validations performed on 7 clinical cases tend to prove that the method is reliable for most of these separation planes.
Geraghty, John P; Grogan, Garry; Ebert, Martin A
2013-04-30
This study investigates the variation in segmentation of several pelvic anatomical structures on computed tomography (CT) between multiple observers and a commercial automatic segmentation method, in the context of quality assurance and evaluation during a multicentre clinical trial. CT scans of two prostate cancer patients ('benchmarking cases'), one high risk (HR) and one intermediate risk (IR), were sent to multiple radiotherapy centres for segmentation of prostate, rectum and bladder structures according to the TROG 03.04 "RADAR" trial protocol definitions. The same structures were automatically segmented using iPlan software for the same two patients, allowing structures defined by automatic segmentation to be quantitatively compared with those defined by multiple observers. A sample of twenty trial patient datasets were also used to automatically generate anatomical structures for quantitative comparison with structures defined by individual observers for the same datasets. There was considerable agreement amongst all observers and automatic segmentation of the benchmarking cases for bladder (mean spatial variations < 0.4 cm across the majority of image slices). Although there was some variation in interpretation of the superior-inferior (cranio-caudal) extent of rectum, human-observer contours were typically within a mean 0.6 cm of automatically-defined contours. Prostate structures were more consistent for the HR case than the IR case with all human observers segmenting a prostate with considerably more volume (mean +113.3%) than that automatically segmented. Similar results were seen across the twenty sample datasets, with disagreement between iPlan and observers dominant at the prostatic apex and superior part of the rectum, which is consistent with observations made during quality assurance reviews during the trial. This study has demonstrated quantitative analysis for comparison of multi-observer segmentation studies. For automatic segmentation algorithms based on image-registration as in iPlan, it is apparent that agreement between observer and automatic segmentation will be a function of patient-specific image characteristics, particularly for anatomy with poor contrast definition. For this reason, it is suggested that automatic registration based on transformation of a single reference dataset adds a significant systematic bias to the resulting volumes and their use in the context of a multicentre trial should be carefully considered.
NASA Astrophysics Data System (ADS)
Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.
2015-03-01
Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.
Anatomical entity mention recognition at literature scale
Pyysalo, Sampo; Ananiadou, Sophia
2014-01-01
Motivation: Anatomical entities ranging from subcellular structures to organ systems are central to biomedical science, and mentions of these entities are essential to understanding the scientific literature. Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced. Results: We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition. The system incorporates a broad array of approaches proposed to benefit tagging, including the use of Unified Medical Language System (UMLS)- and Open Biomedical Ontologies (OBO)-based lexical resources, word representations induced from unlabeled text, statistical truecasing and non-local features. We train and evaluate the system on a newly introduced corpus that substantially extends on previously available resources, and apply the resulting tagger to automatically annotate the entire open access scientific domain literature. The resulting analyses have been applied to extend services provided by the Europe PubMed Central literature database. Availability and implementation: All tools and resources introduced in this work are available from http://nactem.ac.uk/anatomytagger. Contact: sophia.ananiadou@manchester.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24162468
Automatic computation of 2D cardiac measurements from B-mode echocardiography
NASA Astrophysics Data System (ADS)
Park, JinHyeong; Feng, Shaolei; Zhou, S. Kevin
2012-03-01
We propose a robust and fully automatic algorithm which computes the 2D echocardiography measurements recommended by America Society of Echocardiography. The algorithm employs knowledge-based imaging technologies which can learn the expert's knowledge from the training images and expert's annotation. Based on the models constructed from the learning stage, the algorithm searches initial location of the landmark points for the measurements by utilizing heart structure of left ventricle including mitral valve aortic valve. It employs the pseudo anatomic M-mode image generated by accumulating the line images in 2D parasternal long axis view along the time to refine the measurement landmark points. The experiment results with large volume of data show that the algorithm runs fast and is robust comparable to expert.
Validation and detection of vessel landmarks by using anatomical knowledge
NASA Astrophysics Data System (ADS)
Beck, Thomas; Bernhardt, Dominik; Biermann, Christina; Dillmann, Rüdiger
2010-03-01
The detection of anatomical landmarks is an important prerequisite to analyze medical images fully automatically. Several machine learning approaches have been proposed to parse 3D CT datasets and to determine the location of landmarks with associated uncertainty. However, it is a challenging task to incorporate high-level anatomical knowledge to improve these classification results. We propose a new approach to validate candidates for vessel bifurcation landmarks which is also applied to systematically search missed and to validate ambiguous landmarks. A knowledge base is trained providing human-readable geometric information of the vascular system, mainly vessel lengths, radii and curvature information, for validation of landmarks and to guide the search process. To analyze the bifurcation area surrounding a vessel landmark of interest, a new approach is proposed which is based on Fast Marching and incorporates anatomical information from the knowledge base. Using the proposed algorithms, an anatomical knowledge base has been generated based on 90 manually annotated CT images containing different parts of the body. To evaluate the landmark validation a set of 50 carotid datasets has been tested in combination with a state of the art landmark detector with excellent results. Beside the carotid bifurcation the algorithm is designed to handle a wide range of vascular landmarks, e.g. celiac, superior mesenteric, renal, aortic, iliac and femoral bifurcation.
SU-F-T-423: Automating Treatment Planning for Cervical Cancer in Low- and Middle- Income Countries
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kisling, K; Zhang, L; Yang, J
Purpose: To develop and test two independent algorithms that automatically create the photon treatment fields for a four-field box beam arrangement, a common treatment technique for cervical cancer in low- and middle-income countries. Methods: Two algorithms were developed and integrated into Eclipse using its Advanced Programming Interface:3D Method: We automatically segment bony anatomy on CT using an in-house multi-atlas contouring tool and project the structures into the beam’s-eye-view. We identify anatomical landmarks on the projections to define the field apertures. 2D Method: We generate DRRs for all four beams. An atlas of DRRs for six standard patients with corresponding fieldmore » apertures are deformably registered to the test patient DRRs. The set of deformed atlas apertures are fitted to an expected shape to define the final apertures. Both algorithms were tested on 39 patient CTs, and the resulting treatment fields were scored by a radiation oncologist. We also investigated the feasibility of using one algorithm as an independent check of the other algorithm. Results: 96% of the 3D-Method-generated fields and 79% of the 2D-method-generated fields were scored acceptable for treatment (“Per Protocol” or “Acceptable Variation”). The 3D Method generated more fields scored “Per Protocol” than the 2D Method (62% versus 17%). The 4% of the 3D-Method-generated fields that were scored “Unacceptable Deviation” were all due to an improper L5 vertebra contour resulting in an unacceptable superior jaw position. When these same patients were planned with the 2D method, the superior jaw was acceptable, suggesting that the 2D method can be used to independently check the 3D method. Conclusion: Our results show that our 3D Method is feasible for automatically generating cervical treatment fields. Furthermore, the 2D Method can serve as an automatic, independent check of the automatically-generated treatment fields. These algorithms will be implemented for fully automated cervical treatment planning.« less
Xie, Long; Pluta, John B.; Das, Sandhitsu R.; Wisse, Laura E.M.; Wang, Hongzhi; Mancuso, Lauren; Kliot, Dasha; Avants, Brian B.; Ding, Song-Lin; Manjón, José V.; Wolk, David A.; Yushkevich, Paul A.
2016-01-01
Rational The human perirhinal cortex (PRC) plays critical roles in episodic and semantic memory and visual perception. The PRC consists of Brodmann areas 35 and 36 (BA35, BA36). In Alzheimer's disease (AD), BA35 is the first cortical site affected by neurofibrillary tangle pathology, which is closely linked to neural injury in AD. Large anatomical variability, manifested in the form of different cortical folding and branching patterns, makes it difficult to segment the PRC in MRI scans. Pathology studies have found that in ~97% of specimens, the PRC falls into one of three discrete anatomical variants. However, current methods for PRC segmentation and morphometry in MRI are based on single-template approaches, which may not be able to accurately model these discrete variants Methods A multi-template analysis pipeline that explicitly accounts for anatomical variability is used to automatically label the PRC and measure its thickness in T2-weighted MRI scans. The pipeline uses multi-atlas segmentation to automatically label medial temporal lobe cortices including entorhinal cortex, PRC and the parahippocampal cortex. Pairwise registration between label maps and clustering based on residual dissimilarity after registration are used to construct separate templates for the anatomical variants of the PRC. An optimal path of deformations linking these templates is used to establish correspondences between all the subjects. Experimental evaluation focuses on the ability of single-template and multi-template analyses to detect differences in the thickness of medial temporal lobe cortices between patients with amnestic mild cognitive impairment (aMCI, n=41) and age-matched controls (n=44). Results The proposed technique is able to generate templates that recover the three dominant discrete variants of PRC and establish more meaningful correspondences between subjects than a single-template approach. The largest reduction in thickness associated with aMCI, in absolute terms, was found in left BA35 using both regional and summary thickness measures. Further, statistical maps of regional thickness difference between aMCI and controls revealed different patterns for the three anatomical variants. PMID:27702610
A quality score for coronary artery tree extraction results
NASA Astrophysics Data System (ADS)
Cao, Qing; Broersen, Alexander; Kitslaar, Pieter H.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke
2018-02-01
Coronary artery trees (CATs) are often extracted to aid the fully automatic analysis of coronary artery disease on coronary computed tomography angiography (CCTA) images. Automatically extracted CATs often miss some arteries or include wrong extractions which require manual corrections before performing successive steps. For analyzing a large number of datasets, a manual quality check of the extraction results is time-consuming. This paper presents a method to automatically calculate quality scores for extracted CATs in terms of clinical significance of the extracted arteries and the completeness of the extracted CAT. Both right dominant (RD) and left dominant (LD) anatomical statistical models are generated and exploited in developing the quality score. To automatically determine which model should be used, a dominance type detection method is also designed. Experiments are performed on the automatically extracted and manually refined CATs from 42 datasets to evaluate the proposed quality score. In 39 (92.9%) cases, the proposed method is able to measure the quality of the manually refined CATs with higher scores than the automatically extracted CATs. In a 100-point scale system, the average scores for automatically and manually refined CATs are 82.0 (+/-15.8) and 88.9 (+/-5.4) respectively. The proposed quality score will assist the automatic processing of the CAT extractions for large cohorts which contain both RD and LD cases. To the best of our knowledge, this is the first time that a general quality score for an extracted CAT is presented.
Deformable templates guided discriminative models for robust 3D brain MRI segmentation.
Liu, Cheng-Yi; Iglesias, Juan Eugenio; Tu, Zhuowen
2013-10-01
Automatically segmenting anatomical structures from 3D brain MRI images is an important task in neuroimaging. One major challenge is to design and learn effective image models accounting for the large variability in anatomy and data acquisition protocols. A deformable template is a type of generative model that attempts to explicitly match an input image with a template (atlas), and thus, they are robust against global intensity changes. On the other hand, discriminative models combine local image features to capture complex image patterns. In this paper, we propose a robust brain image segmentation algorithm that fuses together deformable templates and informative features. It takes advantage of the adaptation capability of the generative model and the classification power of the discriminative models. The proposed algorithm achieves both robustness and efficiency, and can be used to segment brain MRI images with large anatomical variations. We perform an extensive experimental study on four datasets of T1-weighted brain MRI data from different sources (1,082 MRI scans in total) and observe consistent improvement over the state-of-the-art systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van de Velde, Joris, E-mail: joris.vandevelde@ugent.be; Department of Radiotherapy, Ghent University, Ghent; Audenaert, Emmanuel
Purpose: To develop contouring guidelines for the brachial plexus (BP) using anatomically validated cadaver datasets. Magnetic resonance imaging (MRI) and computed tomography (CT) were used to obtain detailed visualizations of the BP region, with the goal of achieving maximal inclusion of the actual BP in a small contoured volume while also accommodating for anatomic variations. Methods and Materials: CT and MRI were obtained for 8 cadavers positioned for intensity modulated radiation therapy. 3-dimensional reconstructions of soft tissue (from MRI) and bone (from CT) were combined to create 8 separate enhanced CT project files. Dissection of the corresponding cadavers anatomically validatedmore » the reconstructions created. Seven enhanced CT project files were then automatically fitted, separately in different regions, to obtain a single dataset of superimposed BP regions that incorporated anatomic variations. From this dataset, improved BP contouring guidelines were developed. These guidelines were then applied to the 7 original CT project files and also to 1 additional file, left out from the superimposing procedure. The percentage of BP inclusion was compared with the published guidelines. Results: The anatomic validation procedure showed a high level of conformity for the BP regions examined between the 3-dimensional reconstructions generated and the dissected counterparts. Accurate and detailed BP contouring guidelines were developed, which provided corresponding guidance for each level in a clinical dataset. An average margin of 4.7 mm around the anatomically validated BP contour is sufficient to accommodate for anatomic variations. Using the new guidelines, 100% inclusion of the BP was achieved, compared with a mean inclusion of 37.75% when published guidelines were applied. Conclusion: Improved guidelines for BP delineation were developed using combined MRI and CT imaging with validation by anatomic dissection.« less
Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM
NASA Astrophysics Data System (ADS)
Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.
2016-04-01
The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.
Automated branching pattern report generation for laparoscopic surgery assistance
NASA Astrophysics Data System (ADS)
Oda, Masahiro; Matsuzaki, Tetsuro; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku
2015-05-01
This paper presents a method for generating branching pattern reports of abdominal blood vessels for laparoscopic gastrectomy. In gastrectomy, it is very important to understand branching structure of abdominal arteries and veins, which feed and drain specific abdominal organs including the stomach, the liver and the pancreas. In the real clinical stage, a surgeon creates a diagnostic report of the patient anatomy. This report summarizes the branching patterns of the blood vessels related to the stomach. The surgeon decides actual operative procedure. This paper shows an automated method to generate a branching pattern report for abdominal blood vessels based on automated anatomical labeling. The report contains 3D rendering showing important blood vessels and descriptions of branching patterns of each vessel. We have applied this method for fifty cases of 3D abdominal CT scans and confirmed the proposed method can automatically generate branching pattern reports of abdominal arteries.
Griffiths, K R; Grieve, S M; Kohn, M R; Clarke, S; Williams, L M; Korgaonkar, M S
2016-01-01
Although multiple studies have reported structural deficits in multiple brain regions in attention-deficit hyperactivity disorder (ADHD), we do not yet know if these deficits reflect a more systematic disruption to the anatomical organization of large-scale brain networks. Here we used a graph theoretical approach to quantify anatomical organization in children and adolescents with ADHD. We generated anatomical networks based on covariance of gray matter volumes from 92 regions across the brain in children and adolescents with ADHD (n=34) and age- and sex-matched healthy controls (n=28). Using graph theory, we computed metrics that characterize both the global organization of anatomical networks (interconnectivity (clustering), integration (path length) and balance of global integration and localized segregation (small-worldness)) and their local nodal measures (participation (degree) and interaction (betweenness) within a network). Relative to Controls, ADHD participants exhibited altered global organization reflected in more clustering or network segregation. Locally, nodal degree and betweenness were increased in the subcortical amygdalae in ADHD, but reduced in cortical nodes in the anterior cingulate, posterior cingulate, mid temporal pole and rolandic operculum. In ADHD, anatomical networks were disrupted and reflected an emphasis on subcortical local connections centered around the amygdala, at the expense of cortical organization. Brains of children and adolescents with ADHD may be anatomically configured to respond impulsively to the automatic significance of stimulus input without having the neural organization to regulate and inhibit these responses. These findings provide a novel addition to our current understanding of the ADHD connectome. PMID:27824356
Generation algorithm of craniofacial structure contour in cephalometric images
NASA Astrophysics Data System (ADS)
Mondal, Tanmoy; Jain, Ashish; Sardana, H. K.
2010-02-01
Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Computerized cephalometric analysis involves both manual and automatic approaches. The manual approach is limited in accuracy and repeatability. In this paper we have attempted to develop and test a novel method for automatic localization of craniofacial structure based on the detected edges on the region of interest. According to the grey scale feature at the different region of the cephalometric images, an algorithm for obtaining tissue contour is put forward. Using edge detection with specific threshold an improved bidirectional contour tracing approach is proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.
Tooth segmentation system with intelligent editing for cephalometric analysis
NASA Astrophysics Data System (ADS)
Chen, Shoupu
2015-03-01
Cephalometric analysis is the study of the dental and skeletal relationship in the head, and it is used as an assessment and planning tool for improved orthodontic treatment of a patient. Conventional cephalometric analysis identifies bony and soft-tissue landmarks in 2D cephalometric radiographs, in order to diagnose facial features and abnormalities prior to treatment, or to evaluate the progress of treatment. Recent studies in orthodontics indicate that there are persistent inaccuracies and inconsistencies in the results provided using conventional 2D cephalometric analysis. Obviously, plane geometry is inappropriate for analyzing anatomical volumes and their growth; only a 3D analysis is able to analyze the three-dimensional, anatomical maxillofacial complex, which requires computing inertia systems for individual or groups of digitally segmented teeth from an image volume of a patient's head. For the study of 3D cephalometric analysis, the current paper proposes a system for semi-automatically segmenting teeth from a cone beam computed tomography (CBCT) volume with two distinct features, including an intelligent user-input interface for automatic background seed generation, and a graphics processing unit (GPU) acceleration mechanism for three-dimensional GrowCut volume segmentation. Results show a satisfying average DICE score of 0.92, with the use of the proposed tooth segmentation system, by 15 novice users who segmented a randomly sampled tooth set. The average GrowCut processing time is around one second per tooth, excluding user interaction time.
NASA Astrophysics Data System (ADS)
Wentz, Robert; Manduca, Armando; Fletcher, J. G.; Siddiki, Hassan; Shields, Raymond C.; Vrtiska, Terri; Spencer, Garrett; Primak, Andrew N.; Zhang, Jie; Nielson, Theresa; McCollough, Cynthia; Yu, Lifeng
2007-03-01
Purpose: To develop robust, novel segmentation and co-registration software to analyze temporally overlapping CT angiography datasets, with an aim to permit automated measurement of regional aortic pulsatility in patients with abdominal aortic aneurysms. Methods: We perform retrospective gated CT angiography in patients with abdominal aortic aneurysms. Multiple, temporally overlapping, time-resolved CT angiography datasets are reconstructed over the cardiac cycle, with aortic segmentation performed using a priori anatomic assumptions for the aorta and heart. Visual quality assessment is performed following automatic segmentation with manual editing. Following subsequent centerline generation, centerlines are cross-registered across phases, with internal validation of co-registration performed by examining registration at the regions of greatest diameter change (i.e. when the second derivative is maximal). Results: We have performed gated CT angiography in 60 patients. Automatic seed placement is successful in 79% of datasets, requiring either no editing (70%) or minimal editing (less than 1 minute; 12%). Causes of error include segmentation into adjacent, high-attenuating, nonvascular tissues; small segmentation errors associated with calcified plaque; and segmentation of non-renal, small paralumbar arteries. Internal validation of cross-registration demonstrates appropriate registration in our patient population. In general, we observed that aortic pulsatility can vary along the course of the abdominal aorta. Pulsation can also vary within an aneurysm as well as between aneurysms, but the clinical significance of these findings remain unknown. Conclusions: Visualization of large vessel pulsatility is possible using ECG-gated CT angiography, partial scan reconstruction, automatic segmentation, centerline generation, and coregistration of temporally resolved datasets.
Higgins, Sean W; Spratley, E Meade; Boe, Richard A; Hayes, Curtis W; Jiranek, William A; Wayne, Jennifer S
2014-11-05
The inherently complex three-dimensional morphology of both the pelvis and acetabulum create difficulties in accurately determining acetabular orientation. Our objectives were to develop a reliable and accurate methodology for determining three-dimensional acetabular orientation and to utilize it to describe relevant characteristics of a large population of subjects without apparent hip pathology. High-resolution computed tomography studies of 200 patients previously receiving pelvic scans for indications not related to orthopaedic conditions were selected from our institution's database. Three-dimensional models of each osseous pelvis were generated to extract specific anatomical data sets. A novel computational method was developed to determine standard measures of three-dimensional acetabular orientation within an automatically identified anterior pelvic plane reference frame. Automatically selected points on the osseous ridge of the acetabulum were used to generate a best-fit plane for describing acetabular orientation. Our method showed excellent interobserver and intraobserver agreement (an intraclass correlation coefficient [ICC] of >0.999) and achieved high levels of accuracy. A significant difference between males and females in both anteversion (average, 3.5°; 95% confidence interval [CI], 1.9° to 5.1° across all angular definitions; p < 0.0001) and inclination (1.4°; 95% CI, 0.6° to 2.3° for anatomic angular definition; p < 0.002) was observed. Intrapatient asymmetry in anatomic measures showed bilateral differences in anteversion (maximum, 12.1°) and in inclination (maximum, 10.9°). Significant differences in acetabular orientation between the sexes can be detected only with accurate measurements that account for the entire acetabulum. While a wide range of interpatient acetabular orientations was observed, the majority of subjects had acetabula that were relatively symmetrical in both inclination and anteversion. A highly accurate and reproducible method for determining the orientation of the acetabulum's aperture will benefit both surgeons and patients, by further refining the distinctions between normal and abnormal hip characteristics. Enhanced understanding of the acetabulum could be useful in the diagnostic, planning, and execution stages for surgical procedures of the hip or in advancing the design of new implant systems. Copyright © 2014 by The Journal of Bone and Joint Surgery, Incorporated.
An algorithm for automatic parameter adjustment for brain extraction in BrainSuite
NASA Astrophysics Data System (ADS)
Rajagopal, Gautham; Joshi, Anand A.; Leahy, Richard M.
2017-02-01
Brain Extraction (classification of brain and non-brain tissue) of MRI brain images is a crucial pre-processing step necessary for imaging-based anatomical studies of the human brain. Several automated methods and software tools are available for performing this task, but differences in MR image parameters (pulse sequence, resolution) and instrumentand subject-dependent noise and artefacts affect the performance of these automated methods. We describe and evaluate a method that automatically adapts the default parameters of the Brain Surface Extraction (BSE) algorithm to optimize a cost function chosen to reflect accurate brain extraction. BSE uses a combination of anisotropic filtering, Marr-Hildreth edge detection, and binary morphology for brain extraction. Our algorithm automatically adapts four parameters associated with these steps to maximize the brain surface area to volume ratio. We evaluate the method on a total of 109 brain volumes with ground truth brain masks generated by an expert user. A quantitative evaluation of the performance of the proposed algorithm showed an improvement in the mean (s.d.) Dice coefficient from 0.8969 (0.0376) for default parameters to 0.9509 (0.0504) for the optimized case. These results indicate that automatic parameter optimization can result in significant improvements in definition of the brain mask.
Automatic Clustering and Thickness Measurement of Anatomical Variants of the Human Perirhinal Cortex
Xie, Long; Pluta, John; Wang, Hongzhi; Das, Sandhitsu R.; Mancuso, Lauren; Kliot, Dasha; Avants, Brian B.; Ding, Song-Lin; Wolk, David A.; Yushkevich, Paul A.
2015-01-01
The entorhinal cortex (ERC) and the perirhinal cortex (PRC) are subregions of the medial temporal lobe (MTL) that play important roles in episodic memory representations, as well as serving as a conduit between other neocortical areas and the hippocampus. They are also the sites where neuronal damage first occurs in Alzheimer’s disease (AD). The ability to automatically quantify the volume and thickness of the ERC and PRC is desirable because these localized measures can potentially serve as better imaging biomarkers for AD and other neurodegenerative diseases. However, large anatomical variation in the PRC makes it a challenging area for analysis. In order to address this problem, we propose an automatic segmentation, clustering, and thickness measurement approach that explicitly accounts for anatomical variation. The approach is targeted to highly anisotropic (0.4×0.4×2.0mm3) T2-weighted MRI scans that are preferred by many authors for detailed imaging of the MTL, but which pose challenges for segmentation and shape analysis. After automatically labeling MTL substructures using multi-atlas segmentation, our method clusters subjects into groups based on the shape of the PRC, constructs unbiased population templates for each group, and uses the smooth surface representations obtained during template construction to extract regional thickness measurements in the space of each subject. The proposed thickness measures are evaluated in the context of discrimination between patients with Mild Cognitive Impairment (MCI) and normal controls (NC). PMID:25320785
Automatic Perceptual Color Map Generation for Realistic Volume Visualization
Silverstein, Jonathan C.; Parsad, Nigel M.; Tsirline, Victor
2008-01-01
Advances in computed tomography imaging technology and inexpensive high performance computer graphics hardware are making high-resolution, full color (24-bit) volume visualizations commonplace. However, many of the color maps used in volume rendering provide questionable value in knowledge representation and are non-perceptual thus biasing data analysis or even obscuring information. These drawbacks, coupled with our need for realistic anatomical volume rendering for teaching and surgical planning, has motivated us to explore the auto-generation of color maps that combine natural colorization with the perceptual discriminating capacity of grayscale. As evidenced by the examples shown that have been created by the algorithm described, the merging of perceptually accurate and realistically colorized virtual anatomy appears to insightfully interpret and impartially enhance volume rendered patient data. PMID:18430609
A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study.
Ed-Dhahraouy, Mohammed; Riri, Hicham; Ezzahmouly, Manal; Bourzgui, Farid; El Moutaoukkil, Abdelmajid
2018-04-05
The aim of this study was to develop a new method for an automatic detection of reference points in 3D cephalometry to overcome the limits of 2D cephalometric analyses. A specific application was designed using the C++ language for automatic and manual identification of 21 (reference) points on the craniofacial structures. Our algorithm is based on the implementation of an anatomical and geometrical network adapted to the craniofacial structure. This network was constructed based on the anatomical knowledge of the 3D cephalometric (reference) points. The proposed algorithm was tested on five CBCT images. The proposed approach for the automatic 3D cephalometric identification was able to detect 21 points with a mean error of 2.32mm. In this pilot study, we propose an automated methodology for the identification of the 3D cephalometric (reference) points. A larger sample will be implemented in the future to assess the method validity and reliability. Copyright © 2018 CEO. Published by Elsevier Masson SAS. All rights reserved.
Automatic learning-based beam angle selection for thoracic IMRT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Amit, Guy; Marshall, Andrea; Purdie, Thomas G., E-mail: tom.purdie@rmp.uhn.ca
Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationallymore » efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.« less
Freyer, Marcus; Ale, Angelique; Schulz, Ralf B; Zientkowska, Marta; Ntziachristos, Vasilis; Englmeier, Karl-Hans
2010-01-01
The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.
Convolution neural-network-based detection of lung structures
NASA Astrophysics Data System (ADS)
Hasegawa, Akira; Lo, Shih-Chung B.; Freedman, Matthew T.; Mun, Seong K.
1994-05-01
Chest radiography is one of the most primary and widely used techniques in diagnostic imaging. Nowadays with the advent of digital radiology, the digital medical image processing techniques for digital chest radiographs have attracted considerable attention, and several studies on the computer-aided diagnosis (CADx) as well as on the conventional image processing techniques for chest radiographs have been reported. In the automatic diagnostic process for chest radiographs, it is important to outline the areas of the lungs, the heart, and the diaphragm. This is because the original chest radiograph is composed of important anatomic structures and, without knowing exact positions of the organs, the automatic diagnosis may result in unexpected detections. The automatic extraction of an anatomical structure from digital chest radiographs can be a useful tool for (1) the evaluation of heart size, (2) automatic detection of interstitial lung diseases, (3) automatic detection of lung nodules, and (4) data compression, etc. Based on the clearly defined boundaries of heart area, rib spaces, rib positions, and rib cage extracted, one should be able to use this information to facilitate the tasks of the CADx on chest radiographs. In this paper, we present an automatic scheme for the detection of lung field from chest radiographs by using a shift-invariant convolution neural network. A novel algorithm for smoothing boundaries of lungs is also presented.
Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng
2016-01-01
Accurate segmentation and classification of different anatomical structures of teeth from medical images plays an essential role in many clinical applications. Usually, the anatomical structures of teeth are manually labelled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing three dimensional (3D) information, and classify the tooth by employing unsupervised learning Pulse Coupled Neural Networks (PCNN) model. In order to evaluate the proposed method, the experiments are conducted on the different datasets of mandibular molars and the experimental results show that our method can achieve better accuracy and robustness compared to other four state of the art clustering methods.
Schubert, Jonathan T. W.; Badde, Stephanie; Röder, Brigitte
2017-01-01
Task demands modulate tactile localization in sighted humans, presumably through weight adjustments in the spatial integration of anatomical, skin-based, and external, posture-based information. In contrast, previous studies have suggested that congenitally blind humans, by default, refrain from automatic spatial integration and localize touch using only skin-based information. Here, sighted and congenitally blind participants localized tactile targets on the palm or back of one hand, while ignoring simultaneous tactile distractors at congruent or incongruent locations on the other hand. We probed the interplay of anatomical and external location codes for spatial congruency effects by varying hand posture: the palms either both faced down, or one faced down and one up. In the latter posture, externally congruent target and distractor locations were anatomically incongruent and vice versa. Target locations had to be reported either anatomically (“palm” or “back” of the hand), or externally (“up” or “down” in space). Under anatomical instructions, performance was more accurate for anatomically congruent than incongruent target-distractor pairs. In contrast, under external instructions, performance was more accurate for externally congruent than incongruent pairs. These modulations were evident in sighted and blind individuals. Notably, distractor effects were overall far smaller in blind than in sighted participants, despite comparable target-distractor identification performance. Thus, the absence of developmental vision seems to be associated with an increased ability to focus tactile attention towards a non-spatially defined target. Nevertheless, that blind individuals exhibited effects of hand posture and task instructions in their congruency effects suggests that, like the sighted, they automatically integrate anatomical and external information during tactile localization. Moreover, spatial integration in tactile processing is, thus, flexibly adapted by top-down information—here, task instruction—even in the absence of developmental vision. PMID:29228023
A computer-aided diagnosis system of nuclear cataract.
Li, Huiqi; Lim, Joo Hwee; Liu, Jiang; Mitchell, Paul; Tan, Ava Grace; Wang, Jie Jin; Wong, Tien Yin
2010-07-01
Cataracts are the leading cause of blindness worldwide, and nuclear cataract is the most common form of cataract. An algorithm for automatic diagnosis of nuclear cataract is investigated in this paper. Nuclear cataract is graded according to the severity of opacity using slit lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model. On the basis of the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine regression is employed for grade prediction. This is the first time that the nucleus region can be detected automatically in slit lamp images. The system is validated using clinical images and clinical ground truth on >5000 images. The success rate of structure detection is 95% and the average grading difference is 0.36 on a 5.0 scale. The automatic diagnosis system can improve the grading objectivity and potentially be used in clinics and population studies to save the workload of ophthalmologists.
Ross, James C; San José Estépar, Rail; Kindlmann, Gordon; Díaz, Alejandro; Westin, Carl-Fredrik; Silverman, Edwin K; Washko, George R
2010-01-01
We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as incomplete fissures (anatomical structures indicating lobe boundaries), advanced disease states, high body mass index (BMI), and low-dose scanning protocols. In contrast to other algorithms that leverage segmentations of auxiliary structures (esp. vessels and airways), we rely only upon image features indicating fissure locations. We employ a particle system that samples the image domain and provides a set of candidate fissure locations. We follow this stage with maximum a posteriori (MAP) estimation to eliminate poor candidates and then perform a post-processing operation to remove remaining noise particles. We then fit a thin plate spline (TPS) interpolating surface to the fissure particles to form the final lung lobe segmentation. Results indicate that our algorithm performs comparably to pulmonologist-generated lung lobe segmentations on a set of challenging cases.
Ross, James C.; Estépar, Raúl San José; Kindlmann, Gordon; Díaz, Alejandro; Westin, Carl-Fredrik; Silverman, Edwin K.; Washko, George R.
2011-01-01
We present a fully automatic lung lobe segmentation algorithm that is effective in high resolution computed tomography (CT) datasets in the presence of confounding factors such as incomplete fissures (anatomical structures indicating lobe boundaries), advanced disease states, high body mass index (BMI), and low-dose scanning protocols. In contrast to other algorithms that leverage segmentations of auxiliary structures (esp. vessels and airways), we rely only upon image features indicating fissure locations. We employ a particle system that samples the image domain and provides a set of candidate fissure locations. We follow this stage with maximum a posteriori (MAP) estimation to eliminate poor candidates and then perform a post-processing operation to remove remaining noise particles. We then fit a thin plate spline (TPS) interpolating surface to the fissure particles to form the final lung lobe segmentation. Results indicate that our algorithm performs comparably to pulmonologist-generated lung lobe segmentations on a set of challenging cases. PMID:20879396
Feature-Based Morphometry: Discovering Group-related Anatomical Patterns
Toews, Matthew; Wells, William; Collins, D. Louis; Arbel, Tal
2015-01-01
This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). PMID:19853047
Zheng, Yefeng; Barbu, Adrian; Georgescu, Bogdan; Scheuering, Michael; Comaniciu, Dorin
2008-11-01
We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be anatomically accurate, allow manual editing, and provide sufficient information to guide automatic detection and segmentation. Unlike previous work, we explicitly represent important landmarks (such as the valves and the ventricular septum cusps) among the control points of the model. The control points can be detected reliably to guide the automatic model fitting process. Using this model, we develop an efficient and robust approach for automatic heart chamber segmentation in 3-D CT volumes. We formulate the segmentation as a two-step learning problem: anatomical structure localization and boundary delineation. In both steps, we exploit the recent advances in learning discriminative models. A novel algorithm, marginal space learning (MSL), is introduced to solve the 9-D similarity transformation search problem for localizing the heart chambers. After determining the pose of the heart chambers, we estimate the 3-D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our system is the fastest with a speed of 4.0 s per volume (on a dual-core 3.2-GHz processor) for the automatic segmentation of all four chambers.
Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan
NASA Astrophysics Data System (ADS)
Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Rueckert, Daniel; Aljabar, Paul; Hajnal, Joseph V.; Hammers, Alexander
2009-02-01
A robust model for the automatic segmentation of human brain images into anatomically defined regions across the human lifespan would be highly desirable, but such structural segmentations of brain MRI are challenging due to age-related changes. We have developed a new method, based on established algorithms for automatic segmentation of young adults' brains. We used prior information from 30 anatomical atlases, which had been manually segmented into 83 anatomical structures. Target MRIs came from 80 subjects (~12 individuals/decade) from 20 to 90 years, with equal numbers of men, women; data from two different scanners (1.5T, 3T), using the IXI database. Each of the adult atlases was registered to each target MR image. By using additional information from segmentation into tissue classes (GM, WM and CSF) to initialise the warping based on label consistency similarity before feeding this into the previous normalised mutual information non-rigid registration, the registration became robust enough to accommodate atrophy and ventricular enlargement with age. The final segmentation was obtained by combination of the 30 propagated atlases using decision fusion. Kernel smoothing was used for modelling the structural volume changes with aging. Example linear correlation coefficients with age were, for lateral ventricular volume, rmale=0.76, rfemale=0.58 and, for hippocampal volume, rmale=-0.6, rfemale=-0.4 (allρ<0.01).
Intelligent navigation to improve obstetrical sonography.
Yeo, Lami; Romero, Roberto
2016-04-01
'Manual navigation' by the operator is the standard method used to obtain information from two-dimensional and volumetric sonography. Two-dimensional sonography is highly operator dependent and requires extensive training and expertise to assess fetal anatomy properly. Most of the sonographic examination time is devoted to acquisition of images, while 'retrieval' and display of diagnostic planes occurs rapidly (essentially instantaneously). In contrast, volumetric sonography has a rapid acquisition phase, but the retrieval and display of relevant diagnostic planes is often time-consuming, tedious and challenging. We propose the term 'intelligent navigation' to refer to a new method of interrogation of a volume dataset whereby identification and selection of key anatomical landmarks allow the system to: 1) generate a geometrical reconstruction of the organ of interest; and 2) automatically navigate, find, extract and display specific diagnostic planes. This is accomplished using operator-independent algorithms that are both predictable and adaptive. Virtual Intelligent Sonographer Assistance (VIS-Assistance®) is a tool that allows operator-independent sonographic navigation and exploration of the surrounding structures in previously identified diagnostic planes. The advantage of intelligent (over manual) navigation in volumetric sonography is the short time required for both acquisition and retrieval and display of diagnostic planes. Intelligent navigation technology automatically realigns the volume, and reorients and standardizes the anatomical position, so that the fetus and the diagnostic planes are consistently displayed in the same manner each time, regardless of the fetal position or the initial orientation. Automatic labeling of anatomical structures, subject orientation and each of the diagnostic planes is also possible. Intelligent navigation technology can operate on conventional computers, and is not dependent on specific ultrasound platforms or on the use of software to perform manual navigation of volume datasets. Diagnostic planes and VIS-Assistance videoclips can be transmitted by telemedicine so that expert consultants can evaluate the images to provide an opinion. The end result is a user-friendly, simple, fast and consistent method of obtaining sonographic images with decreased operator dependency. Intelligent navigation is one approach to improve obstetrical sonography. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
NASA Astrophysics Data System (ADS)
Tamez-Peña, José G.; Barbu-McInnis, Monica; Totterman, Saara
2006-03-01
Abnormal MR findings including cartilage defects, cartilage denuded areas, osteophytes, and bone marrow edema (BME) are used in staging and evaluating the degree of osteoarthritis (OA) in the knee. The locations of the abnormal findings have been correlated to the degree of pain and stiffness of the joint in the same location. The definition of the anatomic region in MR images is not always an objective task, due to the lack of clear anatomical features. This uncertainty causes variance in the location of the abnormality between readers and time points. Therefore, it is important to have a reproducible system to define the anatomic regions. This works present a computerized approach to define the different anatomic knee regions. The approach is based on an algorithm that uses unique features of the femur and its spatial relation in the extended knee. The femur features are found from three dimensional segmentation maps of the knee. From the segmentation maps, the algorithm automatically divides the femur cartilage into five anatomic regions: trochlea, medial weight bearing area, lateral weight bearing area, posterior medial femoral condyle, and posterior lateral femoral condyle. Furthermore, the algorithm automatically labels the medial and lateral tibia cartilage. The unsupervised definition of the knee regions allows a reproducible way to evaluate regional OA changes. This works will present the application of this automated algorithm for the regional analysis of the cartilage tissue.
Modeling and segmentation of intra-cochlear anatomy in conventional CT
NASA Astrophysics Data System (ADS)
Noble, Jack H.; Rutherford, Robert B.; Labadie, Robert F.; Majdani, Omid; Dawant, Benoit M.
2010-03-01
Cochlear implant surgery is a procedure performed to treat profound hearing loss. Since the cochlea is not visible in surgery, the physician uses anatomical landmarks to estimate the pose of the cochlea. Research has indicated that implanting the electrode in a particular cavity of the cochlea, the scala tympani, results in better hearing restoration. The success of the scala tympani implantation is largely dependent on the point of entry and angle of electrode insertion. Errors can occur due to the imprecise nature of landmark-based, manual navigation as well as inter-patient variations between scala tympani and the anatomical landmarks. In this work, we use point distribution models of the intra-cochlear anatomy to study the inter-patient variations between the cochlea and the typical anatomic landmarks, and we implement an active shape model technique to automatically localize intra-cochlear anatomy in conventional CT images, where intra-cochlear structures are not visible. This fully automatic segmentation could aid the surgeon to choose the point of entry and angle of approach to maximize the likelihood of scala tympani insertion, resulting in more substantial hearing restoration.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, H; Lee, Y; Ruschin, M
2015-06-15
Purpose: Automatically derive electron density of tissues using MR images and generate a pseudo-CT for MR-only treatment planning of brain tumours. Methods: 20 stereotactic radiosurgery (SRS) patients’ T1-weighted MR images and CT images were retrospectively acquired. First, a semi-automated tissue segmentation algorithm was developed to differentiate tissues with similar MR intensities and large differences in electron densities. The method started with approximately 12 slices of manually contoured spatial regions containing sinuses and airways, then air, bone, brain, cerebrospinal fluid (CSF) and eyes were automatically segmented using edge detection and anatomical information including location, shape, tissue uniformity and relative intensity distribution.more » Next, soft tissues - muscle and fat were segmented based on their relative intensity histogram. Finally, intensities of voxels in each segmented tissue were mapped into their electron density range to generate pseudo-CT by linearly fitting their relative intensity histograms. Co-registered CT was used as a ground truth. The bone segmentations of pseudo-CT were compared with those of co-registered CT obtained by using a 300HU threshold. The average distances between voxels on external edges of the skull of pseudo-CT and CT in three axial, coronal and sagittal slices with the largest width of skull were calculated. The mean absolute electron density (in Hounsfield unit) difference of voxels in each segmented tissues was calculated. Results: The average of distances between voxels on external skull from pseudo-CT and CT were 0.6±1.1mm (mean±1SD). The mean absolute electron density differences for bone, brain, CSF, muscle and fat are 78±114 HU, and 21±8 HU, 14±29 HU, 57±37 HU, and 31±63 HU, respectively. Conclusion: The semi-automated MR electron density mapping technique was developed using T1-weighted MR images. The generated pseudo-CT is comparable to that of CT in terms of anatomical position of tissues and similarity of electron density assignment. This method can allow MR-only treatment planning.« less
Automatic MRI 2D brain segmentation using graph searching technique.
Pedoia, Valentina; Binaghi, Elisabetta
2013-09-01
Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.
Automatic rectum limit detection by anatomical markers correlation.
Namías, R; D'Amato, J P; del Fresno, M; Vénere, M
2014-06-01
Several diseases take place at the end of the digestive system. Many of them can be diagnosed by means of different medical imaging modalities together with computer aided detection (CAD) systems. These CAD systems mainly focus on the complete segmentation of the digestive tube. However, the detection of limits between different sections could provide important information to these systems. In this paper we present an automatic method for detecting the rectum and sigmoid colon limit using a novel global curvature analysis over the centerline of the segmented digestive tube in different imaging modalities. The results are compared with the gold standard rectum upper limit through a validation scheme comprising two different anatomical markers: the third sacral vertebra and the average rectum length. Experimental results in both magnetic resonance imaging (MRI) and computed tomography colonography (CTC) acquisitions show the efficacy of the proposed strategy in automatic detection of rectum limits. The method is intended for application to the rectum segmentation in MRI for geometrical modeling and as contextual information source in virtual colonoscopies and CAD systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
Uozumi, Y; Nagamune, K
2013-01-01
The purpose of this study is to propose an automatic segmentation about each bone (the femur, the tibia, the patellar, and fibular) of the knee in MDCT image. The proposed method was applied for six patients (Age 33 ± 13, four males/tew females). The proposed method segmented the knee joint into each bone by using anatomical structure for the knee joint. The experiments calculate matching rate of the manual and the proposed method for evaluating it. As a result, The matching rate of the femur, the tibia, the patellar, and fibula were 95.84 ± 0.57%, 94.12 ± 1.01%, 94.49 ± 0.83%, 86.37 ± 4.28%, respectively. This study concluded that the proposed method is enough to segment the knee bones.
Toews, Matthew; Wells, William M.; Collins, Louis; Arbel, Tal
2013-01-01
This paper presents feature-based morphometry (FBM), a new, fully data-driven technique for identifying group-related differences in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between all subjects, FBM models images as a collage of distinct, localized image features which may not be present in all subjects. FBM thus explicitly accounts for the case where the same anatomical tissue cannot be reliably identified in all subjects due to disease or anatomical variability. A probabilistic model describes features in terms of their appearance, geometry, and relationship to sub-groups of a population, and is automatically learned from a set of subject images and group labels. Features identified indicate group-related anatomical structure that can potentially be used as disease biomarkers or as a basis for computer-aided diagnosis. Scale-invariant image features are used, which reflect generic, salient patterns in the image. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer’s (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and obtains an equal error classification rate of 0.78 on new subjects. PMID:20426102
Li, Jianyou; Tanaka, Hiroya
2018-01-01
Traditional splinting processes are skill dependent and irreversible, and patient satisfaction levels during rehabilitation are invariably lowered by the heavy structure and poor ventilation of splints. To overcome this drawback, use of the 3D-printing technology has been proposed in recent years, and there has been an increase in public awareness. However, application of 3D-printing technologies is limited by the low CAD proficiency of clinicians as well as unforeseen scan flaws within anatomic models.A programmable modeling tool has been employed to develop a semi-automatic design system for generating a printable splint model. The modeling process was divided into five stages, and detailed steps involved in construction of the proposed system as well as automatic thickness calculation, the lattice structure, and assembly method have been thoroughly described. The proposed approach allows clinicians to verify the state of the splint model at every stage, thereby facilitating adjustment of input content and/or other parameters to help solve possible modeling issues. A finite element analysis simulation was performed to evaluate the structural strength of generated models. A fit investigation was applied on fabricated splints and volunteers to assess the wearing experience. Manual modeling steps involved in complex splint designs have been programed into the proposed automatic system. Clinicians define the splinting region by drawing two curves, thereby obtaining the final model within minutes. The proposed system is capable of automatically patching up minor flaws within the limb model as well as calculating the thickness and lattice density of various splints. Large splints could be divided into three parts for simultaneous multiple printing. This study highlights the advantages, limitations, and possible strategies concerning application of programmable modeling tools in clinical processes, thereby aiding clinicians with lower CAD proficiencies to become adept with splint design process, thus improving the overall design efficiency of 3D-printed splints.
Nestor, Sean M; Gibson, Erin; Gao, Fu-Qiang; Kiss, Alex; Black, Sandra E
2013-02-01
Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer's disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects. However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity - particularly in pathologically heterogeneous samples. Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols. For the first time we test head-to-head the performance of five common hippocampal labeling protocols for multi-atlas based segmentation, using both the Sunnybrook Longitudinal Dementia Study and the entire Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) baseline and 24-month dataset. We based these atlas libraries on the protocols of (Haller et al., 1997; Killiany et al., 1993; Malykhin et al., 2007; Pantel et al., 2000; Pruessner et al., 2000), and a single operator performed all manual tracings to generate de facto "ground truth" labels. All methods distinguished between normal elders, mild cognitive impairment (MCI), and AD in the expected directions, and showed comparable correlations with measures of episodic memory performance. Only more inclusive protocols distinguished between stable MCI and MCI-to-AD converters, and had slightly better associations with episodic memory. Moreover, we demonstrate that protocols including more posterior anatomy and dorsal white matter compartments furnish the best voxel-overlap accuracies (Dice Similarity Coefficient=0.87-0.89), compared to expert manual tracings, and achieve the smallest sample sizes required to power clinical trials in MCI and AD. The greatest distribution of errors was localized to the caudal hippocampus and the alveus-fimbria compartment when these regions were excluded. The definition of the medial body did not significantly alter accuracy among more comprehensive protocols. Voxel-overlap accuracies between automatic and manual labels were lower for the more pathologically heterogeneous Sunnybrook study in comparison to the ADNI-1 sample. Finally, accuracy among protocols appears to significantly differ the most in AD subjects compared to MCI and normal elders. Together, these results suggest that selection of a candidate protocol for fully automatic multi-template based segmentation in AD can influence both segmentation accuracy when compared to expert manual labels and performance as a biomarker in MCI and AD. Copyright © 2012 Elsevier Inc. All rights reserved.
Nestor, Sean M.; Gibson, Erin; Gao, Fu-Qiang; Kiss, Alex; Black, Sandra E.
2012-01-01
Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer’s disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multitemplate fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects. However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity – particularly in pathologically heterogeneous samples. Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols. For the first time we test head-to-head the performance of five common hippocampal labeling protocols for multi-atlas based segmentation, using both the Sunnybrook Longitudinal Dementia Study and the entire Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) baseline and 24-month dataset. We based these atlas libraries on the protocols of (Haller et al., 1997; Killiany et al., 1993; Malykhin et al., 2007; Pantel et al., 2000; Pruessner et al., 2000), and a single operator performed all manual tracings to generate de facto “ground truth” labels. All methods distinguished between normal elders, mild cognitive impairment (MCI), and AD in the expected directions, and showed comparable correlations with measures of episodic memory performance. Only more inclusive protocols distinguished between stable MCI and MCI-to-AD converters, and had slightly better associations with episodic memory. Moreover, we demonstrate that protocols including more posterior anatomy and dorsal white matter compartments furnish the best voxel-overlap accuracies (Dice Similarity Coefficient = 0.87–0.89), compared to expert manual tracings, and achieve the smallest sample sizes required to power clinical trials in MCI and AD. The greatest distribution of errors was localized to the caudal hippocampus and alveus-fimbria compartment when these regions were excluded. The definition of the medial body did not significantly alter accuracy among more comprehensive protocols. Voxel-overlap accuracies between automatic and manual labels were lower for the more pathologically heterogeneous Sunnybrook study in comparison to the ADNI-1 sample. Finally, accuracy among protocols appears to significantly differ the most in AD subjects compared to MCI and normal elders. Together, these results suggest that selection of a candidate protocol for fully automatic multi-template based segmentation in AD can influence both segmentation accuracy when compared to expert manual labels and performance as a biomarker in MCI and AD. PMID:23142652
Automated selection of computed tomography display parameters using neural networks
NASA Astrophysics Data System (ADS)
Zhang, Di; Neu, Scott; Valentino, Daniel J.
2001-07-01
A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.
Automatic segmentation of pulmonary fissures in x-ray CT images using anatomic guidance
NASA Astrophysics Data System (ADS)
Ukil, Soumik; Sonka, Milan; Reinhardt, Joseph M.
2006-03-01
The pulmonary lobes are the five distinct anatomic divisions of the human lungs. The physical boundaries between the lobes are called the lobar fissures. Detection of lobar fissure positions in pulmonary X-ray CT images is of increasing interest for the early detection of pathologies, and also for the regional functional analysis of the lungs. We have developed a two-step automatic method for the accurate segmentation of the three pulmonary fissures. In the first step, an approximation of the actual fissure locations is made using a 3-D watershed transform on the distance map of the segmented vasculature. Information from the anatomically labeled human airway tree is used to guide the watershed segmentation. These approximate fissure boundaries are then used to define the region of interest (ROI) for a more exact 3-D graph search to locate the fissures. Within the ROI the fissures are enhanced by computing a ridgeness measure, and this is used as the cost function for the graph search. The fissures are detected as the optimal surface within the graph defined by the cost function, which is computed by transforming the problem to the problem of finding a minimum s-t cut on a derived graph. The accuracy of the lobar borders is assessed by comparing the automatic results to manually traced lobe segments. The mean distance error between manually traced and computer detected left oblique, right oblique and right horizontal fissures is 2.3 +/- 0.8 mm, 2.3 +/- 0.7 mm and 1.0 +/- 0.1 mm, respectively.
Torres, Luis G.; Kuntz, Alan; Gilbert, Hunter B.; Swaney, Philip J.; Hendrick, Richard J.; Webster, Robert J.; Alterovitz, Ron
2015-01-01
Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot’s shaft avoid sensitive anatomical structures (e.g., critical vessels and organs) while the surgeon teleoperates the robot’s tip. However, the robot’s unintuitive kinematics makes it difficult for a human user to manually ensure obstacle avoidance along the entire tentacle-like shape of the robot’s shaft. We present a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft. We achieve automatic collision avoidance by precomputing a roadmap of collision-free robot configurations based on a description of the anatomical obstacles, which are attainable via volumetric medical imaging. We also mitigate the effects of kinematic modeling error in reaching the goal positions by adjusting motions based on robot tip position sensing. We evaluate our motion planner on a teleoperated concentric tube robot and demonstrate its obstacle avoidance and accuracy in environments with tubular obstacles. PMID:26413381
Torres, Luis G; Kuntz, Alan; Gilbert, Hunter B; Swaney, Philip J; Hendrick, Richard J; Webster, Robert J; Alterovitz, Ron
2015-05-01
Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot's shaft avoid sensitive anatomical structures (e.g., critical vessels and organs) while the surgeon teleoperates the robot's tip. However, the robot's unintuitive kinematics makes it difficult for a human user to manually ensure obstacle avoidance along the entire tentacle-like shape of the robot's shaft. We present a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft. We achieve automatic collision avoidance by precomputing a roadmap of collision-free robot configurations based on a description of the anatomical obstacles, which are attainable via volumetric medical imaging. We also mitigate the effects of kinematic modeling error in reaching the goal positions by adjusting motions based on robot tip position sensing. We evaluate our motion planner on a teleoperated concentric tube robot and demonstrate its obstacle avoidance and accuracy in environments with tubular obstacles.
Carneiro, Gustavo; Georgescu, Bogdan; Good, Sara; Comaniciu, Dorin
2008-09-01
We propose a novel method for the automatic detection and measurement of fetal anatomical structures in ultrasound images. This problem offers a myriad of challenges, including: difficulty of modeling the appearance variations of the visual object of interest, robustness to speckle noise and signal dropout, and large search space of the detection procedure. Previous solutions typically rely on the explicit encoding of prior knowledge and formulation of the problem as a perceptual grouping task solved through clustering or variational approaches. These methods are constrained by the validity of the underlying assumptions and usually are not enough to capture the complex appearances of fetal anatomies. We propose a novel system for fast automatic detection and measurement of fetal anatomies that directly exploits a large database of expert annotated fetal anatomical structures in ultrasound images. Our method learns automatically to distinguish between the appearance of the object of interest and background by training a constrained probabilistic boosting tree classifier. This system is able to produce the automatic segmentation of several fetal anatomies using the same basic detection algorithm. We show results on fully automatic measurement of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL), humerus length (HL), and crown rump length (CRL). Notice that our approach is the first in the literature to deal with the HL and CRL measurements. Extensive experiments (with clinical validation) show that our system is, on average, close to the accuracy of experts in terms of segmentation and obstetric measurements. Finally, this system runs under half second on a standard dual-core PC computer.
NASA Astrophysics Data System (ADS)
Wojenski, Andrzej; Kasprowicz, Grzegorz; Pozniak, Krzysztof T.; Romaniuk, Ryszard
2013-10-01
The paper describes a concept of automatic firmware generation for reconfigurable measurement systems, which uses FPGA devices and measurement cards in FMC standard. Following sections are described in details: automatic HDL code generation for FPGA devices, automatic communication interfaces implementation, HDL drivers for measurement cards, automatic serial connection between multiple measurement backplane boards, automatic build of memory map (address space), automatic generated firmware management. Presented solutions are required in many advanced measurement systems, like Beam Position Monitors or GEM detectors. This work is a part of a wider project for automatic firmware generation and management of reconfigurable systems. Solutions presented in this paper are based on previous publication in SPIE.
A machine learning approach for classification of anatomical coverage in CT
NASA Astrophysics Data System (ADS)
Wang, Xiaoyong; Lo, Pechin; Ramakrishna, Bharath; Goldin, Johnathan; Brown, Matthew
2016-03-01
Automatic classification of anatomical coverage of medical images is critical for big data mining and as a pre-processing step to automatically trigger specific computer aided diagnosis systems. The traditional way to identify scans through DICOM headers has various limitations due to manual entry of series descriptions and non-standardized naming conventions. In this study, we present a machine learning approach where multiple binary classifiers were used to classify different anatomical coverages of CT scans. A one-vs-rest strategy was applied. For a given training set, a template scan was selected from the positive samples and all other scans were registered to it. Each registered scan was then evenly split into k × k × k non-overlapping blocks and for each block the mean intensity was computed. This resulted in a 1 × k3 feature vector for each scan. The feature vectors were then used to train a SVM based classifier. In this feasibility study, four classifiers were built to identify anatomic coverages of brain, chest, abdomen-pelvis, and chest-abdomen-pelvis CT scans. Each classifier was trained and tested using a set of 300 scans from different subjects, composed of 150 positive samples and 150 negative samples. Area under the ROC curve (AUC) of the testing set was measured to evaluate the performance in a two-fold cross validation setting. Our results showed good classification performance with an average AUC of 0.96.
Phenotype detection in morphological mutant mice using deformation features.
Roy, Sharmili; Liang, Xi; Kitamoto, Asanobu; Tamura, Masaru; Shiroishi, Toshihiko; Brown, Michael S
2013-01-01
Large-scale global efforts are underway to knockout each of the approximately 25,000 mouse genes and interpret their roles in shaping the mammalian embryo. Given the tremendous amount of data generated by imaging mutated prenatal mice, high-throughput image analysis systems are inevitable to characterize mammalian development and diseases. Current state-of-the-art computational systems offer only differential volumetric analysis of pre-defined anatomical structures between various gene-knockout mice strains. For subtle anatomical phenotypes, embryo phenotyping still relies on the laborious histological techniques that are clearly unsuitable in such big data environment. This paper presents a system that automatically detects known phenotypes and assists in discovering novel phenotypes in muCT images of mutant mice. Deformation features obtained from non-linear registration of mutant embryo to a normal consensus average image are extracted and analyzed to compute phenotypic and candidate phenotypic areas. The presented system is evaluated using C57BL/10 embryo images. All cases of ventricular septum defect and polydactyly, well-known to be present in this strain, are successfully detected. The system predicts potential phenotypic areas in the liver that are under active histological evaluation for possible phenotype of this mouse line.
Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Van de Velde, Joris, E-mail: joris.vandevelde@ugent.be; Department of Radiotherapy, Ghent University, Ghent; Wouters, Johan
Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. Thismore » procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result.« less
Magnetic resonance imaging for diagnosis of early Alzheimer's disease.
Colliot, O; Hamelin, L; Sarazin, M
2013-10-01
A major challenge for neuroimaging is to contribute to the early diagnosis of Alzheimer's disease (AD). In particular, magnetic resonance imaging (MRI) allows detecting different types of structural and functional abnormalities at an early stage of the disease. Anatomical MRI is the most widely used technique and provides local and global measures of atrophy. The recent diagnostic criteria of "mild cognitive impairment due to AD" include hippocampal atrophy, which is considered a marker of neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in the hippocampus and throughout the whole brain. Recent modalities such as diffusion-tensor imaging and resting-state functional MRI provide additional measures that could contribute to the early diagnosis but require further validation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.
Haptic feedback in OP:Sense - augmented reality in telemanipulated robotic surgery.
Beyl, T; Nicolai, P; Mönnich, H; Raczkowksy, J; Wörn, H
2012-01-01
In current research, haptic feedback in robot assisted interventions plays an important role. However most approaches to haptic feedback only regard the mapping of the current forces at the surgical instrument to the haptic input devices, whereas surgeons demand a combination of medical imaging and telemanipulated robotic setups. In this paper we describe how this feature is integrated in our robotic research platform OP:Sense. The proposed method allows the automatic transfer of segmented imaging data to the haptic renderer and therefore allows enriching the haptic feedback with virtual fixtures based on imaging data. Anatomical structures are extracted from pre-operative generated medical images or virtual walls are defined by the surgeon inside the imaging data. Combining real forces with virtual fixtures can guide the surgeon to the regions of interest as well as helps to prevent the risk of damage to critical structures inside the patient. We believe that the combination of medical imaging and telemanipulation is a crucial step for the next generation of MIRS-systems.
Automated construction of arterial and venous trees in retinal images.
Hu, Qiao; Abràmoff, Michael D; Garvin, Mona K
2015-10-01
While many approaches exist to segment retinal vessels in fundus photographs, only a limited number focus on the construction and disambiguation of arterial and venous trees. Previous approaches are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to large vessels. We propose a more global framework to generate arteriovenous trees in retinal images, given a vessel segmentation. In particular, our approach consists of three stages. The first stage is to generate an overconnected vessel network, named the vessel potential connectivity map (VPCM), consisting of vessel segments and the potential connectivity between them. The second stage is to disambiguate the VPCM into multiple anatomical trees, using a graph-based metaheuristic algorithm. The third stage is to classify these trees into arterial or venous (A/V) trees. We evaluated our approach with a ground truth built based on a public database, showing a pixel-wise classification accuracy of 88.15% using a manual vessel segmentation as input, and 86.11% using an automatic vessel segmentation as input.
NASA Astrophysics Data System (ADS)
Olory Agomma, R.; Vázquez, C.; Cresson, T.; De Guise, J.
2018-02-01
Most algorithms to detect and identify anatomical structures in medical images require either to be initialized close to the target structure, or to know that the structure is present in the image, or to be trained on a homogeneous database (e.g. all full body or all lower limbs). Detecting these structures when there is no guarantee that the structure is present in the image, or when the image database is heterogeneous (mixed configurations), is a challenge for automatic algorithms. In this work we compared two state-of-the-art machine learning techniques in order to determine which one is the most appropriate for predicting targets locations based on image patches. By knowing the position of thirteen landmarks points, labelled by an expert in EOS frontal radiography, we learn the displacement between salient points detected in the image and these thirteen landmarks. The learning step is carried out with a machine learning approach by exploring two methods: Convolutional Neural Network (CNN) and Random Forest (RF). The automatic detection of the thirteen landmarks points in a new image is then obtained by averaging the positions of each one of these thirteen landmarks estimated from all the salient points in the new image. We respectively obtain for CNN and RF, an average prediction error (both mean and standard deviation in mm) of 29 +/-18 and 30 +/- 21 for the thirteen landmarks points, indicating the approximate location of anatomical regions. On the other hand, the learning time is 9 days for CNN versus 80 minutes for RF. We provide a comparison of the results between the two machine learning approaches.
Object-oriented approach to the automatic segmentation of bones from pediatric hand radiographs
NASA Astrophysics Data System (ADS)
Shim, Hyeonjoon; Liu, Brent J.; Taira, Ricky K.; Hall, Theodore R.
1997-04-01
The purpose of this paper is to develop a robust and accurate method that automatically segments phalangeal and epiphyseal bones from digital pediatric hand radiographs exhibiting various stages of growth. The development of this system draws principles from object-oriented design, model- guided analysis, and feedback control. A system architecture called 'the object segmentation machine' was implemented incorporating these design philosophies. The system is aided by a knowledge base where all model contours and other information such as age, race, and sex, are stored. These models include object structure models, shape models, 1-D wrist profiles, and gray level histogram models. Shape analysis is performed first by using an arc-length orientation transform to break down a given contour into elementary segments and curves. Then an interpretation tree is used as an inference engine to map known model contour segments to data contour segments obtained from the transform. Spatial and anatomical relationships among contour segments work as constraints from shape model. These constraints aid in generating a list of candidate matches. The candidate match with the highest confidence is chosen to be the current intermediate result. Verification of intermediate results are perform by a feedback control loop.
Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images
NASA Astrophysics Data System (ADS)
Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.
2016-03-01
Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.
Deep residual networks for automatic segmentation of laparoscopic videos of the liver
NASA Astrophysics Data System (ADS)
Gibson, Eli; Robu, Maria R.; Thompson, Stephen; Edwards, P. Eddie; Schneider, Crispin; Gurusamy, Kurinchi; Davidson, Brian; Hawkes, David J.; Barratt, Dean C.; Clarkson, Matthew J.
2017-03-01
Motivation: For primary and metastatic liver cancer patients undergoing liver resection, a laparoscopic approach can reduce recovery times and morbidity while offering equivalent curative results; however, only about 10% of tumours reside in anatomical locations that are currently accessible for laparoscopic resection. Augmenting laparoscopic video with registered vascular anatomical models from pre-procedure imaging could support using laparoscopy in a wider population. Segmentation of liver tissue on laparoscopic video supports the robust registration of anatomical liver models by filtering out false anatomical correspondences between pre-procedure and intra-procedure images. In this paper, we present a convolutional neural network (CNN) approach to liver segmentation in laparoscopic liver procedure videos. Method: We defined a CNN architecture comprising fully-convolutional deep residual networks with multi-resolution loss functions. The CNN was trained in a leave-one-patient-out cross-validation on 2050 video frames from 6 liver resections and 7 laparoscopic staging procedures, and evaluated using the Dice score. Results: The CNN yielded segmentations with Dice scores >=0.95 for the majority of images; however, the inter-patient variability in median Dice score was substantial. Four failure modes were identified from low scoring segmentations: minimal visible liver tissue, inter-patient variability in liver appearance, automatic exposure correction, and pathological liver tissue that mimics non-liver tissue appearance. Conclusion: CNNs offer a feasible approach for accurately segmenting liver from other anatomy on laparoscopic video, but additional data or computational advances are necessary to address challenges due to the high inter-patient variability in liver appearance.
Puccio, Benjamin; Pooley, James P; Pellman, John S; Taverna, Elise C; Craddock, R Cameron
2016-10-25
Skull-stripping is the procedure of removing non-brain tissue from anatomical MRI data. This procedure can be useful for calculating brain volume and for improving the quality of other image processing steps. Developing new skull-stripping algorithms and evaluating their performance requires gold standard data from a variety of different scanners and acquisition methods. We complement existing repositories with manually corrected brain masks for 125 T1-weighted anatomical scans from the Nathan Kline Institute Enhanced Rockland Sample Neurofeedback Study. Skull-stripped images were obtained using a semi-automated procedure that involved skull-stripping the data using the brain extraction based on nonlocal segmentation technique (BEaST) software, and manually correcting the worst results. Corrected brain masks were added into the BEaST library and the procedure was repeated until acceptable brain masks were available for all images. In total, 85 of the skull-stripped images were hand-edited and 40 were deemed to not need editing. The results are brain masks for the 125 images along with a BEaST library for automatically skull-stripping other data. Skull-stripped anatomical images from the Neurofeedback sample are available for download from the Preprocessed Connectomes Project. The resulting brain masks can be used by researchers to improve preprocessing of the Neurofeedback data, as training and testing data for developing new skull-stripping algorithms, and for evaluating the impact on other aspects of MRI preprocessing. We have illustrated the utility of these data as a reference for comparing various automatic methods and evaluated the performance of the newly created library on independent data.
Hanaoka, Shouhei; Masutani, Yoshitaka; Nemoto, Mitsutaka; Nomura, Yukihiro; Yoshikawa, Takeharu; Hayashi, Naoto; Ohtomo, Kuni
2012-01-01
A method for categorizing landmark-local appearances extracted from computed tomography (CT) datasets is presented. Anatomical landmarks in the human body inevitably have inter-individual variations that cause difficulty in automatic landmark detection processes. The goal of this study is to categorize subjects (i.e., training datasets) according to local shape variations of such a landmark so that each subgroup has less shape variation and thus the machine learning of each landmark detector is much easier. The similarity between each subject pair is measured based on the non-rigid registration result between them. These similarities are used by the spectral clustering process. After the clustering, all training datasets in each cluster, as well as synthesized intermediate images calculated from all subject-pairs in the cluster, are used to train the corresponding subgroup detector. All of these trained detectors compose a detector ensemble to detect the target landmark. Evaluation with clinical CT datasets showed great improvement in the detection performance.
Automated planning of MRI scans of knee joints
NASA Astrophysics Data System (ADS)
Bystrov, Daniel; Pekar, Vladimir; Young, Stewart; Dries, Sebastian P. M.; Heese, Harald S.; van Muiswinkel, Arianne M.
2007-03-01
A novel and robust method for automatic scan planning of MRI examinations of knee joints is presented. Clinical knee examinations require acquisition of a 'scout' image, in which the operator manually specifies the scan volume orientations (off-centres, angulations, field-of-view) for the subsequent diagnostic scans. This planning task is time-consuming and requires skilled operators. The proposed automated planning system determines orientations for the diagnostic scan by using a set of anatomical landmarks derived by adapting active shape models of the femur, patella and tibia to the acquired scout images. The expert knowledge required to position scan geometries is learned from previous manually planned scans, allowing individual preferences to be taken into account. The system is able to automatically discriminate between left and right knees. This allows to use and merge training data from both left and right knees, and to automatically transform all learned scan geometries to the side for which a plan is required, providing a convenient integration of the automated scan planning system in the clinical routine. Assessment of the method on the basis of 88 images from 31 different individuals, exhibiting strong anatomical and positional variability demonstrates success, robustness and efficiency of all parts of the proposed approach, which thus has the potential to significantly improve the clinical workflow.
Definition and automatic anatomy recognition of lymph node zones in the pelvis on CT images
NASA Astrophysics Data System (ADS)
Liu, Yu; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Guo, Shuxu; Attor, Rosemary; Reinicke, Danica; Torigian, Drew A.
2016-03-01
Currently, unlike IALSC-defined thoracic lymph node zones, no explicitly provided definitions for lymph nodes in other body regions are available. Yet, definitions are critical for standardizing the recognition, delineation, quantification, and reporting of lymphadenopathy in other body regions. Continuing from our previous work in the thorax, this paper proposes a standardized definition of the grouping of pelvic lymph nodes into 10 zones. We subsequently employ our earlier Automatic Anatomy Recognition (AAR) framework designed for body-wide organ modeling, recognition, and delineation to actually implement these zonal definitions where the zones are treated as anatomic objects. First, all 10 zones and key anatomic organs used as anchors are manually delineated under expert supervision for constructing fuzzy anatomy models of the assembly of organs together with the zones. Then, optimal hierarchical arrangement of these objects is constructed for the purpose of achieving the best zonal recognition. For actual localization of the objects, two strategies are used -- optimal thresholded search for organs and one-shot method for the zones where the known relationship of the zones to key organs is exploited. Based on 50 computed tomography (CT) image data sets for the pelvic body region and an equal division into training and test subsets, automatic zonal localization within 1-3 voxels is achieved.
[Development of a Software for Automatically Generated Contours in Eclipse TPS].
Xie, Zhao; Hu, Jinyou; Zou, Lian; Zhang, Weisha; Zou, Yuxin; Luo, Kelin; Liu, Xiangxiang; Yu, Luxin
2015-03-01
The automatic generation of planning targets and auxiliary contours have achieved in Eclipse TPS 11.0. The scripting language autohotkey was used to develop a software for automatically generated contours in Eclipse TPS. This software is named Contour Auto Margin (CAM), which is composed of operational functions of contours, script generated visualization and script file operations. RESULTS Ten cases in different cancers have separately selected, in Eclipse TPS 11.0 scripts generated by the software could not only automatically generate contours but also do contour post-processing. For different cancers, there was no difference between automatically generated contours and manually created contours. The CAM is a user-friendly and powerful software, and can automatically generated contours fast in Eclipse TPS 11.0. With the help of CAM, it greatly save plan preparation time and improve working efficiency of radiation therapy physicists.
A feature-based developmental model of the infant brain in structural MRI.
Toews, Matthew; Wells, William M; Zöllei, Lilla
2012-01-01
In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days.
46 CFR 112.05-5 - Emergency power source.
Code of Federal Regulations, 2011 CFR
2011-10-01
... generator must be either a diesel engine or a gas turbine. [CGD 74-125A, 47 FR 15267, Apr. 8, 1982, as... power source (automatically connected storage battery or an automatically started generator) 36 hours.1... power source (automatically connected storage battery or an automatically started generator) 8 hours or...
46 CFR 112.05-5 - Emergency power source.
Code of Federal Regulations, 2010 CFR
2010-10-01
... generator must be either a diesel engine or a gas turbine. [CGD 74-125A, 47 FR 15267, Apr. 8, 1982, as... power source (automatically connected storage battery or an automatically started generator) 36 hours.1... power source (automatically connected storage battery or an automatically started generator) 8 hours or...
Automated kidney detection for 3D ultrasound using scan line searching
NASA Astrophysics Data System (ADS)
Noll, Matthias; Nadolny, Anne; Wesarg, Stefan
2016-04-01
Ultrasound (U/S) is a fast and non-expensive imaging modality that is used for the examination of various anatomical structures, e.g. the kidneys. One important task for automatic organ tracking or computer-aided diagnosis is the identification of the organ region. During this process the exact information about the transducer location and orientation is usually unavailable. This renders the implementation of such automatic methods exceedingly challenging. In this work we like to introduce a new automatic method for the detection of the kidney in 3D U/S images. This novel technique analyses the U/S image data along virtual scan lines. Here, characteristic texture changes when entering and leaving the symmetric tissue regions of the renal cortex are searched for. A subsequent feature accumulation along a second scan direction produces a 2D heat map of renal cortex candidates, from which the kidney location is extracted in two steps. First, the strongest candidate as well as its counterpart are extracted by heat map intensity ranking and renal cortex size analysis. This process exploits the heat map gap caused by the renal pelvis region. Substituting the renal pelvis detection with this combined cortex tissue feature increases the detection robustness. In contrast to model based methods that generate characteristic pattern matches, our method is simpler and therefore faster. An evaluation performed on 61 3D U/S data sets showed, that in 55 cases showing none or minor shadowing the kidney location could be correctly identified.
Noël, Geoffroy P J C; Connolly, Ciaran C
2016-01-01
The correct tracking and monitoring of anatomical specimens is not only imperative in any modern body donation programs but also in any universities for which teaching the next generation of health care professionals is the primary mission. This has long been an arduous process for anatomy institutions across the world, and the recent focus of new curricula on self-directed learning adds new stress on specimens which are used by students. The radio frequency identification (RFID) technology has been proposed as a very effective tracking system in healthcare considering that it enables automatic identification and data capture of multiple items at once. In this study, the feasibility of a low-cost RFID inventory system is assessed, from its design to the performance of commercially available RFID tags in a gross anatomy laboratory. The results show that ultrahigh frequency-based RFID tags successfully performed when attached to a collection of 112 plastinated and 280 wet dissected specimens. Comparison analysis of different tags reveals, however, that careful selection of RFID tags needs to be considered when wet specimens need to be tracked as preservation fluids can absorb radio waves energy. This study demonstrates that it is economically feasible to incorporate RFID technology to closely monitor the use of anatomical teaching specimens. The described RFID inventory system was not only able to preserve the integrity of the specimens being used by limiting handling and therefore human error but was also able to identify missing or misplaced specimens and to update their status. © 2015 American Association of Anatomists.
Prosdocimi, Francisco; Bittencourt, Daniela; da Silva, Felipe Rodrigues; Kirst, Matias; Motta, Paulo C.; Rech, Elibio L.
2011-01-01
Characterized by distinctive evolutionary adaptations, spiders provide a comprehensive system for evolutionary and developmental studies of anatomical organs, including silk and venom production. Here we performed cDNA sequencing using massively parallel sequencers (454 GS-FLX Titanium) to generate ∼80,000 reads from the spinning gland of Actinopus spp. (infraorder: Mygalomorphae) and Gasteracantha cancriformis (infraorder: Araneomorphae, Orbiculariae clade). Actinopus spp. retains primitive characteristics on web usage and presents a single undifferentiated spinning gland while the orbiculariae spiders have seven differentiated spinning glands and complex patterns of web usage. MIRA, Celera Assembler and CAP3 software were used to cluster NGS reads for each spider. CAP3 unigenes passed through a pipeline for automatic annotation, classification by biological function, and comparative transcriptomics. Genes related to spider silks were manually curated and analyzed. Although a single spidroin gene family was found in Actinopus spp., a vast repertoire of specialized spider silk proteins was encountered in orbiculariae. Astacin-like metalloproteases (meprin subfamily) were shown to be some of the most sampled unigenes and duplicated gene families in G. cancriformis since its evolutionary split from mygalomorphs. Our results confirm that the evolution of the molecular repertoire of silk proteins was accompanied by the (i) anatomical differentiation of spinning glands and (ii) behavioral complexification in the web usage. Finally, a phylogenetic tree was constructed to cluster most of the known spidroins in gene clades. This is the first large-scale, multi-organism transcriptome for spider spinning glands and a first step into a broad understanding of spider web systems biology and evolution. PMID:21738742
Freire, Paulo G L; Ferrari, Ricardo J
2016-06-01
Multiple sclerosis (MS) is a demyelinating autoimmune disease that attacks the central nervous system (CNS) and affects more than 2 million people worldwide. The segmentation of MS lesions in magnetic resonance imaging (MRI) is a very important task to assess how a patient is responding to treatment and how the disease is progressing. Computational approaches have been proposed over the years to segment MS lesions and reduce the amount of time spent on manual delineation and inter- and intra-rater variability and bias. However, fully-automatic segmentation of MS lesions still remains an open problem. In this work, we propose an iterative approach using Student's t mixture models and probabilistic anatomical atlases to automatically segment MS lesions in Fluid Attenuated Inversion Recovery (FLAIR) images. Our technique resembles a refinement approach by iteratively segmenting brain tissues into smaller classes until MS lesions are grouped as the most hyperintense one. To validate our technique we used 21 clinical images from the 2015 Longitudinal Multiple Sclerosis Lesion Segmentation Challenge dataset. Evaluation using Dice Similarity Coefficient (DSC), True Positive Ratio (TPR), False Positive Ratio (FPR), Volume Difference (VD) and Pearson's r coefficient shows that our technique has a good spatial and volumetric agreement with raters' manual delineations. Also, a comparison between our proposal and the state-of-the-art shows that our technique is comparable and, in some cases, better than some approaches, thus being a viable alternative for automatic MS lesion segmentation in MRI. Copyright © 2016 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hui, C; Suh, Y; Robertson, D
Purpose: To develop a novel algorithm to generate internal respiratory signals for sorting of four-dimensional (4D) computed tomography (CT) images. Methods: The proposed algorithm extracted multiple time resolved features as potential respiratory signals. These features were taken from the 4D CT images and its Fourier transformed space. Several low-frequency locations in the Fourier space and selected anatomical features from the images were used as potential respiratory signals. A clustering algorithm was then used to search for the group of appropriate potential respiratory signals. The chosen signals were then normalized and averaged to form the final internal respiratory signal. Performance ofmore » the algorithm was tested in 50 4D CT data sets and results were compared with external signals from the real-time position management (RPM) system. Results: In almost all cases, the proposed algorithm generated internal respiratory signals that visibly matched the external respiratory signals from the RPM system. On average, the end inspiration times calculated by the proposed algorithm were within 0.1 s of those given by the RPM system. Less than 3% of the calculated end inspiration times were more than one time frame away from those given by the RPM system. In 3 out of the 50 cases, the proposed algorithm generated internal respiratory signals that were significantly smoother than the RPM signals. In these cases, images sorted using the internal respiratory signals showed fewer artifacts in locations corresponding to the discrepancy in the internal and external respiratory signals. Conclusion: We developed a robust algorithm that generates internal respiratory signals from 4D CT images. In some cases, it even showed the potential to outperform the RPM system. The proposed algorithm is completely automatic and generally takes less than 2 min to process. It can be easily implemented into the clinic and can potentially replace the use of external surrogates.« less
Automatically Generated Vegetation Density Maps with LiDAR Survey for Orienteering Purpose
NASA Astrophysics Data System (ADS)
Petrovič, Dušan
2018-05-01
The focus of our research was to automatically generate the most adequate vegetation density maps for orienteering purpose. Application Karttapullatuin was used for automated generation of vegetation density maps, which requires LiDAR data to process an automatically generated map. A part of the orienteering map in the area of Kazlje-Tomaj was used to compare the graphical display of vegetation density. With different settings of parameters in the Karttapullautin application we changed the way how vegetation density of automatically generated map was presented, and tried to match it as much as possible with the orienteering map of Kazlje-Tomaj. Comparing more created maps of vegetation density the most suitable parameter settings to automatically generate maps on other areas were proposed, too.
The Role of Item Models in Automatic Item Generation
ERIC Educational Resources Information Center
Gierl, Mark J.; Lai, Hollis
2012-01-01
Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…
A Feature-based Developmental Model of the Infant Brain in Structural MRI
Toews, Matthew; Wells, William M.; Zöllei, Lilla
2014-01-01
In this paper, anatomical development is modeled as a collection of distinctive image patterns localized in space and time. A Bayesian posterior probability is defined over a random variable of subject age, conditioned on data in the form of scale-invariant image features. The model is automatically learned from a large set of images exhibiting significant variation, used to discover anatomical structure related to age and development, and fit to new images to predict age. The model is applied to a set of 230 infant structural MRIs of 92 subjects acquired at multiple sites over an age range of 8-590 days. Experiments demonstrate that the model can be used to identify age-related anatomical structure, and to predict the age of new subjects with an average error of 72 days. PMID:23286050
Techniques on semiautomatic segmentation using the Adobe Photoshop
NASA Astrophysics Data System (ADS)
Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae
2005-04-01
The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.
Automatic Text Structuring and Summarization.
ERIC Educational Resources Information Center
Salton, Gerard; And Others
1997-01-01
Discussion of the use of information retrieval techniques for automatic generation of semantic hypertext links focuses on automatic text summarization. Topics include World Wide Web links, text segmentation, and evaluation of text summarization by comparing automatically generated abstracts with manually prepared abstracts. (Author/LRW)
Automated construction of arterial and venous trees in retinal images
Hu, Qiao; Abràmoff, Michael D.; Garvin, Mona K.
2015-01-01
Abstract. While many approaches exist to segment retinal vessels in fundus photographs, only a limited number focus on the construction and disambiguation of arterial and venous trees. Previous approaches are local and/or greedy in nature, making them susceptible to errors or limiting their applicability to large vessels. We propose a more global framework to generate arteriovenous trees in retinal images, given a vessel segmentation. In particular, our approach consists of three stages. The first stage is to generate an overconnected vessel network, named the vessel potential connectivity map (VPCM), consisting of vessel segments and the potential connectivity between them. The second stage is to disambiguate the VPCM into multiple anatomical trees, using a graph-based metaheuristic algorithm. The third stage is to classify these trees into arterial or venous (A/V) trees. We evaluated our approach with a ground truth built based on a public database, showing a pixel-wise classification accuracy of 88.15% using a manual vessel segmentation as input, and 86.11% using an automatic vessel segmentation as input. PMID:26636114
Incomplete Hippocampal Inversion: A Comprehensive MRI Study of Over 2000 Subjects.
Cury, Claire; Toro, Roberto; Cohen, Fanny; Fischer, Clara; Mhaya, Amel; Samper-González, Jorge; Hasboun, Dominique; Mangin, Jean-François; Banaschewski, Tobias; Bokde, Arun L W; Bromberg, Uli; Buechel, Christian; Cattrell, Anna; Conrod, Patricia; Flor, Herta; Gallinat, Juergen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lemaitre, Hervé; Martinot, Jean-Luc; Nees, Frauke; Paillère Martinot, Marie-Laure; Orfanos, Dimitri P; Paus, Tomas; Poustka, Luise; Smolka, Michael N; Walter, Henrik; Whelan, Robert; Frouin, Vincent; Schumann, Gunter; Glaunès, Joan A; Colliot, Olivier
2015-01-01
The incomplete-hippocampal-inversion (IHI), also known as malrotation, is an atypical anatomical pattern of the hippocampus, which has been reported in healthy subjects in different studies. However, extensive characterization of IHI in a large sample has not yet been performed. Furthermore, it is unclear whether IHI are restricted to the medial-temporal lobe or are associated with more extensive anatomical changes. Here, we studied the characteristics of IHI in a community-based sample of 2008 subjects of the IMAGEN database and their association with extra-hippocampal anatomical variations. The presence of IHI was assessed on T1-weighted anatomical magnetic resonance imaging (MRI) using visual criteria. We assessed the association of IHI with other anatomical changes throughout the brain using automatic morphometry of cortical sulci. We found that IHI were much more frequent in the left hippocampus (left: 17%, right: 6%, χ(2)-test, p < 10(-28)). Compared to subjects without IHI, subjects with IHI displayed morphological changes in several sulci located mainly in the limbic lobe. Our results demonstrate that IHI are a common left-sided phenomenon in normal subjects and that they are associated with morphological changes outside the medial temporal lobe.
Incomplete Hippocampal Inversion: A Comprehensive MRI Study of Over 2000 Subjects
Cury, Claire; Toro, Roberto; Cohen, Fanny; Fischer, Clara; Mhaya, Amel; Samper-González, Jorge; Hasboun, Dominique; Mangin, Jean-François; Banaschewski, Tobias; Bokde, Arun L. W.; Bromberg, Uli; Buechel, Christian; Cattrell, Anna; Conrod, Patricia; Flor, Herta; Gallinat, Juergen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lemaitre, Hervé; Martinot, Jean-Luc; Nees, Frauke; Paillère Martinot, Marie-Laure; Orfanos, Dimitri P.; Paus, Tomas; Poustka, Luise; Smolka, Michael N.; Walter, Henrik; Whelan, Robert; Frouin, Vincent; Schumann, Gunter; Glaunès, Joan A.; Colliot, Olivier
2015-01-01
The incomplete-hippocampal-inversion (IHI), also known as malrotation, is an atypical anatomical pattern of the hippocampus, which has been reported in healthy subjects in different studies. However, extensive characterization of IHI in a large sample has not yet been performed. Furthermore, it is unclear whether IHI are restricted to the medial-temporal lobe or are associated with more extensive anatomical changes. Here, we studied the characteristics of IHI in a community-based sample of 2008 subjects of the IMAGEN database and their association with extra-hippocampal anatomical variations. The presence of IHI was assessed on T1-weighted anatomical magnetic resonance imaging (MRI) using visual criteria. We assessed the association of IHI with other anatomical changes throughout the brain using automatic morphometry of cortical sulci. We found that IHI were much more frequent in the left hippocampus (left: 17%, right: 6%, χ2−test, p < 10−28). Compared to subjects without IHI, subjects with IHI displayed morphological changes in several sulci located mainly in the limbic lobe. Our results demonstrate that IHI are a common left-sided phenomenon in normal subjects and that they are associated with morphological changes outside the medial temporal lobe. PMID:26733822
Approaches to the automatic generation and control of finite element meshes
NASA Technical Reports Server (NTRS)
Shephard, Mark S.
1987-01-01
The algorithmic approaches being taken to the development of finite element mesh generators capable of automatically discretizing general domains without the need for user intervention are discussed. It is demonstrated that because of the modeling demands placed on a automatic mesh generator, all the approaches taken to date produce unstructured meshes. Consideration is also given to both a priori and a posteriori mesh control devices for automatic mesh generators as well as their integration with geometric modeling and adaptive analysis procedures.
Indirect tissue electrophoresis: a new method for analyzing solid tissue protein.
Smith, A C
1988-01-01
1. The eye lens core (nucleus) has been a valuable source of molecular biologic information. 2. In these studies, lens nuclei are usually homogenized so that any protein information related to anatomical subdivisions, or layers, of the nucleus is lost. 3. The present report is of a new method, indirect tissue electrophoresis (ITE), which, when applied to fish lens nuclei, permitted (a) automatic correlation of protein information with anatomic layer, (b) production of large, clear electrophoretic patterns even from small tissue samples and (c) detection of more proteins than in liquid extracts of homogenized tissues. 4. ITE seems potentially applicable to a variety of solid tissues.
SEGMENTATION OF MITOCHONDRIA IN ELECTRON MICROSCOPY IMAGES USING ALGEBRAIC CURVES.
Seyedhosseini, Mojtaba; Ellisman, Mark H; Tasdizen, Tolga
2013-01-01
High-resolution microscopy techniques have been used to generate large volumes of data with enough details for understanding the complex structure of the nervous system. However, automatic techniques are required to segment cells and intracellular structures in these multi-terabyte datasets and make anatomical analysis possible on a large scale. We propose a fully automated method that exploits both shape information and regional statistics to segment irregularly shaped intracellular structures such as mitochondria in electron microscopy (EM) images. The main idea is to use algebraic curves to extract shape features together with texture features from image patches. Then, these powerful features are used to learn a random forest classifier, which can predict mitochondria locations precisely. Finally, the algebraic curves together with regional information are used to segment the mitochondria at the predicted locations. We demonstrate that our method outperforms the state-of-the-art algorithms in segmentation of mitochondria in EM images.
Automatic lung nodule matching for the follow-up in temporal chest CT scans
NASA Astrophysics Data System (ADS)
Hong, Helen; Lee, Jeongjin; Shin, Yeong Gil
2006-03-01
We propose a fast and robust registration method for matching lung nodules of temporal chest CT scans. Our method is composed of four stages. First, the lungs are extracted from chest CT scans by the automatic segmentation method. Second, the gross translational mismatch is corrected by the optimal cube registration. This initial registration does not require extracting any anatomical landmarks. Third, initial alignment is step by step refined by the iterative surface registration. To evaluate the distance measure between surface boundary points, a 3D distance map is generated by the narrow-band distance propagation, which drives fast and robust convergence to the optimal location. Fourth, nodule correspondences are established by the pairs with the smallest Euclidean distances. The results of pulmonary nodule alignment of twenty patients are reported on a per-center-of mass point basis using the average Euclidean distance (AED) error between corresponding nodules of initial and follow-up scans. The average AED error of twenty patients is significantly reduced to 4.7mm from 30.0mm by our registration. Experimental results show that our registration method aligns the lung nodules much faster than the conventional ones using a distance measure. Accurate and fast result of our method would be more useful for the radiologist's evaluation of pulmonary nodules on chest CT scans.
Yuan, Peng; Mai, Huaming; Li, Jianfu; Ho, Dennis Chun-Yu; Lai, Yingying; Liu, Siting; Kim, Daeseung; Xiong, Zixiang; Alfi, David M; Teichgraeber, John F; Gateno, Jaime; Xia, James J
2017-12-01
There are many proven problems associated with traditional surgical planning methods for orthognathic surgery. To address these problems, we developed a computer-aided surgical simulation (CASS) system, the AnatomicAligner, to plan orthognathic surgery following our streamlined clinical protocol. The system includes six modules: image segmentation and three-dimensional (3D) reconstruction, registration and reorientation of models to neutral head posture, 3D cephalometric analysis, virtual osteotomy, surgical simulation, and surgical splint generation. The accuracy of the system was validated in a stepwise fashion: first to evaluate the accuracy of AnatomicAligner using 30 sets of patient data, then to evaluate the fitting of splints generated by AnatomicAligner using 10 sets of patient data. The industrial gold standard system, Mimics, was used as the reference. When comparing the results of segmentation, virtual osteotomy and transformation achieved with AnatomicAligner to the ones achieved with Mimics, the absolute deviation between the two systems was clinically insignificant. The average surface deviation between the two models after 3D model reconstruction in AnatomicAligner and Mimics was 0.3 mm with a standard deviation (SD) of 0.03 mm. All the average surface deviations between the two models after virtual osteotomy and transformations were smaller than 0.01 mm with a SD of 0.01 mm. In addition, the fitting of splints generated by AnatomicAligner was at least as good as the ones generated by Mimics. We successfully developed a CASS system, the AnatomicAligner, for planning orthognathic surgery following the streamlined planning protocol. The system has been proven accurate. AnatomicAligner will soon be available freely to the boarder clinical and research communities.
Yuan, Peng; Mai, Huaming; Li, Jianfu; Ho, Dennis Chun-Yu; Lai, Yingying; Liu, Siting; Kim, Daeseung; Xiong, Zixiang; Alfi, David M.; Teichgraeber, John F.; Gateno, Jaime
2017-01-01
Purpose There are many proven problems associated with traditional surgical planning methods for orthognathic surgery. To address these problems, we developed a computer-aided surgical simulation (CASS) system, the AnatomicAligner, to plan orthognathic surgery following our streamlined clinical protocol. Methods The system includes six modules: image segmentation and three-dimensional (3D) reconstruction, registration and reorientation of models to neutral head posture, 3D cephalometric analysis, virtual osteotomy, surgical simulation, and surgical splint generation. The accuracy of the system was validated in a stepwise fashion: first to evaluate the accuracy of AnatomicAligner using 30 sets of patient data, then to evaluate the fitting of splints generated by AnatomicAligner using 10 sets of patient data. The industrial gold standard system, Mimics, was used as the reference. Result When comparing the results of segmentation, virtual osteotomy and transformation achieved with AnatomicAligner to the ones achieved with Mimics, the absolute deviation between the two systems was clinically insignificant. The average surface deviation between the two models after 3D model reconstruction in AnatomicAligner and Mimics was 0.3 mm with a standard deviation (SD) of 0.03 mm. All the average surface deviations between the two models after virtual osteotomy and transformations were smaller than 0.01 mm with a SD of 0.01 mm. In addition, the fitting of splints generated by AnatomicAligner was at least as good as the ones generated by Mimics. Conclusion We successfully developed a CASS system, the AnatomicAligner, for planning orthognathic surgery following the streamlined planning protocol. The system has been proven accurate. AnatomicAligner will soon be available freely to the boarder clinical and research communities. PMID:28432489
Automatic 3d Building Model Generations with Airborne LiDAR Data
NASA Astrophysics Data System (ADS)
Yastikli, N.; Cetin, Z.
2017-11-01
LiDAR systems become more and more popular because of the potential use for obtaining the point clouds of vegetation and man-made objects on the earth surface in an accurate and quick way. Nowadays, these airborne systems have been frequently used in wide range of applications such as DEM/DSM generation, topographic mapping, object extraction, vegetation mapping, 3 dimensional (3D) modelling and simulation, change detection, engineering works, revision of maps, coastal management and bathymetry. The 3D building model generation is the one of the most prominent applications of LiDAR system, which has the major importance for urban planning, illegal construction monitoring, 3D city modelling, environmental simulation, tourism, security, telecommunication and mobile navigation etc. The manual or semi-automatic 3D building model generation is costly and very time-consuming process for these applications. Thus, an approach for automatic 3D building model generation is needed in a simple and quick way for many studies which includes building modelling. In this study, automatic 3D building models generation is aimed with airborne LiDAR data. An approach is proposed for automatic 3D building models generation including the automatic point based classification of raw LiDAR point cloud. The proposed point based classification includes the hierarchical rules, for the automatic production of 3D building models. The detailed analyses for the parameters which used in hierarchical rules have been performed to improve classification results using different test areas identified in the study area. The proposed approach have been tested in the study area which has partly open areas, forest areas and many types of the buildings, in Zekeriyakoy, Istanbul using the TerraScan module of TerraSolid. The 3D building model was generated automatically using the results of the automatic point based classification. The obtained results of this research on study area verified that automatic 3D building models can be generated successfully using raw LiDAR point cloud data.
Granados, Alejandro; Vakharia, Vejay; Rodionov, Roman; Schweiger, Martin; Vos, Sjoerd B; O'Keeffe, Aidan G; Li, Kuo; Wu, Chengyuan; Miserocchi, Anna; McEvoy, Andrew W; Clarkson, Matthew J; Duncan, John S; Sparks, Rachel; Ourselin, Sébastien
2018-06-01
The accurate and automatic localisation of SEEG electrodes is crucial for determining the location of epileptic seizure onset. We propose an algorithm for the automatic segmentation of electrode bolts and contacts that accounts for electrode bending in relation to regional brain anatomy. Co-registered post-implantation CT, pre-implantation MRI, and brain parcellation images are used to create regions of interest to automatically segment bolts and contacts. Contact search strategy is based on the direction of the bolt with distance and angle constraints, in addition to post-processing steps that assign remaining contacts and predict contact position. We measured the accuracy of contact position, bolt angle, and anatomical region at the tip of the electrode in 23 post-SEEG cases comprising two different surgical approaches when placing a guiding stylet close to and far from target point. Local and global bending are computed when modelling electrodes as elastic rods. Our approach executed on average in 36.17 s with a sensitivity of 98.81% and a positive predictive value (PPV) of 95.01%. Compared to manual segmentation, the position of contacts had a mean absolute error of 0.38 mm and the mean bolt angle difference of [Formula: see text] resulted in a mean displacement error of 0.68 mm at the tip of the electrode. Anatomical regions at the tip of the electrode were in strong concordance with those selected manually by neurosurgeons, [Formula: see text], with average distance between regions of 0.82 mm when in disagreement. Our approach performed equally in two surgical approaches regardless of the amount of electrode bending. We present a method robust to electrode bending that can accurately segment contact positions and bolt orientation. The techniques presented in this paper will allow further characterisation of bending within different brain regions.
Applying Hierarchical Model Calibration to Automatically Generated Items.
ERIC Educational Resources Information Center
Williamson, David M.; Johnson, Matthew S.; Sinharay, Sandip; Bejar, Isaac I.
This study explored the application of hierarchical model calibration as a means of reducing, if not eliminating, the need for pretesting of automatically generated items from a common item model prior to operational use. Ultimately the successful development of automatic item generation (AIG) systems capable of producing items with highly similar…
Automatic Item Generation of Probability Word Problems
ERIC Educational Resources Information Center
Holling, Heinz; Bertling, Jonas P.; Zeuch, Nina
2009-01-01
Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…
46 CFR 112.05-5 - Emergency power source.
Code of Federal Regulations, 2013 CFR
2013-10-01
... with § 112.05-1(c). Table 112.05-5(a) Size of vessel and service Type of emergency power source or... power source (automatically connected storage battery or an automatically started generator) 36 hours.1... power source (automatically connected storage battery or an automatically started generator) 8 hours or...
46 CFR 112.05-5 - Emergency power source.
Code of Federal Regulations, 2012 CFR
2012-10-01
... with § 112.05-1(c). Table 112.05-5(a) Size of vessel and service Type of emergency power source or... power source (automatically connected storage battery or an automatically started generator) 36 hours.1... power source (automatically connected storage battery or an automatically started generator) 8 hours or...
46 CFR 112.05-5 - Emergency power source.
Code of Federal Regulations, 2014 CFR
2014-10-01
... with § 112.05-1(c). Table 112.05-5(a) Size of vessel and service Type of emergency power source or... power source (automatically connected storage battery or an automatically started generator) 36 hours.1... power source (automatically connected storage battery or an automatically started generator) 8 hours or...
Gap-free segmentation of vascular networks with automatic image processing pipeline.
Hsu, Chih-Yang; Ghaffari, Mahsa; Alaraj, Ali; Flannery, Michael; Zhou, Xiaohong Joe; Linninger, Andreas
2017-03-01
Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vascular trees. However, topological analysis of vascular trees require proper connectivity without gaps, loops or dangling segments. Proper tree connectivity is also important for high quality rendering of surface meshes for scientific visualization or 3D printing. We present a fully automated vessel enhancement pipeline with automated parameter settings for vessel enhancement of tree-like structures from customary imaging sources, including 3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and computed tomography angiography. The output of the filter pipeline is a vessel-enhanced image which is ideal for generating anatomical consistent network representations of the cerebral angioarchitecture for further topological or statistical analysis. The filter pipeline combined with computational modeling can potentially improve computer-aided diagnosis of cerebrovascular diseases by delivering biometrics and anatomy of the vasculature. It may serve as the first step in fully automatic epidemiological analysis of large clinical datasets. The automatic analysis would enable rigorous statistical comparison of biometrics in subject-specific vascular trees. The robust and accurate image segmentation using a validated filter pipeline would also eliminate operator dependency that has been observed in manual segmentation. Moreover, manual segmentation is time prohibitive given that vascular trees have more than thousands of segments and bifurcations so that interactive segmentation consumes excessive human resources. Subject-specific trees are a first step toward patient-specific hemodynamic simulations for assessing treatment outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.
Automatic Synthesis of Panoramic Radiographs from Dental Cone Beam Computed Tomography Data.
Luo, Ting; Shi, Changrong; Zhao, Xing; Zhao, Yunsong; Xu, Jinqiu
2016-01-01
In this paper, we propose an automatic method of synthesizing panoramic radiographs from dental cone beam computed tomography (CBCT) data for directly observing the whole dentition without the superimposition of other structures. This method consists of three major steps. First, the dental arch curve is generated from the maximum intensity projection (MIP) of 3D CBCT data. Then, based on this curve, the long axial curves of the upper and lower teeth are extracted to create a 3D panoramic curved surface describing the whole dentition. Finally, the panoramic radiograph is synthesized by developing this 3D surface. Both open-bite shaped and closed-bite shaped dental CBCT datasets were applied in this study, and the resulting images were analyzed to evaluate the effectiveness of this method. With the proposed method, a single-slice panoramic radiograph can clearly and completely show the whole dentition without the blur and superimposition of other dental structures. Moreover, thickened panoramic radiographs can also be synthesized with increased slice thickness to show more features, such as the mandibular nerve canal. One feature of the proposed method is that it is automatically performed without human intervention. Another feature of the proposed method is that it requires thinner panoramic radiographs to show the whole dentition than those produced by other existing methods, which contributes to the clarity of the anatomical structures, including the enamel, dentine and pulp. In addition, this method can rapidly process common dental CBCT data. The speed and image quality of this method make it an attractive option for observing the whole dentition in a clinical setting.
Gobée, O Paul; Jansma, Daniël; DeRuiter, Marco C
2011-10-01
The many synonyms for anatomical structures confuse medical students and complicate medical communication. Easily accessible translations would alleviate this problem. None of the presently available resources-Terminologia Anatomica (TA), digital terminologies such as the Foundational Model of Anatomy (FMA), and websites-are fully satisfactory to this aim. Internet technologies offer new possibilities to solve the problem. Several authors have called for an online TA. An online translation resource should be easily accessible, user-friendly, comprehensive, expandable, and its quality determinable. As first step towards this goal, we built a translation website that we named www.AnatomicalTerms.info, based on the database of the FMA. It translates between English, Latin, eponyms, and to a lesser extent other languages, and presently contains over 31,000 terms for 7,250 structures, covering 95% of TA. In addition, it automatically presents searches for images, documents and anatomical variations regarding the sought structure. Several terminological and conceptual issues were encountered in transferring data from TA and FMA into AnatomicalTerms.info, resultant from these resources' different set-ups (paper versus digital) and targets (machine versus human-user). To the best of our knowledge, AnatomicalTerms.info is unique in its combination of user-friendliness and comprehensiveness. As next step, wiki-like expandability will be added to enable open contribution of clinical synonyms and terms in different languages. Specific quality measures will be taken to strike a balance between open contribution and quality assurance. AnatomicalTerms.info's mechanism that "translates" terms to structures furthermore may enhance targeted searching by linking images, descriptions, and other anatomical resources to the structures. Copyright © 2011 Wiley-Liss, Inc.
A reusable anatomically segmented digital mannequin for public health communication.
Fujieda, Kaori; Okubo, Kosaku
2016-01-01
The ongoing development of world wide web technologies has facilitated a change in health communication, which has now become bi-directional and encompasses people with diverse backgrounds. To enable an even greater role for medical illustrations, a data set, BodyParts3D, has been generated and its data set can be used by anyone to create and exchange customised three-dimensional (3D) anatomical images. BP3D comprises more than 3000 3D object files created by segmenting a digital mannequin in accordance with anatomical naming conventions. This paper describes the methodologies and features used to generate an anatomically correct male mannequin.
Silverstein, Jonathan C; Dech, Fred; Kouchoukos, Philip L
2004-01-01
Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information promises to expand surgeons' abilities to interpret images and plan treatment.
Automatic Certification of Kalman Filters for Reliable Code Generation
NASA Technical Reports Server (NTRS)
Denney, Ewen; Fischer, Bernd; Schumann, Johann; Richardson, Julian
2005-01-01
AUTOFILTER is a tool for automatically deriving Kalman filter code from high-level declarative specifications of state estimation problems. It can generate code with a range of algorithmic characteristics and for several target platforms. The tool has been designed with reliability of the generated code in mind and is able to automatically certify that the code it generates is free from various error classes. Since documentation is an important part of software assurance, AUTOFILTER can also automatically generate various human-readable documents, containing both design and safety related information. We discuss how these features address software assurance standards such as DO-178B.
Robust automatic measurement of 3D scanned models for the human body fat estimation.
Giachetti, Andrea; Lovato, Christian; Piscitelli, Francesco; Milanese, Chiara; Zancanaro, Carlo
2015-03-01
In this paper, we present an automatic tool for estimating geometrical parameters from 3-D human scans independent on pose and robustly against the topological noise. It is based on an automatic segmentation of body parts exploiting curve skeleton processing and ad hoc heuristics able to remove problems due to different acquisition poses and body types. The software is able to locate body trunk and limbs, detect their directions, and compute parameters like volumes, areas, girths, and lengths. Experimental results demonstrate that measurements provided by our system on 3-D body scans of normal and overweight subjects acquired in different poses are highly correlated with the body fat estimates obtained on the same subjects with dual-energy X-rays absorptiometry (DXA) scanning. In particular, maximal lengths and girths, not requiring precise localization of anatomical landmarks, demonstrate a good correlation (up to 96%) with the body fat and trunk fat. Regression models based on our automatic measurements can be used to predict body fat values reasonably well.
A procedure for automating CFD simulations of an inlet-bleed problem
NASA Technical Reports Server (NTRS)
Chyu, Wei J.; Rimlinger, Mark J.; Shih, Tom I.-P.
1995-01-01
A procedure was developed to improve the turn-around time for computational fluid dynamics (CFD) simulations of an inlet-bleed problem involving oblique shock-wave/boundary-layer interactions on a flat plate with bleed into a plenum through one or more circular holes. This procedure is embodied in a preprocessor called AUTOMAT. With AUTOMAT, once data for the geometry and flow conditions have been specified (either interactively or via a namelist), it will automatically generate all input files needed to perform a three-dimensional Navier-Stokes simulation of the prescribed inlet-bleed problem by using the PEGASUS and OVERFLOW codes. The input files automatically generated by AUTOMAT include those for the grid system and those for the initial and boundary conditions. The grid systems automatically generated by AUTOMAT are multi-block structured grids of the overlapping type. Results obtained by using AUTOMAT are presented to illustrate its capability.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhukov, A. V.; Komarov, A. N.; Safronov, A. N.
The principles of central control of the power generating units of thermal power plants by automatic secondary frequency and active power overcurrent regulation systems, and the algorithms for interactions between automatic power control systems for the power production units in thermal power plants and centralized systems for automatic frequency and power regulation, are discussed. The order of switching the power generating units of thermal power plants over to control by a centralized system for automatic frequency and power regulation and by the Central Coordinating System for automatic frequency and power regulation is presented. The results of full-scale system tests ofmore » the control of power generating units of the Kirishskaya, Stavropol, and Perm GRES (State Regional Electric Power Plants) by the Central Coordinating System for automatic frequency and power regulation at the United Power System of Russia on September 23-25, 2008, are reported.« less
Lower limb estimation from sparse landmarks using an articulated shape model.
Zhang, Ju; Fernandez, Justin; Hislop-Jambrich, Jacqui; Besier, Thor F
2016-12-08
Rapid generation of lower limb musculoskeletal models is essential for clinically applicable patient-specific gait modeling. Estimation of muscle and joint contact forces requires accurate representation of bone geometry and pose, as well as their muscle attachment sites, which define muscle moment arms. Motion-capture is a routine part of gait assessment but contains relatively sparse geometric information. Standard methods for creating customized models from motion-capture data scale a reference model without considering natural shape variations. We present an articulated statistical shape model of the left lower limb with embedded anatomical landmarks and muscle attachment regions. This model is used in an automatic workflow, implemented in an easy-to-use software application, that robustly and accurately estimates realistic lower limb bone geometry, pose, and muscle attachment regions from seven commonly used motion-capture landmarks. Estimated bone models were validated on noise-free marker positions to have a lower (p=0.001) surface-to-surface root-mean-squared error of 4.28mm, compared to 5.22mm using standard isotropic scaling. Errors at a variety of anatomical landmarks were also lower (8.6mm versus 10.8mm, p=0.001). We improve upon standard lower limb model scaling methods with shape model-constrained realistic bone geometries, regional muscle attachment sites, and higher accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Lee, Joohwi; Kim, Sun Hyung; Oguz, Ipek; Styner, Martin
2016-03-01
The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the previous cortical thickness analysis pipeline.
NASA Astrophysics Data System (ADS)
Brion, Eliott; Richter, Christian; Macq, Benoit; Stützer, Kristin; Exner, Florian; Troost, Esther; Hölscher, Tobias; Bondar, Luiza
2017-03-01
External beam radiation therapy (EBRT) treats cancer by delivering daily fractions of radiation to a target volume. For prostate cancer, the target undergoes day-to-day variations in position, volume, and shape. For stereotactic photon and for proton EBRT, endorectal balloons (ERBs) can be used to limit variations. To date, patterns of non-rigid variations for patients with ERB have not been modeled. We extracted and modeled the patient-specific patterns of variations, using regularly acquired CT-images, non-rigid point cloud registration, and principal component analysis (PCA). For each patient, a non-rigid point-set registration method, called Coherent Point Drift, (CPD) was used to automatically generate landmark correspondences between all target shapes. To ensure accurate registrations, we tested and validated CPD by identifying parameter values leading to the smallest registration errors (surface matching error 0.13+/-0.09 mm). PCA demonstrated that 88+/-3.2% of the target motion could be explained using only 4 principal modes. The most dominant component of target motion is a squeezing and stretching in the anterior-posterior and superior-inferior directions. A PCA model of daily landmark displacements, generated using 6 to 10 CT-scans, could explain well the target motion for the CT-scans not included in the model (modeling error decreased from 1.83+/-0.8 mm for 6 CT-scans to 1.6+/-0.7 mm for 10 CT-scans). PCA modeling error was smaller than the naive approximation by the mean shape (approximation error 2.66+/-0.59 mm). Future work will investigate the use of the PCA-model to improve the accuracy of EBRT techniques that are highly susceptible to anatomical variations such as, proton therapy
NASA Astrophysics Data System (ADS)
Chaisaowong, Kraisorn; Jiang, Mingze; Faltin, Peter; Merhof, Dorit; Eisenhawer, Christian; Gube, Monika; Kraus, Thomas
2016-03-01
Pleural thickenings are caused by asbestos exposure and may evolve into malignant pleural mesothelioma. An early diagnosis plays a key role towards an early treatment and an increased survival rate. Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. A computer-assisted diagnosis system to automatically assess pleural thickenings has been developed, which includes not only a quantitative assessment with respect to size and location, but also enhances this information with an anatomical description, i.e. lung side (left, right), part of pleura (pars costalis, mediastinalis, diaphragmatica, spinalis), as well as vertical (upper, middle, lower) and horizontal (ventral, dorsal) position. For this purpose, a 3D anatomical model of the lung surface has been manually constructed as a 3D atlas. Three registration sub-steps including rigid, affine, and nonrigid registration align the input patient lung to the 3D anatomical atlas model of the lung surface. Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties. Through this added information, an enhancement to the existing computer-assisted diagnosis system is presented in order to assure a higher precision and reproducible assessment of pleural thickenings, aiming at the diagnosis of the pleural mesothelioma in its early stage.
ERIC Educational Resources Information Center
Lorié, William A.
2013-01-01
A reverse engineering approach to automatic item generation (AIG) was applied to a figure-based publicly released test item from the Organisation for Economic Cooperation and Development (OECD) Programme for International Student Assessment (PISA) mathematical literacy cognitive instrument as part of a proof of concept. The author created an item…
Irimia, Andrei; Goh, S.-Y. Matthew; Torgerson, Carinna M.; Stein, Nathan R.; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.
2013-01-01
Objective To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Methods Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. Results We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Conclusion Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. PMID:24011495
Irimia, Andrei; Goh, S-Y Matthew; Torgerson, Carinna M; Stein, Nathan R; Chambers, Micah C; Vespa, Paul M; Van Horn, John D
2013-10-01
To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. Published by Elsevier B.V.
Leblond, Guillaume; Gaitero, Luis; Moens, Noel M M; Zur Linden, Alex; James, Fiona M K; Monteith, Gabrielle J; Runciman, John
2017-11-01
Objectives Ventral atlantoaxial stabilization techniques are challenging surgical procedures in dogs. Available surgical guidelines are based upon subjective anatomical landmarks, and limited radiographic and computed tomographic data. The aims of this study were (1) to provide detailed anatomical descriptions of atlantoaxial optimal safe implantation corridors to generate objective recommendations for optimal implant placements and (2) to compare anatomical data obtained in non-affected Toy breed dogs, affected Toy breed dogs suffering from atlantoaxial instability and non-affected Beagle dogs. Methods Anatomical data were collected from a prospectively recruited population of 27 dogs using a previously validated method of optimal safe implantation corridor analysis using computed tomographic images. Results Optimal implant positions and three-dimensional numerical data were generated successfully in all cases. Anatomical landmarks could be used to generate objective definitions of optimal insertion points which were applicable across all three groups. Overall the geometrical distribution of all implant sites was similar in all three groups with a few exceptions. Clinical Significance This study provides extensive anatomical data available to facilitate surgical planning of implant placement for atlantoaxial stabilization. Our data suggest that non-affected Toy breed dogs and non-affected Beagle dogs constitute reasonable research models to study atlantoaxial stabilization constructs. Schattauer GmbH Stuttgart.
A strategy for automatically generating programs in the lucid programming language
NASA Technical Reports Server (NTRS)
Johnson, Sally C.
1987-01-01
A strategy for automatically generating and verifying simple computer programs is described. The programs are specified by a precondition and a postcondition in predicate calculus. The programs generated are in the Lucid programming language, a high-level, data-flow language known for its attractive mathematical properties and ease of program verification. The Lucid programming is described, and the automatic program generation strategy is described and applied to several example problems.
[Development of a Compared Software for Automatically Generated DVH in Eclipse TPS].
Xie, Zhao; Luo, Kelin; Zou, Lian; Hu, Jinyou
2016-03-01
This study is to automatically calculate the dose volume histogram(DVH) for the treatment plan, then to compare it with requirements of doctor's prescriptions. The scripting language Autohotkey and programming language C# were used to develop a compared software for automatically generated DVH in Eclipse TPS. This software is named Show Dose Volume Histogram (ShowDVH), which is composed of prescription documents generation, operation functions of DVH, software visualization and DVH compared report generation. Ten cases in different cancers have been separately selected, in Eclipse TPS 11.0 ShowDVH could not only automatically generate DVH reports but also accurately determine whether treatment plans meet the requirements of doctor’s prescriptions, then reports gave direction for setting optimization parameters of intensity modulated radiated therapy. The ShowDVH is an user-friendly and powerful software, and can automatically generated compared DVH reports fast in Eclipse TPS 11.0. With the help of ShowDVH, it greatly saves plan designing time and improves working efficiency of radiation therapy physicists.
Enhanced anatomical calibration in human movement analysis.
Donati, Marco; Camomilla, Valentina; Vannozzi, Giuseppe; Cappozzo, Aurelio
2007-07-01
The representation of human movement requires knowledge of both movement and morphology of bony segments. The determination of subject-specific morphology data and their registration with movement data is accomplished through an anatomical calibration procedure (calibrated anatomical systems technique: CAST). This paper describes a novel approach to this calibration (UP-CAST) which, as compared with normally used techniques, achieves better repeatability, a shorter application time, and can be effectively performed by non-skilled examiners. Instead of the manual location of prominent bony anatomical landmarks, the description of which is affected by subjective interpretation, a large number of unlabelled points is acquired over prominent parts of the subject's bone, using a wand fitted with markers. A digital model of a template-bone is then submitted to isomorphic deformation and re-orientation to optimally match the above-mentioned points. The locations of anatomical landmarks are automatically made available. The UP-CAST was validated considering the femur as a paradigmatic case. Intra- and inter-examiner repeatability of the identification of anatomical landmarks was assessed both in vivo, using average weight subjects, and on bare bones. Accuracy of the identification was assessed using the anatomical landmark locations manually located on bare bones as reference. The repeatability of this method was markedly higher than that reported in the literature and obtained using the conventional palpation (ranges: 0.9-7.6 mm and 13.4-17.9, respectively). Accuracy resulted, on average, in a maximal error of 11 mm. Results suggest that the principal source of variability resides in the discrepancy between subject's and template bone morphology and not in the inter-examiner differences. The UP-CAST anatomical calibration could be considered a promising alternative to conventional calibration contributing to a more repeatable 3D human movement analysis.
ERIC Educational Resources Information Center
Nowinski, Wieslaw L.; Thirunavuukarasuu, Arumugam; Ananthasubramaniam, Anand; Chua, Beng Choon; Qian, Guoyu; Nowinska, Natalia G.; Marchenko, Yevgen; Volkau, Ihar
2009-01-01
Preparation of tests and student's assessment by the instructor are time consuming. We address these two tasks in neuroanatomy education by employing a digital media application with a three-dimensional (3D), interactive, fully segmented, and labeled brain atlas. The anatomical and vascular models in the atlas are linked to "Terminologia…
Mental rotation and the motor system: embodiment head over heels.
Krüger, Markus; Amorim, Michel-Ange; Ebersbach, Mirjam
2014-01-01
We examined whether body parts attached to abstract stimuli automatically force embodiment in a mental rotation task. In Experiment 1, standard cube combinations reflecting a human pose were added with (1) body parts on anatomically possible locations, (2) body parts on anatomically impossible locations, (3) colored end cubes, and (4) simple end cubes. Participants (N=30) had to decide whether two simultaneously presented stimuli, rotated in the picture plane, were identical or not. They were fastest and made less errors in the possible-body condition, but were slowest and least accurate in the impossible-body condition. A second experiment (N=32) replicated the results and ruled out that the poor performance in the impossible-body condition was due to the specific stimulus material. The findings of both experiments suggest that body parts automatically trigger embodiment, even when it is counterproductive and dramatically impairs performance, as in the impossible-body condition. It can furthermore be concluded that body parts cannot be used flexibly for spatial orientation in mental rotation tasks, compared to colored end cubes. Thus, embodiment appears to be a strong and inflexible mechanism that may, under certain conditions, even impede performance. Copyright © 2013 Elsevier B.V. All rights reserved.
Automatic recognition of surface landmarks of anatomical structures of back and posture
NASA Astrophysics Data System (ADS)
Michoński, Jakub; Glinkowski, Wojciech; Witkowski, Marcin; Sitnik, Robert
2012-05-01
Faulty postures, scoliosis and sagittal plane deformities should be detected as early as possible to apply preventive and treatment measures against major clinical consequences. To support documentation of the severity of deformity and diminish x-ray exposures, several solutions utilizing analysis of back surface topography data were introduced. A novel approach to automatic recognition and localization of anatomical landmarks of the human back is presented that may provide more repeatable results and speed up the whole procedure. The algorithm was designed as a two-step process involving a statistical model built upon expert knowledge and analysis of three-dimensional back surface shape data. Voronoi diagram is used to connect mean geometric relations, which provide a first approximation of the positions, with surface curvature distribution, which further guides the recognition process and gives final locations of landmarks. Positions obtained using the developed algorithms are validated with respect to accuracy of manual landmark indication by experts. Preliminary validation proved that the landmarks were localized correctly, with accuracy depending mostly on the characteristics of a given structure. It was concluded that recognition should mainly take into account the shape of the back surface, putting as little emphasis on the statistical approximation as possible.
Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.
Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M
2016-01-01
Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well.
Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem
Wang, Jun Yi; Ngo, Michael M.; Hessl, David; Hagerman, Randi J.; Rivera, Susan M.
2016-01-01
Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer’s segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well. PMID:27213683
Automatic attention to emotional stimuli: neural correlates.
Carretié, Luis; Hinojosa, José A; Martín-Loeches, Manuel; Mercado, Francisco; Tapia, Manuel
2004-08-01
We investigated the capability of emotional and nonemotional visual stimulation to capture automatic attention, an aspect of the interaction between cognitive and emotional processes that has received scant attention from researchers. Event-related potentials were recorded from 37 subjects using a 60-electrode array, and were submitted to temporal and spatial principal component analyses to detect and quantify the main components, and to source localization software (LORETA) to determine their spatial origin. Stimuli capturing automatic attention were of three types: emotionally positive, emotionally negative, and nonemotional pictures. Results suggest that initially (P1: 105 msec after stimulus), automatic attention is captured by negative pictures, and not by positive or nonemotional ones. Later (P2: 180 msec), automatic attention remains captured by negative pictures, but also by positive ones. Finally (N2: 240 msec), attention is captured only by positive and nonemotional stimuli. Anatomically, this sequence is characterized by decreasing activation of the visual association cortex (VAC) and by the growing involvement, from dorsal to ventral areas, of the anterior cingulate cortex (ACC). Analyses suggest that the ACC and not the VAC is responsible for experimental effects described above. Intensity, latency, and location of neural activity related to automatic attention thus depend clearly on the stimulus emotional content and on its associated biological importance. Copyright 2004 Wiley-Liss, Inc.
Hirose, Tomoaki; Igami, Tsuyoshi; Koga, Kusuto; Hayashi, Yuichiro; Ebata, Tomoki; Yokoyama, Yukihiro; Sugawara, Gen; Mizuno, Takashi; Yamaguchi, Junpei; Mori, Kensaku; Nagino, Masato
2017-03-01
Fusion angiography using reconstructed multidetector-row computed tomography (MDCT) images, and cholangiography using reconstructed images from MDCT with a cholangiographic agent include an anatomical gap due to the different periods of MDCT scanning. To conquer such gaps, we attempted to develop a cholangiography procedure that automatically reconstructs a cholangiogram from portal-phase MDCT images. The automatically produced cholangiography procedure utilized an original software program that was developed by the Graduate School of Information Science, Nagoya University. This program structured 5 candidate biliary tracts, and automatically selected one as the candidate for cholangiography. The clinical value of the automatically produced cholangiography procedure was estimated based on a comparison with manually produced cholangiography. Automatically produced cholangiograms were reconstructed for 20 patients who underwent MDCT scanning before biliary drainage for distal biliary obstruction. The procedure showed the ability to extract the 5 main biliary branches and the 21 subsegmental biliary branches in 55 and 25 % of the cases, respectively. The extent of aberrant connections and aberrant extractions outside the biliary tract was acceptable. Among all of the cholangiograms, 5 were clinically applied with no correction, 8 were applied with modest improvements, and 3 produced a correct cholangiography before automatic selection. Although our procedure requires further improvement based on the analysis of additional patient data, it may represent an alternative to direct cholangiography in the future.
Fast left ventricle tracking in CMR images using localized anatomical affine optical flow
NASA Astrophysics Data System (ADS)
Queirós, Sandro; Vilaça, João. L.; Morais, Pedro; Fonseca, Jaime C.; D'hooge, Jan; Barbosa, Daniel
2015-03-01
In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 +/- 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction
Automatic transperineal ultrasound probe positioning based on CT scan for image guided radiotherapy
NASA Astrophysics Data System (ADS)
Camps, S. M.; Verhaegen, F.; Paiva Fonesca, G.; de With, P. H. N.; Fontanarosa, D.
2017-03-01
Image interpretation is crucial during ultrasound image acquisition. A skilled operator is typically needed to verify if the correct anatomical structures are all visualized and with sufficient quality. The need for this operator is one of the major reasons why presently ultrasound is not widely used in radiotherapy workflows. To solve this issue, we introduce an algorithm that uses anatomical information derived from a CT scan to automatically provide the operator with a patient-specific ultrasound probe setup. The first application we investigated, for its relevance to radiotherapy, is 4D transperineal ultrasound image acquisition for prostate cancer patients. As initial test, the algorithm was applied on a CIRS multi-modality pelvic phantom. Probe setups were calculated in order to allow visualization of the prostate and adjacent edges of bladder and rectum, as clinically required. Five of the proposed setups were reproduced using a precision robotic arm and ultrasound volumes were acquired. A gel-filled probe cover was used to ensure proper acoustic coupling, while taking into account possible tilted positions of the probe with respect to the flat phantom surface. Visual inspection of the acquired volumes revealed that clinical requirements were fulfilled. Preliminary quantitative evaluation was also performed. The mean absolute distance (MAD) was calculated between actual anatomical structure positions and positions predicted by the CT-based algorithm. This resulted in a MAD of (2.8±0.4) mm for prostate, (2.5±0.6) mm for bladder and (2.8±0.6) mm for rectum. These results show that no significant systematic errors due to e.g. probe misplacement were introduced.
An optimized video system for augmented reality in endodontics: a feasibility study.
Bruellmann, D D; Tjaden, H; Schwanecke, U; Barth, P
2013-03-01
We propose an augmented reality system for the reliable detection of root canals in video sequences based on a k-nearest neighbor color classification and introduce a simple geometric criterion for teeth. The new software was implemented using C++, Qt, and the image processing library OpenCV. Teeth are detected in video images to restrict the segmentation of the root canal orifices by using a k-nearest neighbor algorithm. The location of the root canal orifices were determined using Euclidean distance-based image segmentation. A set of 126 human teeth with known and verified locations of the root canal orifices was used for evaluation. The software detects root canals orifices for automatic classification of the teeth in video images and stores location and size of the found structures. Overall 287 of 305 root canals were correctly detected. The overall sensitivity was about 94 %. Classification accuracy for molars ranged from 65.0 to 81.2 % and from 85.7 to 96.7 % for premolars. The realized software shows that observations made in anatomical studies can be exploited to automate real-time detection of root canal orifices and tooth classification with a software system. Automatic storage of location, size, and orientation of the found structures with this software can be used for future anatomical studies. Thus, statistical tables with canal locations will be derived, which can improve anatomical knowledge of the teeth to alleviate root canal detection in the future. For this purpose the software is freely available at: http://www.dental-imaging.zahnmedizin.uni-mainz.de/.
Towards a Framework for Generating Tests to Satisfy Complex Code Coverage in Java Pathfinder
NASA Technical Reports Server (NTRS)
Staats, Matt
2009-01-01
We present work on a prototype tool based on the JavaPathfinder (JPF) model checker for automatically generating tests satisfying the MC/DC code coverage criterion. Using the Eclipse IDE, developers and testers can quickly instrument Java source code with JPF annotations covering all MC/DC coverage obligations, and JPF can then be used to automatically generate tests that satisfy these obligations. The prototype extension to JPF enables various tasks useful in automatic test generation to be performed, such as test suite reduction and execution of generated tests.
Development of an Automatic Differentiation Version of the FPX Rotor Code
NASA Technical Reports Server (NTRS)
Hu, Hong
1996-01-01
The ADIFOR2.0 automatic differentiator is applied to the FPX rotor code along with the grid generator GRGN3. The FPX is an eXtended Full-Potential CFD code for rotor calculations. The automatic differentiation version of the code is obtained, which provides both non-geometry and geometry sensitivity derivatives. The sensitivity derivatives via automatic differentiation are presented and compared with divided difference generated derivatives. The study shows that automatic differentiation method gives accurate derivative values in an efficient manner.
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
The functional therapeutic chemical classification system.
Croset, Samuel; Overington, John P; Rebholz-Schuhmann, Dietrich
2014-03-15
Drug repositioning is the discovery of new indications for compounds that have already been approved and used in a clinical setting. Recently, some computational approaches have been suggested to unveil new opportunities in a systematic fashion, by taking into consideration gene expression signatures or chemical features for instance. We present here a novel method based on knowledge integration using semantic technologies, to capture the functional role of approved chemical compounds. In order to computationally generate repositioning hypotheses, we used the Web Ontology Language to formally define the semantics of over 20 000 terms with axioms to correctly denote various modes of action (MoA). Based on an integration of public data, we have automatically assigned over a thousand of approved drugs into these MoA categories. The resulting new resource is called the Functional Therapeutic Chemical Classification System and was further evaluated against the content of the traditional Anatomical Therapeutic Chemical Classification System. We illustrate how the new classification can be used to generate drug repurposing hypotheses, using Alzheimers disease as a use-case. https://www.ebi.ac.uk/chembl/ftc; https://github.com/loopasam/ftc. croset@ebi.ac.uk Supplementary data are available at Bioinformatics online.
Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters
Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina
2011-01-01
Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation. PMID:22003741
Segmentation of nerve bundles and ganglia in spine MRI using particle filters.
Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina
2011-01-01
Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation.
Morphology-based three-dimensional segmentation of coronary artery tree from CTA scans
NASA Astrophysics Data System (ADS)
Banh, Diem Phuc T.; Kyprianou, Iacovos S.; Paquerault, Sophie; Myers, Kyle J.
2007-03-01
We developed an algorithm based on a rule-based threshold framework to segment the coronary arteries from angiographic computed tomography (CTA) data. Computerized segmentation of the coronary arteries is a challenging procedure due to the presence of diverse anatomical structures surrounding the heart on cardiac CTA data. The proposed algorithm incorporates various levels of image processing and organ information including region, connectivity and morphology operations. It consists of three successive stages. The first stage involves the extraction of the three-dimensional scaffold of the heart envelope. This stage is semiautomatic requiring a reader to review the CTA scans and manually select points along the heart envelope in slices. These points are further processed using a surface spline-fitting technique to automatically generate the heart envelope. The second stage consists of segmenting the left heart chambers and coronary arteries using grayscale threshold, size and connectivity criteria. This is followed by applying morphology operations to further detach the left and right coronary arteries from the aorta. In the final stage, the 3D vessel tree is reconstructed and labeled using an Isolated Connected Threshold technique. The algorithm was developed and tested on a patient coronary artery CTA that was graciously shared by the Department of Radiology of the Massachusetts General Hospital. The test showed that our method constantly segmented the vessels above 79% of the maximum gray-level and automatically extracted 55 of the 58 coronary segments that can be seen on the CTA scan by a reader. These results are an encouraging step toward our objective of generating high resolution models of the male and female heart that will be subsequently used as phantoms for medical imaging system optimization studies.
Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang
2016-01-01
Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543
Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang
2016-01-01
Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.
Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng
2017-04-01
Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing 3 dimensional (3D) information, and classify the tooth by employing unsupervised learning i.e., k-means++ method. In order to evaluate the proposed method, the experiments are conducted on the sufficient and extensive datasets of mandibular molars. The experimental results show that our method can achieve higher accuracy and robustness compared to other three clustering methods. Copyright © 2016 Elsevier Ltd. All rights reserved.
Sungjun Lim; Nowak, Michael R; Yoonsuck Choe
2016-08-01
We present a novel, parallelizable algorithm capable of automatically reconstructing and calculating anatomical statistics of cerebral vascular networks embedded in large volumes of Rat Nissl-stained data. In this paper, we report the results of our method using Rattus somatosensory cortical data acquired using Knife-Edge Scanning Microscopy. Our algorithm performs the reconstruction task with averaged precision, recall, and F2-score of 0.978, 0.892, and 0.902 respectively. Calculated anatomical statistics show some conformance to values previously reported. The results that can be obtained from our method are expected to help explicate the relationship between the structural organization of the microcirculation and normal (and abnormal) cerebral functioning.
ERIC Educational Resources Information Center
Arendasy, Martin; Sommer, Markus
2007-01-01
This article deals with the investigation of the psychometric quality and constructs validity of algebra word problems generated by means of a schema-based version of the automatic min-max approach. Based on review of the research literature in algebra word problem solving and automatic item generation this new approach is introduced as a…
NASA Technical Reports Server (NTRS)
Chan, William M.; Akien, Edwin (Technical Monitor)
2002-01-01
For many years, generation of overset grids for complex configurations has required the use of a number of different independently developed software utilities. Results created by each step were then visualized using a separate visualization tool before moving on to the next. A new software tool called OVERGRID was developed which allows the user to perform all the grid generation steps and visualization under one environment. OVERGRID provides grid diagnostic functions such as surface tangent and normal checks as well as grid manipulation functions such as extraction, extrapolation, concatenation, redistribution, smoothing, and projection. Moreover, it also contains hyperbolic surface and volume grid generation modules that are specifically suited for overset grid generation. It is the first time that such a unified interface existed for the creation of overset grids for complex geometries. New concepts on automatic overset surface grid generation around surface discontinuities will also be briefly presented. Special control curves on the surface such as intersection curves, sharp edges, open boundaries, are called seam curves. The seam curves are first automatically extracted from a multiple panel network description of the surface. Points where three or more seam curves meet are automatically identified and are called seam corners. Seam corner surface grids are automatically generated using a singular axis topology. Hyperbolic surface grids are then grown from the seam curves that are automatically trimmed away from the seam corners.
My Corporis Fabrica: an ontology-based tool for reasoning and querying on complex anatomical models
2014-01-01
Background Multiple models of anatomy have been developed independently and for different purposes. In particular, 3D graphical models are specially useful for visualizing the different organs composing the human body, while ontologies such as FMA (Foundational Model of Anatomy) are symbolic models that provide a unified formal description of anatomy. Despite its comprehensive content concerning the anatomical structures, the lack of formal descriptions of anatomical functions in FMA limits its usage in many applications. In addition, the absence of connection between 3D models and anatomical ontologies makes it difficult and time-consuming to set up and access to the anatomical content of complex 3D objects. Results First, we provide a new ontology of anatomy called My Corporis Fabrica (MyCF), which conforms to FMA but extends it by making explicit how anatomical structures are composed, how they contribute to functions, and also how they can be related to 3D complex objects. Second, we have equipped MyCF with automatic reasoning capabilities that enable model checking and complex queries answering. We illustrate the added-value of such a declarative approach for interactive simulation and visualization as well as for teaching applications. Conclusions The novel vision of ontologies that we have developed in this paper enables a declarative assembly of different models to obtain composed models guaranteed to be anatomically valid while capturing the complexity of human anatomy. The main interest of this approach is its declarativity that makes possible for domain experts to enrich the knowledge base at any moment through simple editors without having to change the algorithmic machinery. This provides MyCF software environment a flexibility to process and add semantics on purpose for various applications that incorporate not only symbolic information but also 3D geometric models representing anatomical entities as well as other symbolic information like the anatomical functions. PMID:24936286
White Matter Tract Segmentation as Multiple Linear Assignment Problems
Sharmin, Nusrat; Olivetti, Emanuele; Avesani, Paolo
2018-01-01
Diffusion magnetic resonance imaging (dMRI) allows to reconstruct the main pathways of axons within the white matter of the brain as a set of polylines, called streamlines. The set of streamlines of the whole brain is called the tractogram. Organizing tractograms into anatomically meaningful structures, called tracts, is known as the tract segmentation problem, with important applications to neurosurgical planning and tractometry. Automatic tract segmentation techniques can be unsupervised or supervised. A common criticism of unsupervised methods, like clustering, is that there is no guarantee to obtain anatomically meaningful tracts. In this work, we focus on supervised tract segmentation, which is driven by prior knowledge from anatomical atlases or from examples, i.e., segmented tracts from different subjects. We present a supervised tract segmentation method that segments a given tract of interest in the tractogram of a new subject using multiple examples as prior information. Our proposed tract segmentation method is based on the idea of streamline correspondence i.e., on finding corresponding streamlines across different tractograms. In the literature, streamline correspondence has been addressed with the nearest neighbor (NN) strategy. Differently, here we formulate the problem of streamline correspondence as a linear assignment problem (LAP), which is a cornerstone of combinatorial optimization. With respect to the NN, the LAP introduces a constraint of one-to-one correspondence between streamlines, that forces the correspondences to follow the local anatomical differences between the example and the target tract, neglected by the NN. In the proposed solution, we combined the Jonker-Volgenant algorithm (LAPJV) for solving the LAP together with an efficient way of computing the nearest neighbors of a streamline, which massively reduces the total amount of computations needed to segment a tract. Moreover, we propose a ranking strategy to merge correspondences coming from different examples. We validate the proposed method on tractograms generated from the human connectome project (HCP) dataset and compare the segmentations with the NN method and the ROI-based method. The results show that LAP-based segmentation is vastly more accurate than ROI-based segmentation and substantially more accurate than the NN strategy. We provide a Free/OpenSource implementation of the proposed method. PMID:29467600
White Matter Tract Segmentation as Multiple Linear Assignment Problems.
Sharmin, Nusrat; Olivetti, Emanuele; Avesani, Paolo
2017-01-01
Diffusion magnetic resonance imaging (dMRI) allows to reconstruct the main pathways of axons within the white matter of the brain as a set of polylines, called streamlines. The set of streamlines of the whole brain is called the tractogram. Organizing tractograms into anatomically meaningful structures, called tracts, is known as the tract segmentation problem, with important applications to neurosurgical planning and tractometry. Automatic tract segmentation techniques can be unsupervised or supervised. A common criticism of unsupervised methods, like clustering, is that there is no guarantee to obtain anatomically meaningful tracts. In this work, we focus on supervised tract segmentation, which is driven by prior knowledge from anatomical atlases or from examples, i.e., segmented tracts from different subjects. We present a supervised tract segmentation method that segments a given tract of interest in the tractogram of a new subject using multiple examples as prior information. Our proposed tract segmentation method is based on the idea of streamline correspondence i.e., on finding corresponding streamlines across different tractograms. In the literature, streamline correspondence has been addressed with the nearest neighbor (NN) strategy. Differently, here we formulate the problem of streamline correspondence as a linear assignment problem (LAP), which is a cornerstone of combinatorial optimization. With respect to the NN, the LAP introduces a constraint of one-to-one correspondence between streamlines, that forces the correspondences to follow the local anatomical differences between the example and the target tract, neglected by the NN. In the proposed solution, we combined the Jonker-Volgenant algorithm (LAPJV) for solving the LAP together with an efficient way of computing the nearest neighbors of a streamline, which massively reduces the total amount of computations needed to segment a tract. Moreover, we propose a ranking strategy to merge correspondences coming from different examples. We validate the proposed method on tractograms generated from the human connectome project (HCP) dataset and compare the segmentations with the NN method and the ROI-based method. The results show that LAP-based segmentation is vastly more accurate than ROI-based segmentation and substantially more accurate than the NN strategy. We provide a Free/OpenSource implementation of the proposed method.
Automatic Thesaurus Generation for an Electronic Community System.
ERIC Educational Resources Information Center
Chen, Hsinchun; And Others
1995-01-01
This research reports an algorithmic approach to the automatic generation of thesauri for electronic community systems. The techniques used include term filtering, automatic indexing, and cluster analysis. The Worm Community System, used by molecular biologists studying the nematode worm C. elegans, was used as the testbed for this research.…
Automatic Semantic Generation and Arabic Translation of Mathematical Expressions on the Web
ERIC Educational Resources Information Center
Doush, Iyad Abu; Al-Bdarneh, Sondos
2013-01-01
Automatic processing of mathematical information on the web imposes some difficulties. This paper presents a novel technique for automatic generation of mathematical equations semantic and Arabic translation on the web. The proposed system facilitates unambiguous representation of mathematical equations by correlating equations to their known…
Reproducing the internal and external anatomy of fossil bones: Two new automatic digital tools.
Profico, Antonio; Schlager, Stefan; Valoriani, Veronica; Buzi, Costantino; Melchionna, Marina; Veneziano, Alessio; Raia, Pasquale; Moggi-Cecchi, Jacopo; Manzi, Giorgio
2018-04-21
We present two new automatic tools, developed under the R environment, to reproduce the internal and external structures of bony elements. The first method, Computer-Aided Laser Scanner Emulator (CA-LSE), provides the reconstruction of the external portions of a 3D mesh by simulating the action of a laser scanner. The second method, Automatic Segmentation Tool for 3D objects (AST-3D), performs the digital reconstruction of anatomical cavities. We present the application of CA-LSE and AST-3D methods to different anatomical remains, highly variable in terms of shape, size and structure: a modern human skull, a malleus bone, and a Neanderthal deciduous tooth. Both methods are developed in the R environment and embedded in the packages "Arothron" and "Morpho," where both the codes and the data are fully available. The application of CA-LSE and AST-3D allows the isolation and manipulation of the internal and external components of the 3D virtual representation of complex bony elements. In particular, we present the output of the four case studies: a complete modern human endocast and the right maxillary sinus, the dental pulp of the Neanderthal tooth and the inner network of blood vessels of the malleus. Both methods demonstrated to be much faster, cheaper, and more accurate than other conventional approaches. The tools we presented are available as add-ons in existing software within the R platform. Because of ease of application, and unrestrained availability of the methods proposed, these tools can be widely used by paleoanthropologists, paleontologists and anatomists. © 2018 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Jin, Dakai; Guo, Junfeng; Dougherty, Timothy M.; Iyer, Krishna S.; Hoffman, Eric A.; Saha, Punam K.
2016-03-01
Pulmonary vascular dysfunction has been implicated in smoking-related susceptibility to emphysema. With the growing interest in characterizing arterial morphology for early evaluation of the vascular role in pulmonary diseases, there is an increasing need for the standardization of a framework for arterial morphological assessment at airway segmental levels. In this paper, we present an effective and robust semi-automatic framework to segment pulmonary arteries at different anatomic airway branches and measure their cross-sectional area (CSA). The method starts with user-specified endpoints of a target arterial segment through a custom-built graphical user interface. It then automatically detect the centerline joining the endpoints, determines the local structure orientation and computes the CSA along the centerline after filtering out the adjacent pulmonary structures, such as veins or airway walls. Several new techniques are presented, including collision-impact based cost function for centerline detection, radial sample-line based CSA computation, and outlier analysis of radial distance to subtract adjacent neighboring structures in the CSA measurement. The method was applied to repeat-scan pulmonary multirow detector CT (MDCT) images from ten healthy subjects (age: 21-48 Yrs, mean: 28.5 Yrs; 7 female) at functional residual capacity (FRC). The reproducibility of computed arterial CSA from four airway segmental regions in middle and lower lobes was analyzed. The overall repeat-scan intra-class correlation (ICC) of the computed CSA from all four airway regions in ten subjects was 96% with maximum ICC found at LB10 and RB4 regions.
An automatic system to detect and extract texts in medical images for de-identification
NASA Astrophysics Data System (ADS)
Zhu, Yingxuan; Singh, P. D.; Siddiqui, Khan; Gillam, Michael
2010-03-01
Recently, there is an increasing need to share medical images for research purpose. In order to respect and preserve patient privacy, most of the medical images are de-identified with protected health information (PHI) before research sharing. Since manual de-identification is time-consuming and tedious, so an automatic de-identification system is necessary and helpful for the doctors to remove text from medical images. A lot of papers have been written about algorithms of text detection and extraction, however, little has been applied to de-identification of medical images. Since the de-identification system is designed for end-users, it should be effective, accurate and fast. This paper proposes an automatic system to detect and extract text from medical images for de-identification purposes, while keeping the anatomic structures intact. First, considering the text have a remarkable contrast with the background, a region variance based algorithm is used to detect the text regions. In post processing, geometric constraints are applied to the detected text regions to eliminate over-segmentation, e.g., lines and anatomic structures. After that, a region based level set method is used to extract text from the detected text regions. A GUI for the prototype application of the text detection and extraction system is implemented, which shows that our method can detect most of the text in the images. Experimental results validate that our method can detect and extract text in medical images with a 99% recall rate. Future research of this system includes algorithm improvement, performance evaluation, and computation optimization.
Cavailloles, F; Bazin, J P; Capderou, A; Valette, H; Herbert, J L; Di Paola, R
1987-05-01
A method for automatic processing of cardiac first-pass radionuclide study is presented. This technique, factor analysis of dynamic structures (FADS) provides an automatic separation of anatomical structures according to their different temporal behaviour, even if they are superimposed. FADS has been applied to 76 studies. A description of factor patterns obtained in various pathological categories is presented. FADS provides easy diagnosis of shunts and tricuspid insufficiency. Quantitative information derived from the factors (cardiac output and mean transit time) were compared to those obtained by the region of interest method. Using FADS, a higher correlation with cardiac catheterization was found for cardiac output calculation. Thus compared to the ROI method, FADS presents obvious advantages: a good separation of overlapping cardiac chambers is obtained; this operator independant method provides more objective and reproducible results. A number of parameters of the cardio-pulmonary function can be assessed by first-pass radionuclide angiocardiography (RNA) [1,2]. Usually, they are calculated using time-activity curves (TAC) from regions of interest (ROI) drawn on the cardiac chambers and the lungs. This method has two main drawbacks: (1) the lack of inter and intra-observers reproducibility; (2) the problem of crosstalk which affects the evaluation of the cardio-pulmonary performance. The crosstalk on planar imaging is due to anatomical superimposition of the cardiac chambers and lungs. The activity measured in any ROI is the sum of the activity in several organs and 'decontamination' of the TAC cannot easily be performed using the ROI method [3]. Factor analysis of dynamic structures (FADS) [4,5] can solve the two problems mentioned above. It provides an automatic separation of anatomical structures according to their different temporal behaviour, even if they are superimposed. The resulting factors are estimates of the time evolution of the activity in each structure (underlying physiological components), and the associated factor images are estimates of the spatial distribution of each factor. The aim of this study was to assess the reliability of FADS in first pass RNA and compare the results to those obtained by the ROI method which is generally considered as the routine procedure.
van Dam, Peter M; Gordon, Jeffrey P; Laks, Michael M; Boyle, Noel G
2015-01-01
Non-invasive electrocardiographic imaging (ECGI) of the cardiac muscle can help the pre-procedure planning of the ablation of ventricular arrhythmias by reducing the time to localize the origin. Our non-invasive ECGI system, the cardiac isochrone positioning system (CIPS), requires non-intersecting meshes of the heart, lungs and torso. However, software to reconstruct the meshes of the heart, lungs and torso with the capability to check and prevent these intersections is currently lacking. Consequently the reconstruction of a patient specific model with realistic atrial and ventricular wall thickness and incorporating blood cavities, lungs and torso usually requires additional several days of manual work. Therefore new software was developed that checks and prevents any intersections, and thus enables the use of accurate reconstructed anatomical models within CIPS. In this preliminary study we investigated the accuracy of the created patient specific anatomical models from MRI or CT. During the manual segmentation of the MRI data the boundaries of the relevant tissues are determined. The resulting contour lines are used to automatically morph reference meshes of the heart, lungs or torso to match the boundaries of the morphed tissue. Five patients were included in the study; models of the heart, lungs and torso were reconstructed from standard cardiac MRI images. The accuracy was determined by computing the distance between the segmentation contours and the morphed meshes. The average accuracy of the reconstructed cardiac geometry was within 2mm with respect to the manual segmentation contours on the MRI images. Derived wall volumes and left ventricular wall thickness were within the range reported in literature. For each reconstructed heart model the anatomical heart axis was computed using the automatically determined anatomical landmarks of the left apex and the mitral valve. The accuracy of the reconstructed heart models was well within the accuracy of the used medical image data (pixel size <1.5mm). For the lungs and torso the number of triangles in the mesh was reduced, thus decreasing the accuracy of the reconstructed mesh. A novel software tool has been introduced, which is able to reconstruct accurate cardiac anatomical models from MRI or CT within only a few hours. This new anatomical reconstruction tool might reduce the modeling errors within the cardiac isochrone positioning system and thus enable the clinical application of CIPS to localize the PVC/VT focus to the ventricular myocardium from only the standard 12 lead ECG. Copyright © 2015 Elsevier Inc. All rights reserved.
Accurate airway centerline extraction based on topological thinning using graph-theoretic analysis.
Bian, Zijian; Tan, Wenjun; Yang, Jinzhu; Liu, Jiren; Zhao, Dazhe
2014-01-01
The quantitative analysis of the airway tree is of critical importance in the CT-based diagnosis and treatment of popular pulmonary diseases. The extraction of airway centerline is a precursor to identify airway hierarchical structure, measure geometrical parameters, and guide visualized detection. Traditional methods suffer from extra branches and circles due to incomplete segmentation results, which induce false analysis in applications. This paper proposed an automatic and robust centerline extraction method for airway tree. First, the centerline is located based on the topological thinning method; border voxels are deleted symmetrically to preserve topological and geometrical properties iteratively. Second, the structural information is generated using graph-theoretic analysis. Then inaccurate circles are removed with a distance weighting strategy, and extra branches are pruned according to clinical anatomic knowledge. The centerline region without false appendices is eventually determined after the described phases. Experimental results show that the proposed method identifies more than 96% branches and keep consistency across different cases and achieves superior circle-free structure and centrality.
Bergamino, Maurizio; Hamilton, David J; Castelletti, Lara; Barletta, Laura; Castellan, Lucio
2015-03-01
In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org. © The Author(s) 2013.
Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Achten, Eric; De Neve, Wilfried; Van Hoof, Tom
2015-12-23
The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers. Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial. For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733). Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.
Saxena, Vishal; Kim, Minwook; Keah, Niobra M.; Neuwirth, Alexander L.; Stoeckl, Brendan D.; Bickard, Kevin; Restle, David J.; Salowe, Rebecca; Wang, Margaret Ye; Steinberg, David R.
2016-01-01
Cartilage has a poor healing response, and few viable options exist for repair of extensive damage. Hyaluronic acid (HA) hydrogels seeded with mesenchymal stem cells (MSCs) polymerized through UV crosslinking can generate functional tissue, but this crosslinking is not compatible with indirect rapid prototyping utilizing opaque anatomic molds. Methacrylate-modified polymers can also be chemically crosslinked in a cytocompatible manner using ammonium persulfate (APS) and N,N,N′,N′-tetramethylethylenediamine (TEMED). The objectives of this study were to (1) compare APS/TEMED crosslinking with UV crosslinking in terms of functional maturation of MSC-seeded HA hydrogels; (2) generate an anatomic mold of a complex joint surface through rapid prototyping; and (3) grow anatomic MSC-seeded HA hydrogel constructs using this alternative crosslinking method. Juvenile bovine MSCs were suspended in methacrylated HA (MeHA) and crosslinked either through UV polymerization or chemically with APS/TEMED to generate cylindrical constructs. Minipig porcine femoral heads were imaged using microCT, and anatomic negative molds were generated by three-dimensional printing using fused deposition modeling. Molded HA constructs were produced using the APS/TEMED method. All constructs were cultured for up to 12 weeks in a chemically defined medium supplemented with TGF-β3 and characterized by mechanical testing, biochemical assays, and histologic analysis. Both UV- and APS/TEMED-polymerized constructs showed increasing mechanical properties and robust proteoglycan and collagen deposition over time. At 12 weeks, APS/TEMED-polymerized constructs had higher equilibrium and dynamic moduli than UV-polymerized constructs, with no differences in proteoglycan or collagen content. Molded HA constructs retained their hemispherical shape in culture and demonstrated increasing mechanical properties and proteoglycan and collagen deposition, especially at the edges compared to the center of these larger constructs. Immunohistochemistry showed abundant collagen type II staining and little collagen type I staining. APS/TEMED crosslinking can be used to produce MSC-seeded HA-based neocartilage and can be used in combination with rapid prototyping techniques to generate anatomic MSC-seeded HA constructs for use in filling large and anatomically complex chondral defects or for biologic joint replacement. PMID:26871863
78 FR 13213 - Regional Reliability Standard PRC-006-NPCC-1- Automatic Underfrequency Load Shedding
Federal Register 2010, 2011, 2012, 2013, 2014
2013-02-27
...; Order No. 775] Regional Reliability Standard PRC-006-NPCC-1--Automatic Underfrequency Load Shedding... transferred to the system upon loss of the facility.'' \\27\\ Compensatory load shedding is automatic shedding of load adequate to compensate for the loss of a generator due to the generator tripping early (i.e...
System for Automatic Generation of Examination Papers in Discrete Mathematics
ERIC Educational Resources Information Center
Fridenfalk, Mikael
2013-01-01
A system was developed for automatic generation of problems and solutions for examinations in a university distance course in discrete mathematics and tested in a pilot experiment involving 200 students. Considering the success of such systems in the past, particularly including automatic assessment, it should not take long before such systems are…
Progressive data transmission for anatomical landmark detection in a cloud.
Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D
2012-01-01
In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi
2017-02-01
We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.
Papadakis, Antonios E; Perisinakis, Kostas; Damilakis, John
2014-10-01
To study the effect of patient size, body region and modulation strength on tube current and image quality on CT examinations that use automatic tube current modulation (ATCM). Ten physical anthropomorphic phantoms that simulate an individual as neonate, 1-, 5-, 10-year-old and adult at various body habitus were employed. CT acquisition of head, neck, thorax and abdomen/pelvis was performed with ATCM activated at weak, average and strong modulation strength. The mean modulated mAs (mAsmod) values were recorded. Image noise was measured at selected anatomical sites. The mAsmod recorded for neonate compared to 10-year-old increased by 30 %, 14 %, 6 % and 53 % for head, neck, thorax and abdomen/pelvis, respectively, (P < 0.05). The mAsmod was lower than the preselected mAs with the exception of the 10-year-old phantom. In paediatric and adult phantoms, the mAsmod ranged from 44 and 53 for weak to 117 and 93 for strong modulation strength, respectively. At the same exposure parameters image noise increased with body size (P < 0.05). The ATCM system studied here may affect dose differently for different patient habitus. Dose may decrease for overweight adults but increase for children older than 5 years old. Care should be taken when implementing ATCM protocols to ensure that image quality is maintained. • ATCM efficiency is related to the size of the patient's body. • ATCM should be activated without caution in overweight adult individuals. • ATCM may increase radiation dose in children older than 5 years old. • ATCM efficiency depends on the protocol selected for a specific anatomical region. • Modulation strength may be appropriately tuned to enhance ATCM efficiency.
Efficient segmentation of 3D fluoroscopic datasets from mobile C-arm
NASA Astrophysics Data System (ADS)
Styner, Martin A.; Talib, Haydar; Singh, Digvijay; Nolte, Lutz-Peter
2004-05-01
The emerging mobile fluoroscopic 3D technology linked with a navigation system combines the advantages of CT-based and C-arm-based navigation. The intra-operative, automatic segmentation of 3D fluoroscopy datasets enables the combined visualization of surgical instruments and anatomical structures for enhanced planning, surgical eye-navigation and landmark digitization. We performed a thorough evaluation of several segmentation algorithms using a large set of data from different anatomical regions and man-made phantom objects. The analyzed segmentation methods include automatic thresholding, morphological operations, an adapted region growing method and an implicit 3D geodesic snake method. In regard to computational efficiency, all methods performed within acceptable limits on a standard Desktop PC (30sec-5min). In general, the best results were obtained with datasets from long bones, followed by extremities. The segmentations of spine, pelvis and shoulder datasets were generally of poorer quality. As expected, the threshold-based methods produced the worst results. The combined thresholding and morphological operations methods were considered appropriate for a smaller set of clean images. The region growing method performed generally much better in regard to computational efficiency and segmentation correctness, especially for datasets of joints, and lumbar and cervical spine regions. The less efficient implicit snake method was able to additionally remove wrongly segmented skin tissue regions. This study presents a step towards efficient intra-operative segmentation of 3D fluoroscopy datasets, but there is room for improvement. Next, we plan to study model-based approaches for datasets from the knee and hip joint region, which would be thenceforth applied to all anatomical regions in our continuing development of an ideal segmentation procedure for 3D fluoroscopic images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn
2016-07-15
Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less
Automatic Item Generation via Frame Semantics: Natural Language Generation of Math Word Problems.
ERIC Educational Resources Information Center
Deane, Paul; Sheehan, Kathleen
This paper is an exploration of the conceptual issues that have arisen in the course of building a natural language generation (NLG) system for automatic test item generation. While natural language processing techniques are applicable to general verbal items, mathematics word problems are particularly tractable targets for natural language…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jani, S; Low, D; Lamb, J
2015-06-15
Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments weremore » simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and automatically detected using 3D setup images of two imaging modalities across three commonly-treated anatomical sites.« less
ERIC Educational Resources Information Center
Kelley, Ann E.; Hernandez, Pepe J.; Schiltz, Craig A.
2006-01-01
Adaptive motor actions require prior knowledge of instrumental contingencies. With practice, these actions can become highly automatic in nature. However, the molecular and anatomical substrates mediating these related forms of learning are not understood. In the present study, we used in situ hybridization to measure the mRNA levels of two…
Automatic pose correction for image-guided nonhuman primate brain surgery planning
NASA Astrophysics Data System (ADS)
Ghafurian, Soheil; Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.
2016-03-01
Intracranial delivery of recombinant DNA and neurochemical analysis in nonhuman primate (NHP) requires precise targeting of various brain structures via imaging derived coordinates in stereotactic surgeries. To attain targeting precision, the surgical planning needs to be done on preoperative three dimensional (3D) CT and/or MR images, in which the animals head is fixed in a pose identical to the pose during the stereotactic surgery. The matching of the image to the pose in the stereotactic frame can be done manually by detecting key anatomical landmarks on the 3D MR and CT images such as ear canal and ear bar zero position. This is not only time intensive but also prone to error due to the varying initial poses in the images which affects both the landmark detection and rotation estimation. We have introduced a fast, reproducible, and semi-automatic method to detect the stereotactic coordinate system in the image and correct the pose. The method begins with a rigid registration of the subject images to an atlas and proceeds to detect the anatomical landmarks through a sequence of optimization, deformable and multimodal registration algorithms. The results showed similar precision (maximum difference of 1.71 in average in-plane rotation) to a manual pose correction.
Ozhinsky, Eugene; Vigneron, Daniel B; Nelson, Sarah J
2011-04-01
To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands. The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality. 3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality. The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases. Copyright © 2011 Wiley-Liss, Inc.
ERIC Educational Resources Information Center
Chen, Jian; Smith, Andrew D.; Khan, Majid A.; Sinning, Allan R.; Conway, Marianne L.; Cui, Dongmei
2017-01-01
Recent improvements in three-dimensional (3D) virtual modeling software allows anatomists to generate high-resolution, visually appealing, colored, anatomical 3D models from computed tomography (CT) images. In this study, high-resolution CT images of a cadaver were used to develop clinically relevant anatomic models including facial skull, nasal…
Ferrario, Damien; Grychtol, Bartłomiej; Adler, Andy; Solà, Josep; Böhm, Stephan H; Bodenstein, Marc
2012-11-01
Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the ability of EIT technology to reconstruct relevant impedance changes at their anatomical locations, provided that information about the thoracic boundary shape (and electrode positions) are used for reconstruction.
Active shape models incorporating isolated landmarks for medical image annotation
NASA Astrophysics Data System (ADS)
Norajitra, Tobias; Meinzer, Hans-Peter; Stieltjes, Bram; Maier-Hein, Klaus H.
2014-03-01
Apart from their robustness in anatomic surface segmentation, purely surface based 3D Active Shape Models lack the ability to automatically detect and annotate non-surface key points of interest. However, annotation of anatomic landmarks is desirable, as it yields additional anatomic and functional information. Moreover, landmark detection might help to further improve accuracy during ASM segmentation. We present an extension of surface-based 3D Active Shape Models incorporating isolated non-surface landmarks. Positions of isolated and surface landmarks are modeled conjoint within a point distribution model (PDM). Isolated landmark appearance is described by a set of haar-like features, supporting local landmark detection on the PDM estimates using a kNN-Classi er. Landmark detection was evaluated in a leave-one-out cross validation on a reference dataset comprising 45 CT volumes of the human liver after shape space projection. Depending on the anatomical landmark to be detected, our experiments have shown in about 1/4 up to more than 1/2 of all test cases a signi cant improvement in detection accuracy compared to the position estimates delivered by the PDM. Our results encourage further research with regard to the combination of shape priors and machine learning for landmark detection within the Active Shape Model Framework.
Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid
, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also
Automatic Structural Parcellation of Mouse Brain MRI Using Multi-Atlas Label Fusion
Ma, Da; Cardoso, Manuel J.; Modat, Marc; Powell, Nick; Wells, Jack; Holmes, Holly; Wiseman, Frances; Tybulewicz, Victor; Fisher, Elizabeth; Lythgoe, Mark F.; Ourselin, Sébastien
2014-01-01
Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework. PMID:24475148
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, X; Rossi, P; Jani, A
Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage.more » During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful tool for image-guided interventions in prostate-cancer diagnosis and treatment. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.« less
46 CFR 63.01-3 - Scope and applicability.
Code of Federal Regulations, 2010 CFR
2010-10-01
... Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING AUTOMATIC AUXILIARY... automatic auxiliary boilers, automatic heating boilers, automatic waste heat boilers, donkey boilers... control systems) used for the generation of steam and/or oxidation of ordinary waste materials and garbage...
46 CFR 63.01-3 - Scope and applicability.
Code of Federal Regulations, 2011 CFR
2011-10-01
... Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) MARINE ENGINEERING AUTOMATIC AUXILIARY... automatic auxiliary boilers, automatic heating boilers, automatic waste heat boilers, donkey boilers... control systems) used for the generation of steam and/or oxidation of ordinary waste materials and garbage...
A Model-Based Method for Content Validation of Automatically Generated Test Items
ERIC Educational Resources Information Center
Zhang, Xinxin; Gierl, Mark
2016-01-01
The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…
NASA Astrophysics Data System (ADS)
Leavens, Claudia; Vik, Torbjørn; Schulz, Heinrich; Allaire, Stéphane; Kim, John; Dawson, Laura; O'Sullivan, Brian; Breen, Stephen; Jaffray, David; Pekar, Vladimir
2008-03-01
Manual contouring of target volumes and organs at risk in radiation therapy is extremely time-consuming, in particular for treating the head-and-neck area, where a single patient treatment plan can take several hours to contour. As radiation treatment delivery moves towards adaptive treatment, the need for more efficient segmentation techniques will increase. We are developing a method for automatic model-based segmentation of the head and neck. This process can be broken down into three main steps: i) automatic landmark identification in the image dataset of interest, ii) automatic landmark-based initialization of deformable surface models to the patient image dataset, and iii) adaptation of the deformable models to the patient-specific anatomical boundaries of interest. In this paper, we focus on the validation of the first step of this method, quantifying the results of our automatic landmark identification method. We use an image atlas formed by applying thin-plate spline (TPS) interpolation to ten atlas datasets, using 27 manually identified landmarks in each atlas/training dataset. The principal variation modes returned by principal component analysis (PCA) of the landmark positions were used by an automatic registration algorithm, which sought the corresponding landmarks in the clinical dataset of interest using a controlled random search algorithm. Applying a run time of 60 seconds to the random search, a root mean square (rms) distance to the ground-truth landmark position of 9.5 +/- 0.6 mm was calculated for the identified landmarks. Automatic segmentation of the brain, mandible and brain stem, using the detected landmarks, is demonstrated.
Donati, Marco; Camomilla, Valentina; Vannozzi, Giuseppe; Cappozzo, Aurelio
2008-07-19
The quantitative description of joint mechanics during movement requires the reconstruction of the position and orientation of selected anatomical axes with respect to a laboratory reference frame. These anatomical axes are identified through an ad hoc anatomical calibration procedure and their position and orientation are reconstructed relative to bone-embedded frames normally derived from photogrammetric marker positions and used to describe movement. The repeatability of anatomical calibration, both within and between subjects, is crucial for kinematic and kinetic end results. This paper illustrates an anatomical calibration approach, which does not require anatomical landmark manual palpation, described in the literature to be prone to great indeterminacy. This approach allows for the estimate of subject-specific bone morphology and automatic anatomical frame identification. The experimental procedure consists of digitization through photogrammetry of superficial points selected over the areas of the bone covered with a thin layer of soft tissue. Information concerning the location of internal anatomical landmarks, such as a joint center obtained using a functional approach, may also be added. The data thus acquired are matched with the digital model of a deformable template bone. Consequently, the repeatability of pelvis, knee and hip joint angles is determined. Five volunteers, each of whom performed five walking trials, and six operators, with no specific knowledge of anatomy, participated in the study. Descriptive statistics analysis was performed during upright posture, showing a limited dispersion of all angles (less than 3 deg) except for hip and knee internal-external rotation (6 deg and 9 deg, respectively). During level walking, the ratio of inter-operator and inter-trial error and an absolute subject-specific repeatability were assessed. For pelvic and hip angles, and knee flexion-extension the inter-operator error was equal to the inter-trial error-the absolute error ranging from 0.1 deg to 0.9 deg. Knee internal-external rotation and ab-adduction showed, on average, inter-operator errors, which were 8% and 28% greater than the relevant inter-trial errors, respectively. The absolute error was in the range 0.9-2.9 deg.
Development of an Automatic Grid Generator for Multi-Element High-Lift Wings
NASA Technical Reports Server (NTRS)
Eberhardt, Scott; Wibowo, Pratomo; Tu, Eugene
1996-01-01
The procedure to generate the grid around a complex wing configuration is presented in this report. The automatic grid generation utilizes the Modified Advancing Front Method as a predictor and an elliptic scheme as a corrector. The scheme will advance the surface grid one cell outward and the newly obtained grid is corrected using the Laplace equation. The predictor-corrector step ensures that the grid produced will be smooth for every configuration. The predictor-corrector scheme is extended for a complex wing configuration. A new technique is developed to deal with the grid generation in the wing-gaps and on the flaps. It will create the grids that fill the gap on the wing surface and the gap created by the flaps. The scheme recognizes these configurations automatically so that minimal user input is required. By utilizing an appropriate sequence in advancing the grid points on a wing surface, the automatic grid generation for complex wing configurations is achieved.
Knowledge Base for Automatic Generation of Online IMS LD Compliant Course Structures
ERIC Educational Resources Information Center
Pacurar, Ecaterina Giacomini; Trigano, Philippe; Alupoaie, Sorin
2006-01-01
Our article presents a pedagogical scenarios-based web application that allows the automatic generation and development of pedagogical websites. These pedagogical scenarios are represented in the IMS Learning Design standard. Our application is a web portal helping teachers to dynamically generate web course structures, to edit pedagogical content…
26 CFR 26.6081-1 - Automatic extension of time for filing generation-skipping transfer tax returns.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 26 Internal Revenue 14 2011-04-01 2010-04-01 true Automatic extension of time for filing generation-skipping transfer tax returns. 26.6081-1 Section 26.6081-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) ESTATE AND GIFT TAXES GENERATION-SKIPPING TRANSFER TAX...
26 CFR 26.6081-1 - Automatic extension of time for filing generation-skipping transfer tax returns.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 26 Internal Revenue 14 2010-04-01 2010-04-01 false Automatic extension of time for filing generation-skipping transfer tax returns. 26.6081-1 Section 26.6081-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) ESTATE AND GIFT TAXES GENERATION-SKIPPING TRANSFER TAX...
26 CFR 26.6081-1 - Automatic extension of time for filing generation-skipping transfer tax returns.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 14 2013-04-01 2013-04-01 false Automatic extension of time for filing generation-skipping transfer tax returns. 26.6081-1 Section 26.6081-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) ESTATE AND GIFT TAXES GENERATION-SKIPPING TRANSFER TAX...
26 CFR 26.6081-1 - Automatic extension of time for filing generation-skipping transfer tax returns.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 26 Internal Revenue 14 2014-04-01 2013-04-01 true Automatic extension of time for filing generation-skipping transfer tax returns. 26.6081-1 Section 26.6081-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) ESTATE AND GIFT TAXES GENERATION-SKIPPING TRANSFER TAX...
26 CFR 26.6081-1 - Automatic extension of time for filing generation-skipping transfer tax returns.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 14 2012-04-01 2012-04-01 false Automatic extension of time for filing generation-skipping transfer tax returns. 26.6081-1 Section 26.6081-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) ESTATE AND GIFT TAXES GENERATION-SKIPPING TRANSFER TAX...
Exploring the anatomical encoding of voice with a mathematical model of the vocal system.
Assaneo, M Florencia; Sitt, Jacobo; Varoquaux, Gael; Sigman, Mariano; Cohen, Laurent; Trevisan, Marcos A
2016-11-01
The faculty of language depends on the interplay between the production and perception of speech sounds. A relevant open question is whether the dimensions that organize voice perception in the brain are acoustical or depend on properties of the vocal system that produced it. One of the main empirical difficulties in answering this question is to generate sounds that vary along a continuum according to the anatomical properties the vocal apparatus that produced them. Here we use a mathematical model that offers the unique possibility of synthesizing vocal sounds by controlling a small set of anatomically based parameters. In a first stage the quality of the synthetic voice was evaluated. Using specific time traces for sub-glottal pressure and tension of the vocal folds, the synthetic voices generated perceptual responses, which are indistinguishable from those of real speech. The synthesizer was then used to investigate how the auditory cortex responds to the perception of voice depending on the anatomy of the vocal apparatus. Our fMRI results show that sounds are perceived as human vocalizations when produced by a vocal system that follows a simple relationship between the size of the vocal folds and the vocal tract. We found that these anatomical parameters encode the perceptual vocal identity (male, female, child) and show that the brain areas that respond to human speech also encode vocal identity. On the basis of these results, we propose that this low-dimensional model of the vocal system is capable of generating realistic voices and represents a novel tool to explore the voice perception with a precise control of the anatomical variables that generate speech. Furthermore, the model provides an explanation of how auditory cortices encode voices in terms of the anatomical parameters of the vocal system. Copyright © 2016 Elsevier Inc. All rights reserved.
Using 3D modeling techniques to enhance teaching of difficult anatomical concepts
Pujol, Sonia; Baldwin, Michael; Nassiri, Joshua; Kikinis, Ron; Shaffer, Kitt
2016-01-01
Rationale and Objectives Anatomy is an essential component of medical education as it is critical for the accurate diagnosis in organs and human systems. The mental representation of the shape and organization of different anatomical structures is a crucial step in the learning process. The purpose of this pilot study is to demonstrate the feasibility and benefits of developing innovative teaching modules for anatomy education of first-year medical students based on 3D reconstructions from actual patient data. Materials and Methods A total of 196 models of anatomical structures from 16 anonymized CT datasets were generated using the 3D Slicer open-source software platform. The models focused on three anatomical areas: the mediastinum, the upper abdomen and the pelvis. Online optional quizzes were offered to first-year medical students to assess their comprehension in the areas of interest. Specific tasks were designed for students to complete using the 3D models. Results Scores of the quizzes confirmed a lack of understanding of 3D spatial relationships of anatomical structures despite standard instruction including dissection. Written task material and qualitative review by students suggested that interaction with 3D models led to a better understanding of the shape and spatial relationships among structures, and helped illustrate anatomical variations from one body to another. Conclusion The study demonstrates the feasibility of one possible approach to the generation of 3D models of the anatomy from actual patient data. The educational materials developed have the potential to supplement the teaching of complex anatomical regions and help demonstrate the anatomic variation among patients. PMID:26897601
Atlas-based segmentation of 3D cerebral structures with competitive level sets and fuzzy control.
Ciofolo, Cybèle; Barillot, Christian
2009-06-01
We propose a novel approach for the simultaneous segmentation of multiple structures with competitive level sets driven by fuzzy control. To this end, several contours evolve simultaneously toward previously defined anatomical targets. A fuzzy decision system combines the a priori knowledge provided by an anatomical atlas with the intensity distribution of the image and the relative position of the contours. This combination automatically determines the directional term of the evolution equation of each level set. This leads to a local expansion or contraction of the contours, in order to match the boundaries of their respective targets. Two applications are presented: the segmentation of the brain hemispheres and the cerebellum, and the segmentation of deep internal structures. Experimental results on real magnetic resonance (MR) images are presented, quantitatively assessed and discussed.
Automatic query formulations in information retrieval.
Salton, G; Buckley, C; Fox, E A
1983-07-01
Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.
Teijeiro, E J; Macías, R J; Morales, J M; Guerra, E; López, G; Alvarez, L M; Fernández, F; Maragoto, C; Seijo, F; Alvarez, E
The Neurosurgical Deep Recording System (NDRS) using a personal computer takes the place of complex electronic equipment for recording and processing deep cerebral electrical activity, as a guide in stereotaxic functional neurosurgery. It also permits increased possibilities of presenting information in direct graphic form with automatic management and sufficient flexibility to implement different analyses. This paper describes the possibilities of automatic simultaneous graphic representation in three almost orthogonal planes, available with the new 5.1 version of NDRS so as to facilitate the analysis of anatomophysiological correlation in the localization of deep structures of the brain during minimal access surgery. This new version can automatically show the spatial behaviour of signals registered throughout the path of the electrode inside the brain, superimposed simultaneously on sagittal, coronal and axial sections of an anatomical atlas of the brain, after adjusting the scale automatically according to the dimensions of the brain of each individual patient. This may also be shown in a tridimensional representation of the different planes themselves intercepting. The NDRS system has been successfully used in Spain and Cuba in over 300 functional neurosurgery operations. The new version further facilitates analysis of spatial anatomophysiological correlation for the localization of brain structures. This system has contributed to increase the precision and safety in selecting surgical targets in the control of Parkinson s disease and other disorders of movement.
SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maitree, R; Guzman, G; Chundury, A
Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness ofmore » available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and qualitative assessment, the proposed approach has superior noise reduction and anatomical structures preservation capabilities over existing noise removal methods. Senior Author Dr. Deshan Yang received research funding form ViewRay and Varian.« less
Muirhead, David; Aoun, Patricia; Powell, Michael; Juncker, Flemming; Mollerup, Jens
2010-08-01
The need for higher efficiency, maximum quality, and faster turnaround time is a continuous focus for anatomic pathology laboratories and drives changes in work scheduling, instrumentation, and management control systems. To determine the costs of generating routine, special, and immunohistochemical microscopic slides in a large, academic anatomic pathology laboratory using a top-down approach. The Pathology Economic Model Tool was used to analyze workflow processes at The Nebraska Medical Center's anatomic pathology laboratory. Data from the analysis were used to generate complete cost estimates, which included not only materials, consumables, and instrumentation but also specific labor and overhead components for each of the laboratory's subareas. The cost data generated by the Pathology Economic Model Tool were compared with the cost estimates generated using relative value units. Despite the use of automated systems for different processes, the workflow in the laboratory was found to be relatively labor intensive. The effect of labor and overhead on per-slide costs was significantly underestimated by traditional relative-value unit calculations when compared with the Pathology Economic Model Tool. Specific workflow defects with significant contributions to the cost per slide were identified. The cost of providing routine, special, and immunohistochemical slides may be significantly underestimated by traditional methods that rely on relative value units. Furthermore, a comprehensive analysis may identify specific workflow processes requiring improvement.
Zhang, Xiaoyan; Kim, Daeseung; Shen, Shunyao; Yuan, Peng; Liu, Siting; Tang, Zhen; Zhang, Guangming; Zhou, Xiaobo; Gateno, Jaime
2017-01-01
Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians’ need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change. PMID:29027022
Zhang, Xiaoyan; Kim, Daeseung; Shen, Shunyao; Yuan, Peng; Liu, Siting; Tang, Zhen; Zhang, Guangming; Zhou, Xiaobo; Gateno, Jaime; Liebschner, Michael A K; Xia, James J
2018-04-01
Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians' need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change.
How small could a pup sound? The physical bases of signaling body size in harbor seals
Gross, Stephanie; Garcia, Maxime; Rubio-Garcia, Ana; de Boer, Bart
2017-01-01
Abstract Vocal communication is a crucial aspect of animal behavior. The mechanism which most mammals use to vocalize relies on three anatomical components. First, air overpressure is generated inside the lower vocal tract. Second, as the airstream goes through the glottis, sound is produced via vocal fold vibration. Third, this sound is further filtered by the geometry and length of the upper vocal tract. Evidence from mammalian anatomy and bioacoustics suggests that some of these three components may covary with an animal’s body size. The framework provided by acoustic allometry suggests that, because vocal tract length (VTL) is more strongly constrained by the growth of the body than vocal fold length (VFL), VTL generates more reliable acoustic cues to an animal’s size. This hypothesis is often tested acoustically but rarely anatomically, especially in pinnipeds. Here, we test the anatomical bases of the acoustic allometry hypothesis in harbor seal pups Phoca vitulina. We dissected and measured vocal tract, vocal folds, and other anatomical features of 15 harbor seals post-mortem. We found that, while VTL correlates with body size, VFL does not. This suggests that, while body growth puts anatomical constraints on how vocalizations are filtered by harbor seals’ vocal tract, no such constraints appear to exist on vocal folds, at least during puppyhood. It is particularly interesting to find anatomical constraints on harbor seals’ vocal tracts, the same anatomical region partially enabling pups to produce individually distinctive vocalizations. PMID:29492005
Automatic finite element generators
NASA Technical Reports Server (NTRS)
Wang, P. S.
1984-01-01
The design and implementation of a software system for generating finite elements and related computations are described. Exact symbolic computational techniques are employed to derive strain-displacement matrices and element stiffness matrices. Methods for dealing with the excessive growth of symbolic expressions are discussed. Automatic FORTRAN code generation is described with emphasis on improving the efficiency of the resultant code.
GBM heterogeneity characterization by radiomic analysis of phenotype anatomical planes
NASA Astrophysics Data System (ADS)
Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew
2016-03-01
Glioblastoma multiforme (GBM) is the most common malignant primary tumor of the central nervous system, characterized among other traits by rapid metastatis. Three tissue phenotypes closely associated with GBMs, namely, necrosis (N), contrast enhancement (CE), and edema/invasion (E), exhibit characteristic patterns of texture heterogeneity in magnetic resonance images (MRI). In this study, we propose a novel model to characterize GBM tissue phenotypes using gray level co-occurrence matrices (GLCM) in three anatomical planes. The GLCM encodes local image patches in terms of informative, orientation-invariant texture descriptors, which are used here to sub-classify GBM tissue phenotypes. Experiments demonstrate the model on MRI data of 41 GBM patients, obtained from the cancer genome atlas (TCGA). Intensity-based automatic image registration is applied to align corresponding pairs of fixed T1˗weighted (T1˗WI) post-contrast and fluid attenuated inversion recovery (FLAIR) images. GBM tissue regions are then segmented using the 3D Slicer tool. Texture features are computed from 12 quantifier functions operating on GLCM descriptors, that are generated from MRI intensities within segmented GBM tissue regions. Various classifier models are used to evaluate the effectiveness of texture features for discriminating between GBM phenotypes. Results based on T1-WI scans showed a phenotype classification accuracy of over 88.14%, a sensitivity of 85.37% and a specificity of 96.1%, using the linear discriminant analysis (LDA) classifier. This model has the potential to provide important characteristics of tumors, which can be used for the sub-classification of GBM phenotypes.
NASA Astrophysics Data System (ADS)
Norris, Hannah; Zhang, Yakun; Frush, Jack; Sturgeon, Gregory M.; Minhas, Anum; Tward, Daniel J.; Ratnanather, J. Tilak; Miller, M. I.; Frush, Donald; Samei, Ehsan; Segars, W. Paul
2014-03-01
With the increased use of CT examinations, the associated radiation dose has become a large concern, especially for pediatrics. Much research has focused on reducing radiation dose through new scanning and reconstruction methods. Computational phantoms provide an effective and efficient means for evaluating image quality, patient-specific dose, and organ-specific dose in CT. We previously developed a set of highly-detailed 4D reference pediatric XCAT phantoms at ages of newborn, 1, 5, 10, and 15 years with organ and tissues masses matched to ICRP Publication 89 values. We now extend this reference set to a series of 64 pediatric phantoms of a variety of ages and height and weight percentiles, representative of the public at large. High resolution PET-CT data was reviewed by a practicing experienced radiologist for anatomic regularity and was then segmented with manual and semi-automatic methods to form a target model. A Multi-Channel Large Deformation Diffeomorphic Metric Mapping (MC-LDDMM) algorithm was used to calculate the transform from the best age matching pediatric reference phantom to the patient target. The transform was used to complete the target, filling in the non-segmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. 3D CT data was simulated from the phantoms to demonstrate their ability to generate realistic, patient quality imaging data. The population of pediatric phantoms developed in this work provides a vital tool to investigate dose reduction techniques in 3D and 4D pediatric CT.
Automatic Commercial Permit Sets
DOE Office of Scientific and Technical Information (OSTI.GOV)
Grana, Paul
Final report for Folsom Labs’ Solar Permit Generator project, which has successfully completed, resulting in the development and commercialization of a software toolkit within the cloud-based HelioScope software environment that enables solar engineers to automatically generate and manage draft documents for permit submission.
Casteleyn, C; Simoens, P; Van den Broeck, W
2011-06-01
Many terms used for referring to tonsillar structures are applied in immunological research. However, in many cases, the use of these terms is not in compliance with official veterinary anatomical nomenclature. This is partly attributable to ambiguous descriptions present in conventional anatomical textbooks. This study gives an overview of pertaining controversial terms and promotes the official anatomical terminology applicable to the tonsils, to enhance the unequivocal transfer of knowledge generated during immunological research. © 2011 Blackwell Verlag GmbH.
A statistical parts-based appearance model of inter-subject variability.
Toews, Matthew; Collins, D Louis; Arbel, Tal
2006-01-01
In this article, we present a general statistical parts-based model for representing the appearance of an image set, applied to the problem of inter-subject MR brain image matching. In contrast with global image representations such as active appearance models, the parts-based model consists of a collection of localized image parts whose appearance, geometry and occurrence frequency are quantified statistically. The parts-based approach explicitly addresses the case where one-to-one correspondence does not exist between subjects due to anatomical differences, as parts are not expected to occur in all subjects. The model can be learned automatically, discovering structures that appear with statistical regularity in a large set of subject images, and can be robustly fit to new images, all in the presence of significant inter-subject variability. As parts are derived from generic scale-invariant features, the framework can be applied in a wide variety of image contexts, in order to study the commonality of anatomical parts or to group subjects according to the parts they share. Experimentation shows that a parts-based model can be learned from a large set of MR brain images, and used to determine parts that are common within the group of subjects. Preliminary results indicate that the model can be used to automatically identify distinctive features for inter-subject image registration despite large changes in appearance.
The white matter query language: a novel approach for describing human white matter anatomy
Makris, Nikos; Rathi, Yogesh; Shenton, Martha; Kikinis, Ron; Kubicki, Marek; Westin, Carl-Fredrik
2016-01-01
We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion MRI volumes. Further, our method simplifies the quantification and statistical analysis of white matter tracts on large diffusion MRI databases. This work reflects the careful syntactical definition of major white matter fiber tracts in the human brain based on a neuroanatomist’s expert knowledge. The framework is based on a novel query language with a near-to-English textual syntax. This query language makes it possible to construct a dictionary of anatomical definitions that describe white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This novel method makes it possible to automatically label white matter anatomy across subjects. After describing this method, we provide an example of its implementation where we encode anatomical knowledge in human white matter for ten association and 15 projection tracts per hemisphere, along with seven commissural tracts. Importantly, this novel method is comparable in accuracy to manual labeling. Finally, we present results applying this method to create a white matter atlas from 77 healthy subjects, and we use this atlas in a small proof-of-concept study to detect changes in association tracts that characterize schizophrenia. PMID:26754839
The white matter query language: a novel approach for describing human white matter anatomy.
Wassermann, Demian; Makris, Nikos; Rathi, Yogesh; Shenton, Martha; Kikinis, Ron; Kubicki, Marek; Westin, Carl-Fredrik
2016-12-01
We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion MRI volumes. Further, our method simplifies the quantification and statistical analysis of white matter tracts on large diffusion MRI databases. This work reflects the careful syntactical definition of major white matter fiber tracts in the human brain based on a neuroanatomist's expert knowledge. The framework is based on a novel query language with a near-to-English textual syntax. This query language makes it possible to construct a dictionary of anatomical definitions that describe white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This novel method makes it possible to automatically label white matter anatomy across subjects. After describing this method, we provide an example of its implementation where we encode anatomical knowledge in human white matter for ten association and 15 projection tracts per hemisphere, along with seven commissural tracts. Importantly, this novel method is comparable in accuracy to manual labeling. Finally, we present results applying this method to create a white matter atlas from 77 healthy subjects, and we use this atlas in a small proof-of-concept study to detect changes in association tracts that characterize schizophrenia.
Wang, Li; Ren, Yi; Gao, Yaozong; Tang, Zhen; Chen, Ken-Chung; Li, Jianfu; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Xia, James J.; Shen, Dinggang
2015-01-01
Purpose: A significant number of patients suffer from craniomaxillofacial (CMF) deformity and require CMF surgery in the United States. The success of CMF surgery depends on not only the surgical techniques but also an accurate surgical planning. However, surgical planning for CMF surgery is challenging due to the absence of a patient-specific reference model. Currently, the outcome of the surgery is often subjective and highly dependent on surgeon’s experience. In this paper, the authors present an automatic method to estimate an anatomically correct reference shape of jaws for orthognathic surgery, a common type of CMF surgery. Methods: To estimate a patient-specific jaw reference model, the authors use a data-driven method based on sparse shape composition. Given a dictionary of normal subjects, the authors first use the sparse representation to represent the midface of a patient by the midfaces of the normal subjects in the dictionary. Then, the derived sparse coefficients are used to reconstruct a patient-specific reference jaw shape. Results: The authors have validated the proposed method on both synthetic and real patient data. Experimental results show that the authors’ method can effectively reconstruct the normal shape of jaw for patients. Conclusions: The authors have presented a novel method to automatically estimate a patient-specific reference model for the patient suffering from CMF deformity. PMID:26429255
Comparative analysis of semantic localization accuracies between adult and pediatric DICOM CT images
NASA Astrophysics Data System (ADS)
Robertson, Duncan; Pathak, Sayan D.; Criminisi, Antonio; White, Steve; Haynor, David; Chen, Oliver; Siddiqui, Khan
2012-02-01
Existing literature describes a variety of techniques for semantic annotation of DICOM CT images, i.e. the automatic detection and localization of anatomical structures. Semantic annotation facilitates enhanced image navigation, linkage of DICOM image content and non-image clinical data, content-based image retrieval, and image registration. A key challenge for semantic annotation algorithms is inter-patient variability. However, while the algorithms described in published literature have been shown to cope adequately with the variability in test sets comprising adult CT scans, the problem presented by the even greater variability in pediatric anatomy has received very little attention. Most existing semantic annotation algorithms can only be extended to work on scans of both adult and pediatric patients by adapting parameters heuristically in light of patient size. In contrast, our approach, which uses random regression forests ('RRF'), learns an implicit model of scale variation automatically using training data. In consequence, anatomical structures can be localized accurately in both adult and pediatric CT studies without the need for parameter adaptation or additional information about patient scale. We show how the RRF algorithm is able to learn scale invariance from a combined training set containing a mixture of pediatric and adult scans. Resulting localization accuracy for both adult and pediatric data remains comparable with that obtained using RRFs trained and tested using only adult data.
UIVerify: A Web-Based Tool for Verification and Automatic Generation of User Interfaces
NASA Technical Reports Server (NTRS)
Shiffman, Smadar; Degani, Asaf; Heymann, Michael
2004-01-01
In this poster, we describe a web-based tool for verification and automatic generation of user interfaces. The verification component of the tool accepts as input a model of a machine and a model of its interface, and checks that the interface is adequate (correct). The generation component of the tool accepts a model of a given machine and the user's task, and then generates a correct and succinct interface. This write-up will demonstrate the usefulness of the tool by verifying the correctness of a user interface to a flight-control system. The poster will include two more examples of using the tool: verification of the interface to an espresso machine, and automatic generation of a succinct interface to a large hypothetical machine.
Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi
2017-10-01
We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging issue of anatomical structure segmentation in 3D CT cases. The novelty of this work is the policy of deep learning of the different 2D sectional appearances of 3D anatomical structures for CT cases and the majority voting of the 3D segmentation results from multiple crossed 2D sections to achieve availability and reliability with better efficiency, generality, and flexibility than conventional segmentation methods, which must be guided by human expertise. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Automatic mathematical modeling for real time simulation program (AI application)
NASA Technical Reports Server (NTRS)
Wang, Caroline; Purinton, Steve
1989-01-01
A methodology is described for automatic mathematical modeling and generating simulation models. The major objective was to create a user friendly environment for engineers to design, maintain, and verify their models; to automatically convert the mathematical models into conventional code for computation; and finally, to document the model automatically.
NASA Astrophysics Data System (ADS)
Tang, Zhenchao; Liu, Zhenyu; Li, Ruili; Cui, Xinwei; Li, Hongjun; Dong, Enqing; Tian, Jie
2017-03-01
It's widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviraltherapy- naïve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.
A practical workflow for making anatomical atlases for biological research.
Wan, Yong; Lewis, A Kelsey; Colasanto, Mary; van Langeveld, Mark; Kardon, Gabrielle; Hansen, Charles
2012-01-01
The anatomical atlas has been at the intersection of science and art for centuries. These atlases are essential to biological research, but high-quality atlases are often scarce. Recent advances in imaging technology have made high-quality 3D atlases possible. However, until now there has been a lack of practical workflows using standard tools to generate atlases from images of biological samples. With certain adaptations, CG artists' workflow and tools, traditionally used in the film industry, are practical for building high-quality biological atlases. Researchers have developed a workflow for generating a 3D anatomical atlas using accessible artists' tools. They used this workflow to build a mouse limb atlas for studying the musculoskeletal system's development. This research aims to raise the awareness of using artists' tools in scientific research and promote interdisciplinary collaborations between artists and scientists. This video (http://youtu.be/g61C-nia9ms) demonstrates a workflow for creating an anatomical atlas.
Automatic NEPHIS Coding of Descriptive Titles for Permuted Index Generation.
ERIC Educational Resources Information Center
Craven, Timothy C.
1982-01-01
Describes a system for the automatic coding of most descriptive titles which generates Nested Phrase Indexing System (NEPHIS) input strings of sufficient quality for permuted index production. A series of examples and an 11-item reference list accompany the text. (JL)
Strategies for automatic processing of large aftershock sequences
NASA Astrophysics Data System (ADS)
Kvaerna, T.; Gibbons, S. J.
2017-12-01
Aftershock sequences following major earthquakes present great challenges to seismic bulletin generation. The analyst resources needed to locate events increase with increased event numbers as the quality of underlying, fully automatic, event lists deteriorates. While current pipelines, designed a generation ago, are usually limited to single passes over the raw data, modern systems also allow multiple passes. Processing the raw data from each station currently generates parametric data streams that are later subject to phase-association algorithms which form event hypotheses. We consider a major earthquake scenario and propose to define a region of likely aftershock activity in which we will detect and accurately locate events using a separate, specially targeted, semi-automatic process. This effort may use either pattern detectors or more general algorithms that cover wider source regions without requiring waveform similarity. An iterative procedure to generate automatic bulletins would incorporate all the aftershock event hypotheses generated by the auxiliary process, and filter all phases from these events from the original detection lists prior to a new iteration of the global phase-association algorithm.
101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol
Klein, Arno; Tourville, Jason
2012-01-01
We introduce the Mindboggle-101 dataset, the largest and most complete set of free, publicly accessible, manually labeled human brain images. To manually label the macroscopic anatomy in magnetic resonance images of 101 healthy participants, we created a new cortical labeling protocol that relies on robust anatomical landmarks and minimal manual edits after initialization with automated labels. The “Desikan–Killiany–Tourville” (DKT) protocol is intended to improve the ease, consistency, and accuracy of labeling human cortical areas. Given how difficult it is to label brains, the Mindboggle-101 dataset is intended to serve as brain atlases for use in labeling other brains, as a normative dataset to establish morphometric variation in a healthy population for comparison against clinical populations, and contribute to the development, training, testing, and evaluation of automated registration and labeling algorithms. To this end, we also introduce benchmarks for the evaluation of such algorithms by comparing our manual labels with labels automatically generated by probabilistic and multi-atlas registration-based approaches. All data and related software and updated information are available on the http://mindboggle.info/data website. PMID:23227001
Research-oriented image registry for multimodal image integration.
Tanaka, M; Sadato, N; Ishimori, Y; Yonekura, Y; Yamashita, Y; Komuro, H; Hayahsi, N; Ishii, Y
1998-01-01
To provide multimodal biomedical images automatically, we constructed the research-oriented image registry, Data Delivery System (DDS). DDS was constructed on the campus local area network. Machines which generate images (imagers: DSA, ultrasound, PET, MRI, SPECT and CT) were connected to the campus LAN. Once a patient is registered, all his images are automatically picked up by DDS as they are generated, transferred through the gateway server to the intermediate server, and copied into the directory of the user who registered the patient. DDS informs the user through e-mail that new data have been generated and transferred. Data format is automatically converted into one which is chosen by the user. Data inactive for a certain period in the intermediate server are automatically achieved into the final and permanent data server based on compact disk. As a soft link is automatically generated through this step, a user has access to all (old or new) image data of the patient of his interest. As DDS runs with minimal maintenance, cost and time for data transfer are significantly saved. By making the complex process of data transfer and conversion invisible, DDS has made it easy for naive-to-computer researchers to concentrate on their biomedical interest.
Quantification of regional fat volume in rat MRI
NASA Astrophysics Data System (ADS)
Sacha, Jaroslaw P.; Cockman, Michael D.; Dufresne, Thomas E.; Trokhan, Darren
2003-05-01
Multiple initiatives in the pharmaceutical and beauty care industries are directed at identifying therapies for weight management. Body composition measurements are critical for such initiatives. Imaging technologies that can be used to measure body composition noninvasively include DXA (dual energy x-ray absorptiometry) and MRI (magnetic resonance imaging). Unlike other approaches, MRI provides the ability to perform localized measurements of fat distribution. Several factors complicate the automatic delineation of fat regions and quantification of fat volumes. These include motion artifacts, field non-uniformity, brightness and contrast variations, chemical shift misregistration, and ambiguity in delineating anatomical structures. We have developed an approach to deal practically with those challenges. The approach is implemented in a package, the Fat Volume Tool, for automatic detection of fat tissue in MR images of the rat abdomen, including automatic discrimination between abdominal and subcutaneous regions. We suppress motion artifacts using masking based on detection of implicit landmarks in the images. Adaptive object extraction is used to compensate for intensity variations. This approach enables us to perform fat tissue detection and quantification in a fully automated manner. The package can also operate in manual mode, which can be used for verification of the automatic analysis or for performing supervised segmentation. In supervised segmentation, the operator has the ability to interact with the automatic segmentation procedures to touch-up or completely overwrite intermediate segmentation steps. The operator's interventions steer the automatic segmentation steps that follow. This improves the efficiency and quality of the final segmentation. Semi-automatic segmentation tools (interactive region growing, live-wire, etc.) improve both the accuracy and throughput of the operator when working in manual mode. The quality of automatic segmentation has been evaluated by comparing the results of fully automated analysis to manual analysis of the same images. The comparison shows a high degree of correlation that validates the quality of the automatic segmentation approach.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kang, H; Padilla, L; Hasan, Y
Purpose: To develop a standalone application, which automatically and consistently calculates the coordinates of points A and H based solely on the implanted applicator geometry for cervical cancer HDR brachytherapy. Methods: Manchester point A and ABS point H are both located 2cm lateral from the central tandem plane. While both points are located 2cm above the cervical os, surrogates for the os differ. Point A is defined relative to the anatomical cervical os. Point H is defined relative to the intersection of the tandem with the superior aspects of the ovoids. The application takes an input text file generated bymore » the treatment planning system (TPS, BrachyVision, Varian) that specifies the source geometries. It then outputs the 3D coordinates of points A and H in both the left and right directions. The algorithm was implemented and tested on 34 CT scans of 7 patients treated with HDR brachytherapy delivered using tandem and ovoids. A single experienced user retrospectively and manually placed points A and H on the CT scans, whose coordinates were used as the gold standard for the comparison to the automatically calculated points. Results: The automatically calculated coordinates of points A and H agree within 0.7mm with the gold standard. The averages and standard deviations of the 3D coordinate difference between points placed by the two methods are 0.3±0.1 and 0.4±0.1mm for points A and H, respectively. The maximum difference in 3D magnitude is 0.7mm. Conclusion: The algorithm consistently calculates dose point coordinates independently of the planner for cervical cancer brachytherapy treated with tandem and ovoids. Automated point placement based on the geometry of the implanted applicators agrees in sub-millimeter with careful manual placements by an experienced user. This algorithm expedites the planning process and eliminates dependencies on either user input or TPS visualization tools.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, H; Tan, J; Kavanaugh, J
Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-timemore » and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.« less
Automatic Item Generation: A More Efficient Process for Developing Mathematics Achievement Items?
ERIC Educational Resources Information Center
Embretson, Susan E.; Kingston, Neal M.
2018-01-01
The continual supply of new items is crucial to maintaining quality for many tests. Automatic item generation (AIG) has the potential to rapidly increase the number of items that are available. However, the efficiency of AIG will be mitigated if the generated items must be submitted to traditional, time-consuming review processes. In two studies,…
Research on Generating Method of Embedded Software Test Document Based on Dynamic Model
NASA Astrophysics Data System (ADS)
Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying
2018-03-01
This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoogcarspel, S J; Kontaxis, C; Velden, J M van der
2014-06-01
Purpose: To develop an MR accelerator-enabled online planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases. The technical challenges include; automated stereotactic treatment planning, online MR-based dose calculation and MR guidance during treatment. Methods: Using the CT data of 20 patients previously treated at our institution, a class solution for automated treatment planning for spinal bone metastases was created. For accurate dose simulation right before treatment, we fused geometrically correct online MR data with pretreatment CT data of the target volume (TV). For target tracking during treatment, a dynamic T2-weighted TSE MR sequence was developed. An in house developedmore » GPU based IMRT optimization and dose calculation algorithm was used for fast treatment planning and simulation. An automatically generated treatment plan developed with this treatment planning system was irradiated on a clinical 6 MV linear accelerator and evaluated using a Delta4 dosimeter. Results: The automated treatment planning method yielded clinically viable plans for all patients. The MR-CT fusion based dose calculation accuracy was within 2% as compared to calculations performed with original CT data. The dynamic T2-weighted TSE MR Sequence was able to provide an update of the anatomical location of the TV every 10 seconds. Dose calculation and optimization of the automatically generated treatment plans using only one GPU took on average 8 minutes. The Delta4 measurement of the irradiated plan agreed with the dose calculation with a 3%/3mm gamma pass rate of 86.4%. Conclusions: The development of an MR accelerator-enabled planning-todelivery technique for stereotactic palliative radiotherapy treatment of spinal metastases was presented. Future work will involve developing an intrafraction motion adaptation strategy, MR-only dose calculation, radiotherapy quality-assurance in a magnetic field, and streamlining the entire treatment process on an MR accelerator.« less
Using Automatic Code Generation in the Attitude Control Flight Software Engineering Process
NASA Technical Reports Server (NTRS)
McComas, David; O'Donnell, James R., Jr.; Andrews, Stephen F.
1999-01-01
This paper presents an overview of the attitude control subsystem flight software development process, identifies how the process has changed due to automatic code generation, analyzes each software development phase in detail, and concludes with a summary of our lessons learned.
GIS Data Based Automatic High-Fidelity 3D Road Network Modeling
NASA Technical Reports Server (NTRS)
Wang, Jie; Shen, Yuzhong
2011-01-01
3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks
Automating Traceability for Generated Software Artifacts
NASA Technical Reports Server (NTRS)
Richardson, Julian; Green, Jeffrey
2004-01-01
Program synthesis automatically derives programs from specifications of their behavior. One advantage of program synthesis, as opposed to manual coding, is that there is a direct link between the specification and the derived program. This link is, however, not very fine-grained: it can be best characterized as Program is-derived- from Specification. When the generated program needs to be understood or modified, more $ne-grained linking is useful. In this paper, we present a novel technique for automatically deriving traceability relations between parts of a specification and parts of the synthesized program. The technique is very lightweight and works -- with varying degrees of success - for any process in which one artifact is automatically derived from another. We illustrate the generality of the technique by applying it to two kinds of automatic generation: synthesis of Kalman Filter programs from speci3cations using the Aut- oFilter program synthesis system, and generation of assembly language programs from C source code using the GCC C compilel: We evaluate the effectiveness of the technique in the latter application.
Tuned grid generation with ICEM CFD
NASA Technical Reports Server (NTRS)
Wulf, Armin; Akdag, Vedat
1995-01-01
ICEM CFD is a CAD based grid generation package that supports multiblock structured, unstructured tetrahedral and unstructured hexahedral grids. Major development efforts have been spent to extend ICEM CFD's multiblock structured and hexahedral unstructured grid generation capabilities. The modules added are: a parametric grid generation module and a semi-automatic hexahedral grid generation module. A fully automatic version of the hexahedral grid generation module for around a set of predefined objects in rectilinear enclosures has been developed. These modules will be presented and the procedures used will be described, and examples will be discussed.
Optic disc detection using ant colony optimization
NASA Astrophysics Data System (ADS)
Dias, Marcy A.; Monteiro, Fernando C.
2012-09-01
The retinal fundus images are used in the treatment and diagnosis of several eye diseases, such as diabetic retinopathy and glaucoma. This paper proposes a new method to detect the optic disc (OD) automatically, due to the fact that the knowledge of the OD location is essential to the automatic analysis of retinal images. Ant Colony Optimization (ACO) is an optimization algorithm inspired by the foraging behaviour of some ant species that has been applied in image processing for edge detection. Recently, the ACO was used in fundus images to detect edges, and therefore, to segment the OD and other anatomical retinal structures. We present an algorithm for the detection of OD in the retina which takes advantage of the Gabor wavelet transform, entropy and ACO algorithm. Forty images of the retina from DRIVE database were used to evaluate the performance of our method.
User-guided segmentation for volumetric retinal optical coherence tomography images
Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.
2014-01-01
Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962
Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen
2014-01-01
The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531
User-guided segmentation for volumetric retinal optical coherence tomography images.
Yin, Xin; Chao, Jennifer R; Wang, Ruikang K
2014-08-01
Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.
Lee, Chia-Yen; Wang, Hao-Jen; Lai, Jhih-Hao; Chang, Yeun-Chung; Huang, Chiun-Sheng
2017-01-01
Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model. In addition, competitive winner-guided mechanism is developed for optimal corresponding. The proposed algorithm is evaluated in two ways. Results show that the algorithm can quickly lead to accurate image registration and that the effectiveness is superior to manual registration with a mean error being 0.91 pixels. These findings demonstrate that the proposed registration algorithm is reasonably accurate and provide a novel method of extracting a greater amount of useful data from infrared images. PMID:28145474
Wang, Jieqiong; Miao, Wen; Li, Jing; Li, Meng; Zhen, Zonglei; Sabel, Bernhard; Xian, Junfang; He, Huiguang
2015-11-30
The lateral geniculate nucleus (LGN) is a key relay center of the visual system. Because the LGN morphology is affected by different diseases, it is of interest to analyze its morphology by segmentation. However, existing LGN segmentation methods are non-automatic, inefficient and prone to experimenters' bias. To address these problems, we proposed an automatic LGN segmentation algorithm based on T1-weighted imaging. First, the prior information of LGN was used to create a prior mask. Then region growing was applied to delineate LGN. We evaluated this automatic LGN segmentation method by (1) comparison with manually segmented LGN, (2) anatomically locating LGN in the visual system via LGN-based tractography, (3) application to control and glaucoma patients. The similarity coefficients of automatic segmented LGN and manually segmented one are 0.72 (0.06) for the left LGN and 0.77 (0.07) for the right LGN. LGN-based tractography shows the subcortical pathway seeding from LGN passes the optic tract and also reaches V1 through the optic radiation, which is consistent with the LGN location in the visual system. In addition, LGN asymmetry as well as LGN atrophy along with age is observed in normal controls. The investigation of glaucoma effects on LGN volumes demonstrates that the bilateral LGN volumes shrink in patients. The automatic LGN segmentation is objective, efficient, valid and applicable. Experiment results proved the validity and applicability of the algorithm. Our method will speed up the research on visual system and greatly enhance studies of different vision-related diseases. Copyright © 2015 Elsevier B.V. All rights reserved.
Gaussian curvature analysis allows for automatic block placement in multi-block hexahedral meshing.
Ramme, Austin J; Shivanna, Kiran H; Magnotta, Vincent A; Grosland, Nicole M
2011-10-01
Musculoskeletal finite element analysis (FEA) has been essential to research in orthopaedic biomechanics. The generation of a volumetric mesh is often the most challenging step in a FEA. Hexahedral meshing tools that are based on a multi-block approach rely on the manual placement of building blocks for their mesh generation scheme. We hypothesise that Gaussian curvature analysis could be used to automatically develop a building block structure for multi-block hexahedral mesh generation. The Automated Building Block Algorithm incorporates principles from differential geometry, combinatorics, statistical analysis and computer science to automatically generate a building block structure to represent a given surface without prior information. We have applied this algorithm to 29 bones of varying geometries and successfully generated a usable mesh in all cases. This work represents a significant advancement in automating the definition of building blocks.
Triggers and Anatomical Substrates in the Genesis and Perpetuation of Atrial Fibrillation
Sánchez-Quintana, Damián; López-Mínguez, José Ramón; Pizarro, Gonzalo; Murillo, Margarita; Cabrera, José Angel
2012-01-01
The definition of atrial fibrillation (AF) as a functional electrical disorder does not reflect the significant underlying structural abnormalities. Atrial and Pulmonary Vein (PV) muscle sleeve microstructural remodeling is present, and establishes a vulnerable substrate for AF maintenance. In spite of an incomplete understanding of the anatomo-functional basis for AF, current evidence demonstrates that this arrhythmia usually requires a trigger for initiation and a vulnerable electrophysiological and/or anatomical substrate for maintenance. It is still unclear whether the trigger mechanisms include focal enhanced automaticity, triggered activity and/or micro re-entry from myocardial tissue. Initiation of AF can be favored by both parasympathetic and sympathetic stimulation, which also seem to play a role in maintaining AF. Finally, evolving clinical evidence demonstrates that inflammation is associated with new-onset and recurrent AF through a mechanism that possibly involves cellular degeneration, apoptosis, and subsequent atrial fibrosis. PMID:22920484
Automatic non-proliferative diabetic retinopathy screening system based on color fundus image.
Xiao, Zhitao; Zhang, Xinpeng; Geng, Lei; Zhang, Fang; Wu, Jun; Tong, Jun; Ogunbona, Philip O; Shan, Chunyan
2017-10-26
Non-proliferative diabetic retinopathy is the early stage of diabetic retinopathy. Automatic detection of non-proliferative diabetic retinopathy is significant for clinical diagnosis, early screening and course progression of patients. This paper introduces the design and implementation of an automatic system for screening non-proliferative diabetic retinopathy based on color fundus images. Firstly, the fundus structures, including blood vessels, optic disc and macula, are extracted and located, respectively. In particular, a new optic disc localization method using parabolic fitting is proposed based on the physiological structure characteristics of optic disc and blood vessels. Then, early lesions, such as microaneurysms, hemorrhages and hard exudates, are detected based on their respective characteristics. An equivalent optical model simulating human eyes is designed based on the anatomical structure of retina. Main structures and early lesions are reconstructed in the 3D space for better visualization. Finally, the severity of each image is evaluated based on the international criteria of diabetic retinopathy. The system has been tested on public databases and images from hospitals. Experimental results demonstrate that the proposed system achieves high accuracy for main structures and early lesions detection. The results of severity classification for non-proliferative diabetic retinopathy are also accurate and suitable. Our system can assist ophthalmologists for clinical diagnosis, automatic screening and course progression of patients.
Bercovich, A; Edan, Y; Alchanatis, V; Moallem, U; Parmet, Y; Honig, H; Maltz, E; Antler, A; Halachmi, I
2013-01-01
Body condition evaluation is a common tool to assess energy reserves of dairy cows and to estimate their fatness or thinness. This study presents a computer-vision tool that automatically estimates cow's body condition score. Top-view images of 151 cows were collected on an Israeli research dairy farm using a digital still camera located at the entrance to the milking parlor. The cow's tailhead area and its contour were segmented and extracted automatically. Two types of features of the tailhead contour were extracted: (1) the angles and distances between 5 anatomical points; and (2) the cow signature, which is a 1-dimensional vector of the Euclidean distances from each point in the normalized tailhead contour to the shape center. Two methods were applied to describe the cow's signature and to reduce its dimension: (1) partial least squares regression, and (2) Fourier descriptors of the cow signature. Three prediction models were compared with manual scores of an expert. Results indicate that (1) it is possible to automatically extract and predict body condition from color images without any manual interference; and (2) Fourier descriptors of the cow's signature result in improved performance (R(2)=0.77). Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Stemless shoulder arthroplasty: a literature review
PETRICCIOLI, DARIO; BERTONE, CELESTE; MARCHI, GIACOMO
2015-01-01
The design of humeral implants for shoulder arthroplasty has evolved over the years. The new-generation modular shoulder prostheses have an anatomical humeral stem that replicates the three-dimensional parameters of the proximal humerus. An anatomical reconstruction is the best way to restore stability and mobility of the prosthetic shoulder and improve implant durability. However, a perfect anatomical match is not always possible in, for example, patients with post-traumatic osteoarthritis of the shoulder and deformities in the metaphyseal region. To avoid stem-related complications while retaining the advantages of the fourth generation of shoulder implants, different stemless implants have been developed. The stemless shoulder prosthesis is a new concept in shoulder arthroplasty. The authors review the indications, surgical technique, clinical and radiological midterm results, and complications of these humeral implants. PMID:26151038
Joint detection and localization of multiple anatomical landmarks through learning
NASA Astrophysics Data System (ADS)
Dikmen, Mert; Zhan, Yiqiang; Zhou, Xiang Sean
2008-03-01
Reliable landmark detection in medical images provides the essential groundwork for successful automation of various open problems such as localization, segmentation, and registration of anatomical structures. In this paper, we present a learning-based system to jointly detect (is it there?) and localize (where?) multiple anatomical landmarks in medical images. The contributions of this work exist in two aspects. First, this method takes the advantage from the learning scenario that is able to automatically extract the most distinctive features for multi-landmark detection. Therefore, it is easily adaptable to detect arbitrary landmarks in various kinds of imaging modalities, e.g., CT, MRI and PET. Second, the use of multi-class/cascaded classifier architecture in different phases of the detection stage combined with robust features that are highly efficient in terms of computation time enables a seemingly real time performance, with very high localization accuracy. This method is validated on CT scans of different body sections, e.g., whole body scans, chest scans and abdominal scans. Aside from improved robustness (due to the exploitation of spatial correlations), it gains a run time efficiency in landmark detection. It also shows good scalability performance under increasing number of landmarks.
Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.
2013-01-01
We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967
ADMAP (automatic data manipulation program)
NASA Technical Reports Server (NTRS)
Mann, F. I.
1971-01-01
Instructions are presented on the use of ADMAP, (automatic data manipulation program) an aerospace data manipulation computer program. The program was developed to aid in processing, reducing, plotting, and publishing electric propulsion trajectory data generated by the low thrust optimization program, HILTOP. The program has the option of generating SC4020 electric plots, and therefore requires the SC4020 routines to be available at excution time (even if not used). Several general routines are present, including a cubic spline interpolation routine, electric plotter dash line drawing routine, and single parameter and double parameter sorting routines. Many routines are tailored for the manipulation and plotting of electric propulsion data, including an automatic scale selection routine, an automatic curve labelling routine, and an automatic graph titling routine. Data are accepted from either punched cards or magnetic tape.
2D Automatic body-fitted structured mesh generation using advancing extraction method
USDA-ARS?s Scientific Manuscript database
This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...
2D automatic body-fitted structured mesh generation using advancing extraction method
USDA-ARS?s Scientific Manuscript database
This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like...
Installation and Testing Instructions for the Sandia Automatic Report Generator (ARG).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Clay, Robert L.
Robert L. CLAY Sandia National Laboratories P.O. Box 969 Livermore, CA 94551, U.S.A. rlclay@sandia.gov In this report, we provide detailed and reproducible installation instructions of the Automatic Report Generator (ARG), for both Linux and macOS target platforms.
NASA Astrophysics Data System (ADS)
Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni
Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.
Autonomously generating operations sequences for a Mars Rover using AI-based planning
NASA Technical Reports Server (NTRS)
Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg
2001-01-01
This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.
ERIC Educational Resources Information Center
Arendasy, M.; Sommer, M.
2005-01-01
Two pilot studies (n"1=155, n"2=451) are presented in this article, which were carried out within the development of an item generator for the automatic generation of figural matrices items. The focus of the presented studies was to compare two types of item designs with regard to the effect of variations of the property ''perceptual…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Winkel, D; Bol, GH; Asselen, B van
Purpose: To develop an automated radiotherapy treatment planning and optimization workflow for prostate cancer in order to generate clinical treatment plans. Methods: A fully automated radiotherapy treatment planning and optimization workflow was developed based on the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). To evaluate our method, a retrospective planning study (n=100) was performed on patients treated for prostate cancer with 5 field intensity modulated radiotherapy, receiving a dose of 35×2Gy to the prostate and vesicles and a simultaneous integrated boost of 35×0.2Gy to the prostate only. A comparison was made between the dosimetric values of the automatically andmore » manually generated plans. Operator time to generate a plan and plan efficiency was measured. Results: A comparison of the dosimetric values show that automatically generated plans yield more beneficial dosimetric values. In automatic plans reductions of 43% in the V72Gy of the rectum and 13% in the V72Gy of the bladder are observed when compared to the manually generated plans. Smaller variance in dosimetric values is seen, i.e. the intra- and interplanner variability is decreased. For 97% of the automatically generated plans and 86% of the clinical plans all criteria for target coverage and organs at risk constraints are met. The amount of plan segments and monitor units is reduced by 13% and 9% respectively. Automated planning requires less than one minute of operator time compared to over an hour for manual planning. Conclusion: The automatically generated plans are highly suitable for clinical use. The plans have less variance and a large gain in time efficiency has been achieved. Currently, a pilot study is performed, comparing the preference of the clinician and clinical physicist for the automatic versus manual plan. Future work will include expanding our automated treatment planning method to other tumor sites and develop other automated radiotherapy workflows.« less
Walimbe, Vivek; Shekhar, Raj
2006-12-01
We present an algorithm for automatic elastic registration of three-dimensional (3D) medical images. Our algorithm initially recovers the global spatial mismatch between the reference and floating images, followed by hierarchical octree-based subdivision of the reference image and independent registration of the floating image with the individual subvolumes of the reference image at each hierarchical level. Global as well as local registrations use the six-parameter full rigid-body transformation model and are based on maximization of normalized mutual information (NMI). To ensure robustness of the subvolume registration with low voxel counts, we calculate NMI using a combination of current and prior mutual histograms. To generate a smooth deformation field, we perform direct interpolation of six-parameter rigid-body subvolume transformations obtained at the last subdivision level. Our interpolation scheme involves scalar interpolation of the 3D translations and quaternion interpolation of the 3D rotational pose. We analyzed the performance of our algorithm through experiments involving registration of synthetically deformed computed tomography (CT) images. Our algorithm is general and can be applied to image pairs of any two modalities of most organs. We have demonstrated successful registration of clinical whole-body CT and positron emission tomography (PET) images using this algorithm. The registration accuracy for this application was evaluated, based on validation using expert-identified anatomical landmarks in 15 CT-PET image pairs. The algorithm's performance was comparable to the average accuracy observed for three expert-determined registrations in the same 15 image pairs.
Geometry Processing of Conventionally Produced Mouse Brain Slice Images.
Agarwal, Nitin; Xu, Xiangmin; Gopi, M
2018-04-21
Brain mapping research in most neuroanatomical laboratories relies on conventional processing techniques, which often introduce histological artifacts such as tissue tears and tissue loss. In this paper we present techniques and algorithms for automatic registration and 3D reconstruction of conventionally produced mouse brain slices in a standardized atlas space. This is achieved first by constructing a virtual 3D mouse brain model from annotated slices of Allen Reference Atlas (ARA). Virtual re-slicing of the reconstructed model generates ARA-based slice images corresponding to the microscopic images of histological brain sections. These image pairs are aligned using a geometric approach through contour images. Histological artifacts in the microscopic images are detected and removed using Constrained Delaunay Triangulation before performing global alignment. Finally, non-linear registration is performed by solving Laplace's equation with Dirichlet boundary conditions. Our methods provide significant improvements over previously reported registration techniques for the tested slices in 3D space, especially on slices with significant histological artifacts. Further, as one of the application we count the number of neurons in various anatomical regions using a dataset of 51 microscopic slices from a single mouse brain. To the best of our knowledge the presented work is the first that automatically registers both clean as well as highly damaged high-resolutions histological slices of mouse brain to a 3D annotated reference atlas space. This work represents a significant contribution to this subfield of neuroscience as it provides tools to neuroanatomist for analyzing and processing histological data. Copyright © 2018 Elsevier B.V. All rights reserved.
Moore, C S; Wood, T J; Avery, G; Balcam, S; Needler, L; Beavis, A W; Saunderson, J R
2014-05-07
The purpose of this study was to examine the use of three physical image quality metrics in the calibration of an automatic exposure control (AEC) device for chest radiography with a computed radiography (CR) imaging system. The metrics assessed were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQm), all measured using a uniform chest phantom. Subsequent calibration curves were derived to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated chest images with correct detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated chest images contained clinically realistic projected anatomy and anatomical noise and were scored by experienced image evaluators. Constant DDI and CNR curves do not appear to provide optimized performance across the diagnostic energy range. Conversely, constant eNEQm and SNR do appear to provide optimized performance, with the latter being the preferred calibration metric given as it is easier to measure in practice. Medical physicists may use the SNR image quality metric described here when setting up and optimizing AEC devices for chest radiography CR systems with a degree of confidence that resulting clinical image quality will be adequate for the required clinical task. However, this must be done with close cooperation of expert image evaluators, to ensure appropriate levels of detector air kerma.
NASA Astrophysics Data System (ADS)
Moore, C. S.; Wood, T. J.; Avery, G.; Balcam, S.; Needler, L.; Beavis, A. W.; Saunderson, J. R.
2014-05-01
The purpose of this study was to examine the use of three physical image quality metrics in the calibration of an automatic exposure control (AEC) device for chest radiography with a computed radiography (CR) imaging system. The metrics assessed were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQm), all measured using a uniform chest phantom. Subsequent calibration curves were derived to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated chest images with correct detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated chest images contained clinically realistic projected anatomy and anatomical noise and were scored by experienced image evaluators. Constant DDI and CNR curves do not appear to provide optimized performance across the diagnostic energy range. Conversely, constant eNEQm and SNR do appear to provide optimized performance, with the latter being the preferred calibration metric given as it is easier to measure in practice. Medical physicists may use the SNR image quality metric described here when setting up and optimizing AEC devices for chest radiography CR systems with a degree of confidence that resulting clinical image quality will be adequate for the required clinical task. However, this must be done with close cooperation of expert image evaluators, to ensure appropriate levels of detector air kerma.
Unsupervised MDP Value Selection for Automating ITS Capabilities
ERIC Educational Resources Information Center
Stamper, John; Barnes, Tiffany
2009-01-01
We seek to simplify the creation of intelligent tutors by using student data acquired from standard computer aided instruction (CAI) in conjunction with educational data mining methods to automatically generate adaptive hints. In our previous work, we have automatically generated hints for logic tutoring by constructing a Markov Decision Process…
Automatic Digital Content Generation System for Real-Time Distance Lectures
ERIC Educational Resources Information Center
Iwatsuki, Masami; Takeuchi, Norio; Kobayashi, Hisato; Yana, Kazuo; Takeda, Hiroshi; Yaginuma, Hisashi; Kiyohara, Hajime; Tokuyasu, Akira
2007-01-01
This article describes a new automatic digital content generation system we have developed. Recently some universities, including Hosei University, have been offering students opportunities to take distance interactive classes over the Internet from overseas. When such distance lectures are delivered in English to Japanese students, there is a…
Automatic detection of larynx cancer from contrast-enhanced magnetic resonance images
NASA Astrophysics Data System (ADS)
Doshi, Trushali; Soraghan, John; Grose, Derek; MacKenzie, Kenneth; Petropoulakis, Lykourgos
2015-03-01
Detection of larynx cancer from medical imaging is important for the quantification and for the definition of target volumes in radiotherapy treatment planning (RTP). Magnetic resonance imaging (MRI) is being increasingly used in RTP due to its high resolution and excellent soft tissue contrast. Manually detecting larynx cancer from sequential MRI is time consuming and subjective. The large diversity of cancer in terms of geometry, non-distinct boundaries combined with the presence of normal anatomical regions close to the cancer regions necessitates the development of automatic and robust algorithms for this task. A new automatic algorithm for the detection of larynx cancer from 2D gadoliniumenhanced T1-weighted (T1+Gd) MRI to assist clinicians in RTP is presented. The algorithm employs edge detection using spatial neighborhood information of pixels and incorporates this information in a fuzzy c-means clustering process to robustly separate different tissues types. Furthermore, it utilizes the information of the expected cancerous location for cancer regions labeling. Comparison of this automatic detection system with manual clinical detection on real T1+Gd axial MRI slices of 2 patients (24 MRI slices) with visible larynx cancer yields an average dice similarity coefficient of 0.78+/-0.04 and average root mean square error of 1.82+/-0.28 mm. Preliminary results show that this fully automatic system can assist clinicians in RTP by obtaining quantifiable and non-subjective repeatable detection results in a particular time-efficient and unbiased fashion.
Periodic, On-Demand, and User-Specified Information Reconciliation
NASA Technical Reports Server (NTRS)
Kolano, Paul
2007-01-01
Automated sequence generation (autogen) signifies both a process and software used to automatically generate sequences of commands to operate various spacecraft. Autogen requires fewer workers than are needed for older manual sequence-generation processes and reduces sequence-generation times from weeks to minutes. The autogen software comprises the autogen script plus the Activity Plan Generator (APGEN) program. APGEN can be used for planning missions and command sequences. APGEN includes a graphical user interface that facilitates scheduling of activities on a time line and affords a capability to automatically expand, decompose, and schedule activities.
Applying automatic item generation to create cohesive physics testlets
NASA Astrophysics Data System (ADS)
Mindyarto, B. N.; Nugroho, S. E.; Linuwih, S.
2018-03-01
Computer-based testing has created the demand for large numbers of items. This paper discusses the production of cohesive physics testlets using an automatic item generation concepts and procedures. The testlets were composed by restructuring physics problems to reveal deeper understanding of the underlying physical concepts by inserting a qualitative question and its scientific reasoning question. A template-based testlet generator was used to generate the testlet variants. Using this methodology, 1248 testlet variants were effectively generated from 25 testlet templates. Some issues related to the effective application of the generated physics testlets in practical assessments were discussed.
Hunter, James; Freer, Yvonne; Gatt, Albert; Reiter, Ehud; Sripada, Somayajulu; Sykes, Cindy
2012-11-01
Our objective was to determine whether and how a computer system could automatically generate helpful natural language nursing shift summaries solely from an electronic patient record system, in a neonatal intensive care unit (NICU). A system was developed which automatically generates partial NICU shift summaries (for the respiratory and cardiovascular systems), using data-to-text technology. It was evaluated for 2 months in the NICU at the Royal Infirmary of Edinburgh, under supervision. In an on-ward evaluation, a substantial majority of the summaries was found by outgoing and incoming nurses to be understandable (90%), and a majority was found to be accurate (70%), and helpful (59%). The evaluation also served to identify some outstanding issues, especially with regard to extra content the nurses wanted to see in the computer-generated summaries. It is technically possible automatically to generate limited natural language NICU shift summaries from an electronic patient record. However, it proved difficult to handle electronic data that was intended primarily for display to the medical staff, and considerable engineering effort would be required to create a deployable system from our proof-of-concept software. Copyright © 2012 Elsevier B.V. All rights reserved.
Automatic Query Formulations in Information Retrieval.
ERIC Educational Resources Information Center
Salton, G.; And Others
1983-01-01
Introduces methods designed to reduce role of search intermediaries by generating Boolean search formulations automatically using term frequency considerations from natural language statements provided by system patrons. Experimental results are supplied and methods are described for applying automatic query formulation process in practice.…
Nicholson, Daren T; Chalk, Colin; Funnell, W Robert J; Daniel, Sam J
2006-11-01
The use of computer-generated 3-dimensional (3-D) anatomical models to teach anatomy has proliferated. However, there is little evidence that these models are educationally effective. The purpose of this study was to test the educational effectiveness of a computer-generated 3-D model of the middle and inner ear. We reconstructed a fully interactive model of the middle and inner ear from a magnetic resonance imaging scan of a human cadaver ear. To test the model's educational usefulness, we conducted a randomised controlled study in which 28 medical students completed a Web-based tutorial on ear anatomy that included the interactive model, while a control group of 29 students took the tutorial without exposure to the model. At the end of the tutorials, both groups were asked a series of 15 quiz questions to evaluate their knowledge of 3-D relationships within the ear. The intervention group's mean score on the quiz was 83%, while that of the control group was 65%. This difference in means was highly significant (P < 0.001). Our findings stand in contrast to the handful of previous randomised controlled trials that evaluated the effects of computer-generated 3-D anatomical models on learning. The equivocal and negative results of these previous studies may be due to the limitations of these studies (such as small sample size) as well as the limitations of the models that were studied (such as a lack of full interactivity). Given our positive results, we believe that further research is warranted concerning the educational effectiveness of computer-generated anatomical models.
Severity scores in trauma patients admitted to ICU. Physiological and anatomic models.
Serviá, L; Badia, M; Montserrat, N; Trujillano, J
2018-02-02
The goals of this project were to compare both the anatomic and physiologic severity scores in trauma patients admitted to intensive care unit (ICU), and to elaborate mixed statistical models to improve the precision of the scores. A prospective study of cohorts. The combined medical/surgical ICU in a secondary university hospital. Seven hundred and eighty trauma patients admitted to ICU older than 16 years of age. Anatomic models (ISS and NISS) were compared and combined with physiological models (T-RTS, APACHE II [APII], and MPM II). The probability of death was calculated following the TRISS method. The discrimination was assessed using ROC curves (ABC [CI 95%]), and the calibration using the Hosmer-Lemeshoẃs H test. The mixed models were elaborated with the tree classification method type Chi Square Automatic Interaction Detection. A 14% global mortality was recorded. The physiological models presented the best discrimination values (APII of 0.87 [0.84-0.90]). All models were affected by bad calibration (P<.01). The best mixed model resulted from the combination of APII and ISS (0.88 [0.83-0.90]). This model was able to differentiate between a 7.5% mortality for elderly patients with pathological antecedents and a 25% mortality in patients presenting traumatic brain injury, from a pool of patients with APII values ranging from 10 to 17 and an ISS threshold of 22. The physiological models perform better than the anatomical models in traumatic patients admitted to the ICU. Patients with low scores in the physiological models require an anatomic analysis of the injuries to determine their severity. Copyright © 2017 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.
MeSH indexing based on automatically generated summaries.
Jimeno-Yepes, Antonio J; Plaza, Laura; Mork, James G; Aronson, Alan R; Díaz, Alberto
2013-06-26
MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading.
Automatic generation of user material subroutines for biomechanical growth analysis.
Young, Jonathan M; Yao, Jiang; Ramasubramanian, Ashok; Taber, Larry A; Perucchio, Renato
2010-10-01
The analysis of the biomechanics of growth and remodeling in soft tissues requires the formulation of specialized pseudoelastic constitutive relations. The nonlinear finite element analysis package ABAQUS allows the user to implement such specialized material responses through the coding of a user material subroutine called UMAT. However, hand coding UMAT subroutines is a challenge even for simple pseudoelastic materials and requires substantial time to debug and test the code. To resolve this issue, we develop an automatic UMAT code generation procedure for pseudoelastic materials using the symbolic mathematics package MATHEMATICA and extend the UMAT generator to include continuum growth. The performance of the automatically coded UMAT is tested by simulating the stress-stretch response of a material defined by a Fung-orthotropic strain energy function, subject to uniaxial stretching, equibiaxial stretching, and simple shear in ABAQUS. The MATHEMATICA UMAT generator is then extended to include continuum growth by adding a growth subroutine to the automatically generated UMAT. The MATHEMATICA UMAT generator correctly derives the variables required in the UMAT code, quickly providing a ready-to-use UMAT. In turn, the UMAT accurately simulates the pseudoelastic response. In order to test the growth UMAT, we simulate the growth-based bending of a bilayered bar with differing fiber directions in a nongrowing passive layer. The anisotropic passive layer, being topologically tied to the growing isotropic layer, causes the bending bar to twist laterally. The results of simulations demonstrate the validity of the automatically coded UMAT, used in both standardized tests of hyperelastic materials and for a biomechanical growth analysis.
Automatic detection of regions of interest in mammographic images
NASA Astrophysics Data System (ADS)
Cheng, Erkang; Ling, Haibin; Bakic, Predrag R.; Maidment, Andrew D. A.; Megalooikonomou, Vasileios
2011-03-01
This work is a part of our ongoing study aimed at comparing the topology of anatomical branching structures with the underlying image texture. Detection of regions of interest (ROIs) in clinical breast images serves as the first step in development of an automated system for image analysis and breast cancer diagnosis. In this paper, we have investigated machine learning approaches for the task of identifying ROIs with visible breast ductal trees in a given galactographic image. Specifically, we have developed boosting based framework using the AdaBoost algorithm in combination with Haar wavelet features for the ROI detection. Twenty-eight clinical galactograms with expert annotated ROIs were used for training. Positive samples were generated by resampling near the annotated ROIs, and negative samples were generated randomly by image decomposition. Each detected ROI candidate was given a confidences core. Candidate ROIs with spatial overlap were merged and their confidence scores combined. We have compared three strategies for elimination of false positives. The strategies differed in their approach to combining confidence scores by summation, averaging, or selecting the maximum score.. The strategies were compared based upon the spatial overlap with annotated ROIs. Using a 4-fold cross-validation with the annotated clinical galactographic images, the summation strategy showed the best performance with 75% detection rate. When combining the top two candidates, the selection of maximum score showed the best performance with 96% detection rate.
NASA Astrophysics Data System (ADS)
Ramakrishnan, Sowmya; Alvino, Christopher; Grady, Leo; Kiraly, Atilla
2011-03-01
We present a complete automatic system to extract 3D centerlines of ribs from thoracic CT scans. Our rib centerline system determines the positional information for the rib cage consisting of extracted rib centerlines, spinal canal centerline, pairing and labeling of ribs. We show an application of this output to produce an enhanced visualization of the rib cage by the method of Kiraly et al., in which the ribs are digitally unfolded along their centerlines. The centerline extraction consists of three stages: (a) pre-trace processing for rib localization, (b) rib centerline tracing, and (c) post-trace processing to merge the rib traces. Then we classify ribs from non-ribs and determine anatomical rib labeling. Our novel centerline tracing technique uses the Random Walker algorithm to segment the structural boundary of the rib in successive 2D cross sections orthogonal to the longitudinal direction of the ribs. Then the rib centerline is progressively traced along the rib using a 3D Kalman filter. The rib centerline extraction framework was evaluated on 149 CT datasets with varying slice spacing, dose, and under a variety of reconstruction kernels. The results of the evaluation are presented. The extraction takes approximately 20 seconds on a modern radiology workstation and performs robustly even in the presence of partial volume effects or rib pathologies such as bone metastases or fractures, making the system suitable for assisting clinicians in expediting routine rib reading for oncology and trauma applications.
NASA Astrophysics Data System (ADS)
Lu, Xiaoguang; Xue, Hui; Jolly, Marie-Pierre; Guetter, Christoph; Kellman, Peter; Hsu, Li-Yueh; Arai, Andrew; Zuehlsdorff, Sven; Littmann, Arne; Georgescu, Bogdan; Guehring, Jens
2011-03-01
Cardiac perfusion magnetic resonance imaging (MRI) has proven clinical significance in diagnosis of heart diseases. However, analysis of perfusion data is time-consuming, where automatic detection of anatomic landmarks and key-frames from perfusion MR sequences is helpful for anchoring structures and functional analysis of the heart, leading toward fully automated perfusion analysis. Learning-based object detection methods have demonstrated their capabilities to handle large variations of the object by exploring a local region, i.e., context. Conventional 2D approaches take into account spatial context only. Temporal signals in perfusion data present a strong cue for anchoring. We propose a joint context model to encode both spatial and temporal evidence. In addition, our spatial context is constructed not only based on the landmark of interest, but also the landmarks that are correlated in the neighboring anatomies. A discriminative model is learned through a probabilistic boosting tree. A marginal space learning strategy is applied to efficiently learn and search in a high dimensional parameter space. A fully automatic system is developed to simultaneously detect anatomic landmarks and key frames in both RV and LV from perfusion sequences. The proposed approach was evaluated on a database of 373 cardiac perfusion MRI sequences from 77 patients. Experimental results of a 4-fold cross validation show superior landmark detection accuracies of the proposed joint spatial-temporal approach to the 2D approach that is based on spatial context only. The key-frame identification results are promising.
NASA Astrophysics Data System (ADS)
Rodrigues, Pedro L.; Rodrigues, Nuno F.; Fonseca, Jaime C.; von Krüger, M. A.; Pereira, W. C. A.; Vilaça, João. L.
2015-03-01
Background: Kidney stone is a major universal health problem, affecting 10% of the population worldwide. Percutaneous nephrolithotomy is a first-line and established procedure for disintegration and removal of renal stones. Its surgical success depends on the precise needle puncture of renal calyces, which remains the most challenging task for surgeons. This work describes and tests a new ultrasound based system to alert the surgeon when undesirable anatomical structures are in between the puncture path defined through a tracked needle. Methods: Two circular ultrasound transducers were built with a single 3.3-MHz piezoelectric ceramic PZT SN8, 25.4 mm of radius and resin-epoxy matching and backing layers. One matching layer was designed with a concave curvature to work as an acoustic lens with long focusing. The A-scan signals were filtered and processed to automatically detect reflected echoes. Results: The transducers were mapped in water tank and tested in a study involving 45 phantoms. Each phantom mimics different needle insertion trajectories with a percutaneous path length between 80 and 150 mm. Results showed that the beam cross-sectional area oscillates around the ceramics radius and it was possible to automatically detect echo signals in phantoms with length higher than 80 mm. Conclusions: This new solution may alert the surgeon about anatomical tissues changes during needle insertion, which may decrease the need of X-Ray radiation exposure and ultrasound image evaluation during percutaneous puncture.
Automatic Dance Lesson Generation
ERIC Educational Resources Information Center
Yang, Yang; Leung, H.; Yue, Lihua; Deng, LiQun
2012-01-01
In this paper, an automatic lesson generation system is presented which is suitable in a learning-by-mimicking scenario where the learning objects can be represented as multiattribute time series data. The dance is used as an example in this paper to illustrate the idea. Given a dance motion sequence as the input, the proposed lesson generation…
ERIC Educational Resources Information Center
Chen, Hsinchun; Martinez, Joanne; Kirchhoff, Amy; Ng, Tobun D.; Schatz, Bruce R.
1998-01-01
Grounded on object filtering, automatic indexing, and co-occurrence analysis, an experiment was performed using a parallel supercomputer to analyze over 400,000 abstracts in an INSPEC computer engineering collection. A user evaluation revealed that system-generated thesauri were better than the human-generated INSPEC subject thesaurus in concept…
Automatic Generation of Tests from Domain and Multimedia Ontologies
ERIC Educational Resources Information Center
Papasalouros, Andreas; Kotis, Konstantinos; Kanaris, Konstantinos
2011-01-01
The aim of this article is to present an approach for generating tests in an automatic way. Although other methods have been already reported in the literature, the proposed approach is based on ontologies, representing both domain and multimedia knowledge. The article also reports on a prototype implementation of this approach, which…
Automatic Generation and Ranking of Questions for Critical Review
ERIC Educational Resources Information Center
Liu, Ming; Calvo, Rafael A.; Rus, Vasile
2014-01-01
Critical review skill is one important aspect of academic writing. Generic trigger questions have been widely used to support this activity. When students have a concrete topic in mind, trigger questions are less effective if they are too general. This article presents a learning-to-rank based system which automatically generates specific trigger…
Use of an Automatic Problem Generator to Teach Basic Skills in a First Course in Assembly Language.
ERIC Educational Resources Information Center
Benander, Alan; And Others
1989-01-01
Discussion of the use of computer aided instruction (CAI) and instructional software in college level courses highlights an automatic problem generator, AUTOGEN, that was written for computer science students learning assembly language. Design of the software is explained, and student responses are reported. (nine references) (LRW)
Automatic Generation of Cycle-Approximate TLMs with Timed RTOS Model Support
NASA Astrophysics Data System (ADS)
Hwang, Yonghyun; Schirner, Gunar; Abdi, Samar
This paper presents a technique for automatically generating cycle-approximate transaction level models (TLMs) for multi-process applications mapped to embedded platforms. It incorporates three key features: (a) basic block level timing annotation, (b) RTOS model integration, and (c) RTOS overhead delay modeling. The inputs to TLM generation are application C processes and their mapping to processors in the platform. A processor data model, including pipelined datapath, memory hierarchy and branch delay model is used to estimate basic block execution delays. The delays are annotated to the C code, which is then integrated with a generated SystemC RTOS model. Our abstract RTOS provides dynamic scheduling and inter-process communication (IPC) with processor- and RTOS-specific pre-characterized timing. Our experiments using a MP3 decoder and a JPEG encoder show that timed TLMs, with integrated RTOS models, can be automatically generated in less than a minute. Our generated TLMs simulated three times faster than real-time and showed less than 10% timing error compared to board measurements.
NASA Astrophysics Data System (ADS)
Aziz, Aamer; Hu, Qingmao; Nowinski, Wieslaw L.
2004-04-01
The human cerebral ventricular system is a complex structure that is essential for the well being and changes in which reflect disease. It is clinically imperative that the ventricular system be studied in details. For this reason computer assisted algorithms are essential to be developed. We have developed a novel (patent pending) and robust anatomical knowledge-driven algorithm for automatic extraction of the cerebral ventricular system from MRI. The algorithm is not only unique in its image processing aspect but also incorporates knowledge of neuroanatomy, radiological properties, and variability of the ventricular system. The ventricular system is divided into six 3D regions based on the anatomy and its variability. Within each ventricular region a 2D region of interest (ROI) is defined and is then further subdivided into sub-regions. Various strict conditions that detect and prevent leakage into the extra-ventricular space are specified for each sub-region based on anatomical knowledge. Each ROI is processed to calculate its local statistics, local intensity ranges of cerebrospinal fluid and grey and white matters, set a seed point within the ROI, grow region directionally in 3D, check anti-leakage conditions and correct growing if leakage occurs and connects all unconnected regions grown by relaxing growing conditions. The algorithm was tested qualitatively and quantitatively on normal and pathological MRI cases and worked well. In this paper we discuss in more detail inclusion of anatomical knowledge in the algorithm and usefulness of our approach from clinical perspective.
Lacson, Ronilda C; Barzilay, Regina; Long, William J
2006-10-01
Spoken medical dialogue is a valuable source of information for patients and caregivers. This work presents a first step towards automatic analysis and summarization of spoken medical dialogue. We first abstract a dialogue into a sequence of semantic categories using linguistic and contextual features integrated in a supervised machine-learning framework. Our model has a classification accuracy of 73%, compared to 33% achieved by a majority baseline (p<0.01). We then describe and implement a summarizer that utilizes this automatically induced structure. Our evaluation results indicate that automatically generated summaries exhibit high resemblance to summaries written by humans. In addition, task-based evaluation shows that physicians can reasonably answer questions related to patient care by looking at the automatically generated summaries alone, in contrast to the physicians' performance when they were given summaries from a naïve summarizer (p<0.05). This work demonstrates the feasibility of automatically structuring and summarizing spoken medical dialogue.
Anatomical influences on internally coupled ears in reptiles.
Young, Bruce A
2016-10-01
Many reptiles, and other vertebrates, have internally coupled ears in which a patent anatomical connection allows pressure waves generated by the displacement of one tympanic membrane to propagate (internally) through the head and, ultimately, influence the displacement of the contralateral tympanic membrane. The pattern of tympanic displacement caused by this internal coupling can give rise to novel sensory cues. The auditory mechanics of reptiles exhibit more anatomical variation than in any other vertebrate group. This variation includes structural features such as diverticula and septa, as well as coverings of the tympanic membrane. Many of these anatomical features would likely influence the functional significance of the internal coupling between the tympanic membranes. Several of the anatomical components of the reptilian internally coupled ear are under active motor control, suggesting that in some reptiles the auditory system may be more dynamic than previously recognized.
To develop a flying fish egg inspection system by a digital imaging base system
NASA Astrophysics Data System (ADS)
Chen, Chun-Jen; Jywe, Wenyuh; Hsieh, Tung-Hsien; Chen, Chien Hung
2015-07-01
This paper develops an automatic optical inspection system for flying fish egg quality inspection. The automatic optical inspection system consists of a 2-axes stage, a digital camera, a lens, a LED light source, a vacuum generator, a tube and a tray. This system can automatically find the particle on the flying egg tray and used stage to driver the tube onto the particle. Then use straw and vacuum generator to pick up the particle. The system pick rate is about 30 particles per minute.
Duchateau, Nicolas; Kostantyn Butakov, Constantine Butakoff; Andreu, David; Fernández-Armenta, Juan; Bijnens, Bart; Berruezo, Antonio; Sitges, Marta; Camara, Oscar
2017-01-01
Electro-anatomical maps (EAMs) are commonly acquired in clinical routine for guiding ablation therapies. They provide voltage and activation time information on a 3-D anatomical mesh representation, making them useful for analyzing the electrical activation patterns in specific pathologies. However, the variability between the different acquisitions and anatomies hampers the comparison between different maps. This paper presents two contributions for the analysis of electrical patterns in EAM data from biventricular surfaces of cardiac chambers. The first contribution is an integrated automatic 2-D disk representation (2-D bull’s eye plot) of the left ventricle (LV) and right ventricle (RV) obtained with a quasi-conformal mapping from the 3-D EAM meshes, that allows an analysis of cardiac resynchronization therapy (CRT) lead positioning, interpretation of global (total activation time), and local indices (local activation time (LAT), surrogates of conduction velocity, inter-ventricular, and transmural delays) that characterize changes in the electrical activation pattern. The second contribution is a set of indices derived from the electrical activation: speed maps, computed from LAT values, to study the electrical wave propagation, and histograms of isochrones to analyze regional electrical heterogeneities in the ventricles. We have applied the proposed methods to look for the underlying physiological mechanisms of left bundle branch block (LBBB) and CRT, with the goal of optimizing the therapy by improving CRT response. To better illustrate the benefits of the proposed tools, we created a set of synthetically generated and fully controlled activation patterns, where the proposed representation and indices were validated. Then, the proposed analysis tools are used to analyze EAM data from an experimental swine model of induced LBBB with an implanted CRT device. We have analyzed and compared the electrical activation patterns at baseline, LBBB, and CRT stages in four animals: two without any structural disease and two with an induced infarction. By relating the CRT lead location with electrical dyssynchrony, we evaluated current hypotheses about lead placement in CRT and showed that optimal pacing sites should target the RV lead close to the apex and the LV one distant from it. PMID:29164019
Automatic discovery of cell types and microcircuitry from neural connectomics
Jonas, Eric; Kording, Konrad
2015-01-01
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity, better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets. DOI: http://dx.doi.org/10.7554/eLife.04250.001 PMID:25928186
Automatic discovery of cell types and microcircuitry from neural connectomics
Jonas, Eric; Kording, Konrad
2015-04-30
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity,more » better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets.« less
Computer assisted diagnostic system in tumor radiography.
Faisal, Ahmed; Parveen, Sharmin; Badsha, Shahriar; Sarwar, Hasan; Reza, Ahmed Wasif
2013-06-01
An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.
Automatic discovery of cell types and microcircuitry from neural connectomics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jonas, Eric; Kording, Konrad
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity,more » better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets.« less
Automatic segmentation of mandible in panoramic x-ray.
Abdi, Amir Hossein; Kasaei, Shohreh; Mehdizadeh, Mojdeh
2015-10-01
As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of [Formula: see text] in Dice similarity, specificity, and sensitivity.
An anatomically oriented breast model for MRI
NASA Astrophysics Data System (ADS)
Kutra, Dominik; Bergtholdt, Martin; Sabczynski, Jörg; Dössel, Olaf; Buelow, Thomas
2015-03-01
Breast cancer is the most common cancer in women in the western world. In the breast cancer care-cycle, MRIis e.g. employed in lesion characterization and therapy assessment. Reading of a single three dimensional image or comparing a multitude of such images in a time series is a time consuming task. Radiological reporting is done manually by translating the spatial position of a finding in an image to a generic representation in the form of a breast diagram, outlining quadrants or clock positions. Currently, registration algorithms are employed to aid with the reading and interpretation of longitudinal studies by providing positional correspondence. To aid with the reporting of findings, knowledge about the breast anatomy has to be introduced to translate from patient specific positions to a generic representation. In our approach we fit a geometric primitive, the semi-super-ellipsoid to patient data. Anatomical knowledge is incorporated by fixing the tip of the super-ellipsoid to the mammilla position and constraining its center-point to a reference plane defined by landmarks on the sternum. A coordinate system is then constructed by linearly scaling the fitted super-ellipsoid, defining a unique set of parameters to each point in the image volume. By fitting such a coordinate system to a different image of the same patient, positional correspondence can be generated. We have validated our method on eight pairs of baseline and follow-up scans (16 breasts) that were acquired for the assessment of neo-adjuvant chemotherapy. On average, the location predicted and the actual location of manually set landmarks are within a distance of 5.6 mm. Our proposed method allows for automatic reporting simply by uniformly dividing the super-ellipsoid around its main axis.
Luboz, Vincent; Chabanas, Matthieu; Swider, Pascal; Payan, Yohan
2005-08-01
This paper addresses an important issue raised for the clinical relevance of Computer-Assisted Surgical applications, namely the methodology used to automatically build patient-specific finite element (FE) models of anatomical structures. From this perspective, a method is proposed, based on a technique called the mesh-matching method, followed by a process that corrects mesh irregularities. The mesh-matching algorithm generates patient-specific volume meshes from an existing generic model. The mesh regularization process is based on the Jacobian matrix transform related to the FE reference element and the current element. This method for generating patient-specific FE models is first applied to computer-assisted maxillofacial surgery, and more precisely, to the FE elastic modelling of patient facial soft tissues. For each patient, the planned bone osteotomies (mandible, maxilla, chin) are used as boundary conditions to deform the FE face model, in order to predict the aesthetic outcome of the surgery. Seven FE patient-specific models were successfully generated by our method. For one patient, the prediction of the FE model is qualitatively compared with the patient's post-operative appearance, measured from a computer tomography scan. Then, our methodology is applied to computer-assisted orbital surgery. It is, therefore, evaluated for the generation of 11 patient-specific FE poroelastic models of the orbital soft tissues. These models are used to predict the consequences of the surgical decompression of the orbit. More precisely, an average law is extrapolated from the simulations carried out for each patient model. This law links the size of the osteotomy (i.e. the surgical gesture) and the backward displacement of the eyeball (the consequence of the surgical gesture).
Johansson, Jarkko; Alakurtti, Kati; Joutsa, Juho; Tohka, Jussi; Ruotsalainen, Ulla; Rinne, Juha O
2016-10-01
The striatum is the primary target in regional C-raclopride-PET studies, and despite its small volume, it contains several functional and anatomical subregions. The outcome of the quantitative dopamine receptor study using C-raclopride-PET depends heavily on the quality of the region-of-interest (ROI) definition of these subregions. The aim of this study was to evaluate subregional analysis techniques because new approaches have emerged, but have not yet been compared directly. In this paper, we compared manual ROI delineation with several automatic methods. The automatic methods used either direct clustering of the PET image or individualization of chosen brain atlases on the basis of MRI or PET image normalization. State-of-the-art normalization methods and atlases were applied, including those provided in the FreeSurfer, Statistical Parametric Mapping8, and FSL software packages. Evaluation of the automatic methods was based on voxel-wise congruity with the manual delineations and the test-retest variability and reliability of the outcome measures using data from seven healthy male participants who were scanned twice with C-raclopride-PET on the same day. The results show that both manual and automatic methods can be used to define striatal subregions. Although most of the methods performed well with respect to the test-retest variability and reliability of binding potential, the smallest average test-retest variability and SEM were obtained using a connectivity-based atlas and PET normalization (test-retest variability=4.5%, SEM=0.17). The current state-of-the-art automatic ROI methods can be considered good alternatives for subjective and laborious manual segmentation in C-raclopride-PET studies.
Integrating hidden Markov model and PRAAT: a toolbox for robust automatic speech transcription
NASA Astrophysics Data System (ADS)
Kabir, A.; Barker, J.; Giurgiu, M.
2010-09-01
An automatic time-aligned phone transcription toolbox of English speech corpora has been developed. Especially the toolbox would be very useful to generate robust automatic transcription and able to produce phone level transcription using speaker independent models as well as speaker dependent models without manual intervention. The system is based on standard Hidden Markov Models (HMM) approach and it was successfully experimented over a large audiovisual speech corpus namely GRID corpus. One of the most powerful features of the toolbox is the increased flexibility in speech processing where the speech community would be able to import the automatic transcription generated by HMM Toolkit (HTK) into a popular transcription software, PRAAT, and vice-versa. The toolbox has been evaluated through statistical analysis on GRID data which shows that automatic transcription deviates by an average of 20 ms with respect to manual transcription.
Realistic simulated MRI and SPECT databases. Application to SPECT/MRI registration evaluation.
Aubert-Broche, Berengere; Grova, Christophe; Reilhac, Anthonin; Evans, Alan C; Collins, D Louis
2006-01-01
This paper describes the construction of simulated SPECT and MRI databases that account for realistic anatomical and functional variability. The data is used as a gold-standard to evaluate four SPECT/MRI similarity-based registration methods. Simulation realism was accounted for using accurate physical models of data generation and acquisition. MRI and SPECT simulations were generated from three subjects to take into account inter-subject anatomical variability. Functional SPECT data were computed from six functional models of brain perfusion. Previous models of normal perfusion and ictal perfusion observed in Mesial Temporal Lobe Epilepsy (MTLE) were considered to generate functional variability. We studied the impact noise and intensity non-uniformity in MRI simulations and SPECT scatter correction may have on registration accuracy. We quantified the amount of registration error caused by anatomical and functional variability. Registration involving ictal data was less accurate than registration involving normal data. MR intensity nonuniformity was the main factor decreasing registration accuracy. The proposed simulated database is promising to evaluate many functional neuroimaging methods, involving MRI and SPECT data.
ERIC Educational Resources Information Center
Arendasy, Martin E.; Sommer, Markus
2012-01-01
The use of new test administration technologies such as computerized adaptive testing in high-stakes educational and occupational assessments demands large item pools. Classic item construction processes and previous approaches to automatic item generation faced the problems of a considerable loss of items after the item calibration phase. In this…
2D automatic body-fitted structured mesh generation using advancing extraction method
NASA Astrophysics Data System (ADS)
Zhang, Yaoxin; Jia, Yafei
2018-01-01
This paper presents an automatic mesh generation algorithm for body-fitted structured meshes in Computational Fluids Dynamics (CFD) analysis using the Advancing Extraction Method (AEM). The method is applicable to two-dimensional domains with complex geometries, which have the hierarchical tree-like topography with extrusion-like structures (i.e., branches or tributaries) and intrusion-like structures (i.e., peninsula or dikes). With the AEM, the hierarchical levels of sub-domains can be identified, and the block boundary of each sub-domain in convex polygon shape in each level can be extracted in an advancing scheme. In this paper, several examples were used to illustrate the effectiveness and applicability of the proposed algorithm for automatic structured mesh generation, and the implementation of the method.
Automatic control system generation for robot design validation
NASA Technical Reports Server (NTRS)
Bacon, James A. (Inventor); English, James D. (Inventor)
2012-01-01
The specification and drawings present a new method, system and software product for and apparatus for generating a robotic validation system for a robot design. The robotic validation system for the robot design of a robotic system is automatically generated by converting a robot design into a generic robotic description using a predetermined format, then generating a control system from the generic robotic description and finally updating robot design parameters of the robotic system with an analysis tool using both the generic robot description and the control system.
Automated feature extraction for retinal vascular biometry in zebrafish using OCT angiography
NASA Astrophysics Data System (ADS)
Bozic, Ivan; Rao, Gopikrishna M.; Desai, Vineet; Tao, Yuankai K.
2017-02-01
Zebrafish have been identified as an ideal model for angiogenesis because of anatomical and functional similarities with other vertebrates. The scale and complexity of zebrafish assays are limited by the need to manually treat and serially screen animals, and recent technological advances have focused on automation and improving throughput. Here, we use optical coherence tomography (OCT) and OCT angiography (OCT-A) to perform noninvasive, in vivo imaging of retinal vasculature in zebrafish. OCT-A summed voxel projections were low pass filtered and skeletonized to create an en face vascular map prior to connectivity analysis. Vascular segmentation was referenced to the optic nerve head (ONH), which was identified by automatically segmenting the retinal pigment epithelium boundary on the OCT structural volume. The first vessel branch generation was identified as skeleton segments with branch points closest to the ONH, and subsequent generations were found iteratively by expanding the search space outwards from the ONH. Biometric parameters, including length, curvature, and branch angle of each vessel segment were calculated and grouped by branch generation. Despite manual handling and alignment of each animal over multiple time points, we observe distinct qualitative patterns that enable unique identification of each eye from individual animals. We believe this OCT-based retinal biometry method can be applied for automated animal identification and handling in high-throughput organism-level pharmacological assays and genetic screens. In addition, these extracted features may enable high-resolution quantification of longitudinal vascular changes as a method for studying zebrafish models of retinal neovascularization and vascular remodeling.
Label fusion based brain MR image segmentation via a latent selective model
NASA Astrophysics Data System (ADS)
Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu
2018-04-01
Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.
NASA Astrophysics Data System (ADS)
Dore, C.; Murphy, M.
2013-02-01
This paper outlines a new approach for generating digital heritage models from laser scan or photogrammetric data using Historic Building Information Modelling (HBIM). HBIM is a plug-in for Building Information Modelling (BIM) software that uses parametric library objects and procedural modelling techniques to automate the modelling stage. The HBIM process involves a reverse engineering solution whereby parametric interactive objects representing architectural elements are mapped onto laser scan or photogrammetric survey data. A library of parametric architectural objects has been designed from historic manuscripts and architectural pattern books. These parametric objects were built using an embedded programming language within the ArchiCAD BIM software called Geometric Description Language (GDL). Procedural modelling techniques have been implemented with the same language to create a parametric building façade which automatically combines library objects based on architectural rules and proportions. Different configurations of the façade are controlled by user parameter adjustment. The automatically positioned elements of the façade can be subsequently refined using graphical editing while overlaying the model with orthographic imagery. Along with this semi-automatic method for generating façade models, manual plotting of library objects can also be used to generate a BIM model from survey data. After the 3D model has been completed conservation documents such as plans, sections, elevations and 3D views can be automatically generated for conservation projects.
Automatic corpus callosum segmentation for standardized MR brain scanning
NASA Astrophysics Data System (ADS)
Xu, Qing; Chen, Hong; Zhang, Li; Novak, Carol L.
2007-03-01
Magnetic Resonance (MR) brain scanning is often planned manually with the goal of aligning the imaging plane with key anatomic landmarks. The planning is time-consuming and subject to inter- and intra- operator variability. An automatic and standardized planning of brain scans is highly useful for clinical applications, and for maximum utility should work on patients of all ages. In this study, we propose a method for fully automatic planning that utilizes the landmarks from two orthogonal images to define the geometry of the third scanning plane. The corpus callosum (CC) is segmented in sagittal images by an active shape model (ASM), and the result is further improved by weighting the boundary movement with confidence scores and incorporating region based refinement. Based on the extracted contour of the CC, several important landmarks are located and then combined with landmarks from the coronal or transverse plane to define the geometry of the third plane. Our automatic method is tested on 54 MR images from 24 patients and 3 healthy volunteers, with ages ranging from 4 months to 70 years old. The average accuracy with respect to two manually labeled points on the CC is 3.54 mm and 4.19 mm, and differed by an average of 2.48 degrees from the orientation of the line connecting them, demonstrating that our method is sufficiently accurate for clinical use.
Urschler, Martin; Grassegger, Sabine; Štern, Darko
2015-01-01
Age estimation of individuals is important in human biology and has various medical and forensic applications. Recent interest in MR-based methods aims to investigate alternatives for established methods involving ionising radiation. Automatic, software-based methods additionally promise improved estimation objectivity. To investigate how informative automatically selected image features are regarding their ability to discriminate age, by exploring a recently proposed software-based age estimation method for MR images of the left hand and wrist. One hundred and two MR datasets of left hand images are used to evaluate age estimation performance, consisting of bone and epiphyseal gap volume localisation, computation of one age regression model per bone mapping image features to age and fusion of individual bone age predictions to a final age estimate. Quantitative results of the software-based method show an age estimation performance with a mean absolute difference of 0.85 years (SD = 0.58 years) to chronological age, as determined by a cross-validation experiment. Qualitatively, it is demonstrated how feature selection works and which image features of skeletal maturation are automatically chosen to model the non-linear regression function. Feasibility of automatic age estimation based on MRI data is shown and selected image features are found to be informative for describing anatomical changes during physical maturation in male adolescents.
A benchmark for comparison of dental radiography analysis algorithms.
Wang, Ching-Wei; Huang, Cheng-Ta; Lee, Jia-Hong; Li, Chung-Hsing; Chang, Sheng-Wei; Siao, Ming-Jhih; Lai, Tat-Ming; Ibragimov, Bulat; Vrtovec, Tomaž; Ronneberger, Olaf; Fischer, Philipp; Cootes, Tim F; Lindner, Claudia
2016-07-01
Dental radiography plays an important role in clinical diagnosis, treatment and surgery. In recent years, efforts have been made on developing computerized dental X-ray image analysis systems for clinical usages. A novel framework for objective evaluation of automatic dental radiography analysis algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2015 Bitewing Radiography Caries Detection Challenge and Cephalometric X-ray Image Analysis Challenge. In this article, we present the datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. The main contributions of the challenge include the creation of the dental anatomy data repository of bitewing radiographs, the creation of the anatomical abnormality classification data repository of cephalometric radiographs, and the definition of objective quantitative evaluation for comparison and ranking of the algorithms. With this benchmark, seven automatic methods for analysing cephalometric X-ray image and two automatic methods for detecting bitewing radiography caries have been compared, and detailed quantitative evaluation results are presented in this paper. Based on the quantitative evaluation results, we believe automatic dental radiography analysis is still a challenging and unsolved problem. The datasets and the evaluation software will be made available to the research community, further encouraging future developments in this field. (http://www-o.ntust.edu.tw/~cweiwang/ISBI2015/). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
LIMSI @ 2014 Clinical Decision Support Track
2014-11-01
MeSH and BoW runs) was based on the automatic generation of disease hypotheses for which we used data from OrphaNet [4] and the Disease Symptom Knowledge...with the MeSH terms of the top 5 disease hypotheses generated for the case reports. Compared to the other participants we achieved low scores...clinical question types. Query expansion (for both MeSH and BoW runs) was based on the automatic generation of disease hypotheses for which we used data
van Tellingen, C
2009-04-01
The development in cardiovascular anatomy and physiology is described from a Dutch perspective. The newly formed Republic in the 17th century, with its pragmatism and business-like character, became an ideal breeding ground for Descartes' new philosophy. His separation of body and soul provided a mechanistic model of body structure and formed a firm basis for anatomical and physiological research to become catalysts for a tempestuous growth and progress in medicine. (Neth Heart J 2009;17:130-5.).
Accuracy assessment of building point clouds automatically generated from iphone images
NASA Astrophysics Data System (ADS)
Sirmacek, B.; Lindenbergh, R.
2014-06-01
Low-cost sensor generated 3D models can be useful for quick 3D urban model updating, yet the quality of the models is questionable. In this article, we evaluate the reliability of an automatic point cloud generation method using multi-view iPhone images or an iPhone video file as an input. We register such automatically generated point cloud on a TLS point cloud of the same object to discuss accuracy, advantages and limitations of the iPhone generated point clouds. For the chosen example showcase, we have classified 1.23% of the iPhone point cloud points as outliers, and calculated the mean of the point to point distances to the TLS point cloud as 0.11 m. Since a TLS point cloud might also include measurement errors and noise, we computed local noise values for the point clouds from both sources. Mean (μ) and standard deviation (σ) of roughness histograms are calculated as (μ1 = 0.44 m., σ1 = 0.071 m.) and (μ2 = 0.025 m., σ2 = 0.037 m.) for the iPhone and TLS point clouds respectively. Our experimental results indicate possible usage of the proposed automatic 3D model generation framework for 3D urban map updating, fusion and detail enhancing, quick and real-time change detection purposes. However, further insights should be obtained first on the circumstances that are needed to guarantee a successful point cloud generation from smartphone images.
Estimate of Space Radiation-Induced Cancer Risks for International Space Station Orbits
NASA Technical Reports Server (NTRS)
Wu, Honglu; Atwell, William; Cucinotta, Francis A.; Yang, Chui-hsu
1996-01-01
Excess cancer risks from exposures to space radiation are estimated for various orbits of the International Space Station (ISS). Organ exposures are computed with the transport codes, BRYNTRN and HZETRN, and the computerized anatomical male and computerized anatomical female models. Cancer risk coefficients in the National Council on Radiation Protection and Measurements report No. 98 are used to generate lifetime excess cancer incidence and cancer mortality after a one-month mission to ISS. The generated data are tabulated to serve as a quick reference for assessment of radiation risk to astronauts on ISS missions.
Yin, Xiao-Han; Sterck, Frank; Hao, Guang-You
2018-04-23
Some temperate tree species mitigate the negative impacts of frost-induced xylem cavitation by restoring impaired hydraulic function via positive pressures, and may therefore be more resistant to frost fatigue (the phenomenon that post-freezing xylem becomes more susceptible to hydraulic dysfunction) than nonpressure-generating species. We test this hypothesis and investigate underlying anatomical/physiological mechanisms. Using a common garden experiment, we studied key hydraulic traits and detailed xylem anatomical characteristics of 18 sympatric tree species. These species belong to three functional groups, that is, one generating both root and stem pressures (RSP), one generating only root pressure (RP), and one unable to generate such pressures (NP). The three functional groups diverged substantially in hydraulic efficiency, resistance to drought-induced cavitation, and frost fatigue resistance. Most notably, RSP and RP were more resistant to frost fatigue than NP, but this was at the cost of reduced hydraulic conductivity for RSP and reduced resistance to drought-induced cavitation for RP. Our results show that, in environments with strong frost stress: these groups diverge in hydraulic functioning following multiple trade-offs between hydraulic efficiency, resistance to drought and resistance to frost fatigue; and how differences in anatomical characteristics drive such divergence across species. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
Panser, Karin; Tirian, Laszlo; Schulze, Florian; Villalba, Santiago; Jefferis, Gregory S X E; Bühler, Katja; Straw, Andrew D
2016-08-08
Identifying distinct anatomical structures within the brain and developing genetic tools to target them are fundamental steps for understanding brain function. We hypothesize that enhancer expression patterns can be used to automatically identify functional units such as neuropils and fiber tracts. We used two recent, genome-scale Drosophila GAL4 libraries and associated confocal image datasets to segment large brain regions into smaller subvolumes. Our results (available at https://strawlab.org/braincode) support this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. The basis for the structural assignment is clustering of voxels based on patterns of enhancer expression. These initial clusters are agglomerated to make hierarchical predictions of structure. We applied the algorithm to central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 11 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Harith, Hazreen; Schmutz, Beat; Malekani, Javad; Schuetz, Michael A; Yarlagadda, Prasad K
2016-03-01
Anatomically precontoured plates are commonly used to treat periarticular fractures. A well-fitting plate can be used as a tool for anatomical reduction of the fractured bone. Recent studies highlighted that some plates fit poorly for many patients due to considerable shape variations between bones of the same anatomical site. While it is impossible to design one shape that fits all, it is also burdensome for the manufacturers and hospitals to produce, store and manage multiple plate shapes without the certainty of utilization by a patient population. In this study, we investigated the number of shapes required for maximum fit within a given dataset, and if they could be obtained by manually deforming the original plate. A distal medial tibial plate was automatically positioned on 45 individual tibiae, and the optimal deformation was determined iteratively using finite element analysis simulation. Within the studied dataset, we found that: (i) 89% fit could be achieved with four shapes, (ii) 100% fit was impossible through mechanical deformation, and (iii) the deformations required to obtain the four plate shapes were safe for the stainless steel plate for further clinical use. The proposed framework is easily transferable to other orthopaedic plates. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Automatic Implementation of Ttethernet-Based Time-Triggered Avionics Applications
NASA Astrophysics Data System (ADS)
Gorcitz, Raul Adrian; Carle, Thomas; Lesens, David; Monchaux, David; Potop-Butucaruy, Dumitru; Sorel, Yves
2015-09-01
The design of safety-critical embedded systems such as those used in avionics still involves largely manual phases. But in avionics the definition of standard interfaces embodied in standards such as ARINC 653 or TTEthernet should allow the definition of fully automatic code generation flows that reduce the costs while improving the quality of the generated code, much like compilers have done when replacing manual assembly coding. In this paper, we briefly present such a fully automatic implementation tool, called Lopht, for ARINC653-based time-triggered systems, and then explain how it is currently extended to include support for TTEthernet networks.
Automatic system for 3D reconstruction of the chick eye based on digital photographs.
Wong, Alexander; Genest, Reno; Chandrashekar, Naveen; Choh, Vivian; Irving, Elizabeth L
2012-01-01
The geometry of anatomical specimens is very complex and accurate 3D reconstruction is important for morphological studies, finite element analysis (FEA) and rapid prototyping. Although magnetic resonance imaging, computed tomography and laser scanners can be used for reconstructing biological structures, the cost of the equipment is fairly high and specialised technicians are required to operate the equipment, making such approaches limiting in terms of accessibility. In this paper, a novel automatic system for 3D surface reconstruction of the chick eye from digital photographs of a serially sectioned specimen is presented as a potential cost-effective and practical alternative. The system is designed to allow for automatic detection of the external surface of the chick eye. Automatic alignment of the photographs is performed using a combination of coloured markers and an algorithm based on complex phase order likelihood that is robust to noise and illumination variations. Automatic segmentation of the external boundaries of the eye from the aligned photographs is performed using a novel level-set segmentation approach based on a complex phase order energy functional. The extracted boundaries are sampled to construct a 3D point cloud, and a combination of Delaunay triangulation and subdivision surfaces is employed to construct the final triangular mesh. Experimental results using digital photographs of the chick eye show that the proposed system is capable of producing accurate 3D reconstructions of the external surface of the eye. The 3D model geometry is similar to a real chick eye and could be used for morphological studies and FEA.
Automatic left-atrial segmentation from cardiac 3D ultrasound: a dual-chamber model-based approach
NASA Astrophysics Data System (ADS)
Almeida, Nuno; Sarvari, Sebastian I.; Orderud, Fredrik; Gérard, Olivier; D'hooge, Jan; Samset, Eigil
2016-04-01
In this paper, we present an automatic solution for segmentation and quantification of the left atrium (LA) from 3D cardiac ultrasound. A model-based framework is applied, making use of (deformable) active surfaces to model the endocardial surfaces of cardiac chambers, allowing incorporation of a priori anatomical information in a simple fashion. A dual-chamber model (LA and left ventricle) is used to detect and track the atrio-ventricular (AV) plane, without any user input. Both chambers are represented by parametric surfaces and a Kalman filter is used to fit the model to the position of the endocardial walls detected in the image, providing accurate detection and tracking during the whole cardiac cycle. This framework was tested in 20 transthoracic cardiac ultrasound volumetric recordings of healthy volunteers, and evaluated using manual traces of a clinical expert as a reference. The 3D meshes obtained with the automatic method were close to the reference contours at all cardiac phases (mean distance of 0.03+/-0.6 mm). The AV plane was detected with an accuracy of -0.6+/-1.0 mm. The LA volumes assessed automatically were also in agreement with the reference (mean +/-1.96 SD): 0.4+/-5.3 ml, 2.1+/-12.6 ml, and 1.5+/-7.8 ml at end-diastolic, end-systolic and pre-atrial-contraction frames, respectively. This study shows that the proposed method can be used for automatic volumetric assessment of the LA, considerably reducing the analysis time and effort when compared to manual analysis.
Spine detection in CT and MR using iterated marginal space learning.
Michael Kelm, B; Wels, Michael; Kevin Zhou, S; Seifert, Sascha; Suehling, Michael; Zheng, Yefeng; Comaniciu, Dorin
2013-12-01
Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and Computed Tomography (CT), often require a precise three-dimensional positioning, angulation and labeling of the spinal disks and the vertebrae. A fully automatic and robust approach is a prerequisite for an automated scan alignment as well as for the segmentation and analysis of spinal disks and vertebral bodies in Computer Aided Diagnosis (CAD) applications. In this article, we present a novel method that combines Marginal Space Learning (MSL), a recently introduced concept for efficient discriminative object detection, with a generative anatomical network that incorporates relative pose information for the detection of multiple objects. It is used to simultaneously detect and label the spinal disks. While a novel iterative version of MSL is used to quickly generate candidate detections comprising position, orientation, and scale of the disks with high sensitivity, the anatomical network selects the most likely candidates using a learned prior on the individual nine dimensional transformation spaces. Finally, we propose an optional case-adaptive segmentation approach that allows to segment the spinal disks and vertebrae in MR and CT respectively. Since the proposed approaches are learning-based, they can be trained for MR or CT alike. Experimental results based on 42 MR and 30 CT volumes show that our system not only achieves superior accuracy but also is among the fastest systems of its kind in the literature. On the MR data set the spinal disks of a whole spine are detected in 11.5s on average with 98.6% sensitivity and 0.073 false positive detections per volume. On the CT data a comparable sensitivity of 98.0% with 0.267 false positives is achieved. Detected disks are localized with an average position error of 2.4 mm/3.2 mm and angular error of 3.9°/4.5° in MR/CT, which is close to the employed hypothesis resolution of 2.1 mm and 3.3°. Copyright © 2012 Elsevier B.V. All rights reserved.
Enhancing the Automatic Generation of Hints with Expert Seeding
ERIC Educational Resources Information Center
Stamper, John; Barnes, Tiffany; Croy, Marvin
2011-01-01
The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…
The Automation of Stochastization Algorithm with Use of SymPy Computer Algebra Library
NASA Astrophysics Data System (ADS)
Demidova, Anastasya; Gevorkyan, Migran; Kulyabov, Dmitry; Korolkova, Anna; Sevastianov, Leonid
2018-02-01
SymPy computer algebra library is used for automatic generation of ordinary and stochastic systems of differential equations from the schemes of kinetic interaction. Schemes of this type are used not only in chemical kinetics but also in biological, ecological and technical models. This paper describes the automatic generation algorithm with an emphasis on application details.
NASA Astrophysics Data System (ADS)
Möller, Thomas; Bellin, Knut; Creutzburg, Reiner
2015-03-01
The aim of this paper is to show the recent progress in the design and prototypical development of a software suite Copra Breeder* for semi-automatic generation of test methodologies and security checklists for IT vulnerability assessment in small and medium-sized enterprises.
Automatic rule generation for high-level vision
NASA Technical Reports Server (NTRS)
Rhee, Frank Chung-Hoon; Krishnapuram, Raghu
1992-01-01
Many high-level vision systems use rule-based approaches to solving problems such as autonomous navigation and image understanding. The rules are usually elaborated by experts. However, this procedure may be rather tedious. In this paper, we propose a method to generate such rules automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.
Regulation and Measurement of the Heat Generated by Automatic Tooth Preparation in a Confined Space.
Yuan, Fusong; Zheng, Jianqiao; Sun, Yuchun; Wang, Yong; Lyu, Peijun
2017-06-01
The aim of this study was to assess and regulate heat generation in the dental pulp cavity and circumambient temperature around a tooth during laser ablation with a femtosecond laser in a confined space. The automatic tooth preparing technique is one of the traditional oral clinical technology innovations. In this technique, a robot controlled an ultrashort pulse laser to automatically complete the three-dimensional teeth preparing in a confined space. The temperature control is the main measure for protecting the tooth nerve. Ten tooth specimens were irradiated with a femtosecond laser controlled by a robot in a confined space to generate 10 teeth preparation. During the process, four thermocouple sensors were used to record the pulp cavity and circumambient environment temperatures with or without air cooling. A statistical analysis of the temperatures was performed between the conditions with and without air cooling (p < 0.05). The recordings showed that the temperature with air cooling was lower than that without air cooling and that the heat generated in the pulp cavity was lower than the threshold for dental pulp damage. These results indicate that femtosecond laser ablation with air cooling might be an appropriate method for automatic tooth preparing.
Richard, Jocelyn M.; Plawecki, Andrea M.; Berridge, Kent C.
2013-01-01
Intense fearful behavior and/or intense appetitive eating behavior can be generated by localized amino acid inhibitions along a rostrocaudal anatomical gradient within medial shell of nucleus accumbens of the rat. This can be produced by microinjections in medial shell of either the GABAA agonist muscimol (mimicking intrinsic GABAergic inputs) or the AMPA antagonist DNQX (disrupting corticolimbic glutamate inputs). At rostral sites in medial shell, each drug robustly stimulates appetitive eating and food intake, whereas at more caudal sites the same drugs instead produce increasingly fearful behaviors such as escape, distress vocalizations, and defensive treading (an antipredator behavior rodents emit to snakes and scorpions). Previously we showed that intense motivated behaviors generated by glutamate blockade require local endogenous dopamine and can be modulated in valence by environmental ambience. Here we investigated whether GABAergic generation of intense appetitive and fearful motivations similarly depends on local dopamine signals, and whether the valence of motivations generated by GABAergic inhibition can also be retuned by changes in environmental ambience. We report that the answer to both questions is ‘no’. Eating and fear generated by GABAergic inhibition of accumbens shell does not need endogenous dopamine. Also, the appetitive/fearful valence generated by GABAergic muscimol microinjections resists environmental retuning and is determined almost purely by rostrocaudal anatomical placement. These results suggest that NAc GABAergic release of fear and eating are relatively independent of modulatory dopamine signals, and more anatomically pre-determined in valence balance than release of the same intense behaviors by glutamate disruptions. PMID:23551138
MeSH indexing based on automatically generated summaries
2013-01-01
Background MEDLINE citations are manually indexed at the U.S. National Library of Medicine (NLM) using as reference the Medical Subject Headings (MeSH) controlled vocabulary. For this task, the human indexers read the full text of the article. Due to the growth of MEDLINE, the NLM Indexing Initiative explores indexing methodologies that can support the task of the indexers. Medical Text Indexer (MTI) is a tool developed by the NLM Indexing Initiative to provide MeSH indexing recommendations to indexers. Currently, the input to MTI is MEDLINE citations, title and abstract only. Previous work has shown that using full text as input to MTI increases recall, but decreases precision sharply. We propose using summaries generated automatically from the full text for the input to MTI to use in the task of suggesting MeSH headings to indexers. Summaries distill the most salient information from the full text, which might increase the coverage of automatic indexing approaches based on MEDLINE. We hypothesize that if the results were good enough, manual indexers could possibly use automatic summaries instead of the full texts, along with the recommendations of MTI, to speed up the process while maintaining high quality of indexing results. Results We have generated summaries of different lengths using two different summarizers, and evaluated the MTI indexing on the summaries using different algorithms: MTI, individual MTI components, and machine learning. The results are compared to those of full text articles and MEDLINE citations. Our results show that automatically generated summaries achieve similar recall but higher precision compared to full text articles. Compared to MEDLINE citations, summaries achieve higher recall but lower precision. Conclusions Our results show that automatic summaries produce better indexing than full text articles. Summaries produce similar recall to full text but much better precision, which seems to indicate that automatic summaries can efficiently capture the most important contents within the original articles. The combination of MEDLINE citations and automatically generated summaries could improve the recommendations suggested by MTI. On the other hand, indexing performance might be dependent on the MeSH heading being indexed. Summarization techniques could thus be considered as a feature selection algorithm that might have to be tuned individually for each MeSH heading. PMID:23802936
Planning applications in image analysis
NASA Technical Reports Server (NTRS)
Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.
1994-01-01
We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.
Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources
Xu, Yan; Hua, Ji; Ni, Zhaoheng; Chen, Qinlang; Fan, Yubo; Ananiadou, Sophia; Chang, Eric I-Chao; Tsujii, Junichi
2014-01-01
References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs) work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments) with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available. PMID:25343498
Three-dimensional automatic computer-aided evaluation of pleural effusions on chest CT images
NASA Astrophysics Data System (ADS)
Bi, Mark; Summers, Ronald M.; Yao, Jianhua
2011-03-01
The ability to estimate the volume of pleural effusions is desirable as it can provide information about the severity of the condition and the need for thoracentesis. We present here an improved version of an automated program to measure the volume of pleural effusions using regular chest CT images. First, the lungs are segmented using region growing, mathematical morphology, and anatomical knowledge. The visceral and parietal layers of the pleura are then extracted based on anatomical landmarks, curve fitting and active contour models. The liver and compressed tissues are segmented out using thresholding. The pleural space is then fitted to a Bezier surface which is subsequently projected onto the individual two-dimensional slices. Finally, the volume of the pleural effusion is quantified. Our method was tested on 15 chest CT studies and validated against three separate manual tracings. The Dice coefficients were 0.74+/-0.07, 0.74+/-0.08, and 0.75+/-0.07 respectively, comparable to the variation between two different manual tracings.
Automated liver segmentation using a normalized probabilistic atlas
NASA Astrophysics Data System (ADS)
Linguraru, Marius George; Li, Zhixi; Shah, Furhawn; Chin, See; Summers, Ronald M.
2009-02-01
Probabilistic atlases of anatomical organs, especially the brain and the heart, have become popular in medical image analysis. We propose the construction of probabilistic atlases which retain structural variability by using a size-preserving modified affine registration. The organ positions are modeled in the physical space by normalizing the physical organ locations to an anatomical landmark. In this paper, a liver probabilistic atlas is constructed and exploited to automatically segment liver volumes from abdominal CT data. The atlas is aligned with the patient data through a succession of affine and non-linear registrations. The overlap and correlation with manual segmentations are 0.91 (0.93 DICE coefficient) and 0.99 respectively. Little work has taken place on the integration of volumetric measures of liver abnormality to clinical evaluations, which rely on linear estimates of liver height. Our application measures the liver height at the mid-hepatic line (0.94 correlation with manual measurements) and indicates that its combination with volumetric estimates could assist the development of a noninvasive tool to assess hepatomegaly.
Adaptive geodesic transform for segmentation of vertebrae on CT images
NASA Astrophysics Data System (ADS)
Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang
2014-03-01
Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.
Modeling prostate anatomy from multiple view TRUS images for image-guided HIFU therapy.
Penna, Michael A; Dines, Kris A; Seip, Ralf; Carlson, Roy F; Sanghvi, Narendra T
2007-01-01
Current planning methods for transrectal high-intensity focused ultrasound treatment of prostate cancer rely on manually defining treatment regions in 15-20 sector transrectal ultrasound (TRUS) images of the prostate. Although effective, it is desirable to reduce user interaction time by identifying functionally related anatomic structures (segmenting), then automatically laying out treatment sites using these structures as a guide. Accordingly, a method has been developed to effectively generate solid three-dimensional (3-D) models of the prostate, urethra, and rectal wall from boundary trace data. Modeling the urethra and rectal wall are straightforward, but modeling the prostate is more difficult and has received much attention in the literature. New results presented here are aimed at overcoming many of the limitations of previous approaches to modeling the prostate while using boundary traces obtained via manual tracing in as few as 5 sector and 3 linear images. The results presented here are based on a new type of surface, the Fourier ellipsoid, and the use of sector and linear TRUS images. Tissue-specific 3-D models will ultimately permit finer control of energy deposition and more selective destruction of cancerous regions while sparing critical neighboring structures.
Shear-Wave Elastography: Basic Physics and Musculoskeletal Applications.
Taljanovic, Mihra S; Gimber, Lana H; Becker, Giles W; Latt, L Daniel; Klauser, Andrea S; Melville, David M; Gao, Liang; Witte, Russell S
2017-01-01
In the past 2 decades, sonoelastography has been progressively used as a tool to help evaluate soft-tissue elasticity and add to information obtained with conventional gray-scale and Doppler ultrasonographic techniques. Recently introduced on clinical scanners, shear-wave elastography (SWE) is considered to be more objective, quantitative, and reproducible than compression sonoelastography with increasing applications to the musculoskeletal system. SWE uses an acoustic radiation force pulse sequence to generate shear waves, which propagate perpendicular to the ultrasound beam, causing transient displacements. The distribution of shear-wave velocities at each pixel is directly related to the shear modulus, an absolute measure of the tissue's elastic properties. Shear-wave images are automatically coregistered with standard B-mode images to provide quantitative color elastograms with anatomic specificity. Shear waves propagate faster through stiffer contracted tissue, as well as along the long axis of tendon and muscle. SWE has a promising role in determining the severity of disease and treatment follow-up of various musculoskeletal tissues including tendons, muscles, nerves, and ligaments. This article describes the basic ultrasound physics of SWE and its applications in the evaluation of various traumatic and pathologic conditions of the musculoskeletal system. © RSNA, 2017.
Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A
2013-01-01
The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.
Semi-quantitative assessment of pulmonary perfusion in children using dynamic contrast-enhanced MRI
NASA Astrophysics Data System (ADS)
Fetita, Catalin; Thong, William E.; Ou, Phalla
2013-03-01
This paper addresses the study of semi-quantitative assessment of pulmonary perfusion acquired from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in a study population mainly composed of children with pulmonary malformations. The automatic analysis approach proposed is based on the indicator-dilution theory introduced in 1954. First, a robust method is developed to segment the pulmonary artery and the lungs from anatomical MRI data, exploiting 2D and 3D mathematical morphology operators. Second, the time-dependent contrast signal of the lung regions is deconvolved by the arterial input function for the assessment of the local hemodynamic system parameters, ie. mean transit time, pulmonary blood volume and pulmonary blood flow. The discrete deconvolution method implements here a truncated singular value decomposition (tSVD) method. Parametric images for the entire lungs are generated as additional elements for diagnosis and quantitative follow-up. The preliminary results attest the feasibility of perfusion quantification in pulmonary DCE-MRI and open an interesting alternative to scintigraphy for this type of evaluation, to be considered at least as a preliminary decision in the diagnostic due to the large availability of the technique and to the non-invasive aspects.
Shear-Wave Elastography: Basic Physics and Musculoskeletal Applications
Gimber, Lana H.; Becker, Giles W.; Latt, L. Daniel; Klauser, Andrea S.; Melville, David M.; Gao, Liang; Witte, Russell S.
2017-01-01
In the past 2 decades, sonoelastography has been progressively used as a tool to help evaluate soft-tissue elasticity and add to information obtained with conventional gray-scale and Doppler ultrasonographic techniques. Recently introduced on clinical scanners, shear-wave elastography (SWE) is considered to be more objective, quantitative, and reproducible than compression sonoelastography with increasing applications to the musculoskeletal system. SWE uses an acoustic radiation force pulse sequence to generate shear waves, which propagate perpendicular to the ultrasound beam, causing transient displacements. The distribution of shear-wave velocities at each pixel is directly related to the shear modulus, an absolute measure of the tissue’s elastic properties. Shear-wave images are automatically coregistered with standard B-mode images to provide quantitative color elastograms with anatomic specificity. Shear waves propagate faster through stiffer contracted tissue, as well as along the long axis of tendon and muscle. SWE has a promising role in determining the severity of disease and treatment follow-up of various musculoskeletal tissues including tendons, muscles, nerves, and ligaments. This article describes the basic ultrasound physics of SWE and its applications in the evaluation of various traumatic and pathologic conditions of the musculoskeletal system. ©RSNA, 2017 PMID:28493799
Real-time 3D image reconstruction guidance in liver resection surgery.
Soler, Luc; Nicolau, Stephane; Pessaux, Patrick; Mutter, Didier; Marescaux, Jacques
2014-04-01
Minimally invasive surgery represents one of the main evolutions of surgical techniques. However, minimally invasive surgery adds difficulty that can be reduced through computer technology. From a patient's medical image [US, computed tomography (CT) or MRI], we have developed an Augmented Reality (AR) system that increases the surgeon's intraoperative vision by providing a virtual transparency of the patient. AR is based on two major processes: 3D modeling and visualization of anatomical or pathological structures appearing in the medical image, and the registration of this visualization onto the real patient. We have thus developed a new online service, named Visible Patient, providing efficient 3D modeling of patients. We have then developed several 3D visualization and surgical planning software tools to combine direct volume rendering and surface rendering. Finally, we have developed two registration techniques, one interactive and one automatic providing intraoperative augmented reality view. From January 2009 to June 2013, 769 clinical cases have been modeled by the Visible Patient service. Moreover, three clinical validations have been realized demonstrating the accuracy of 3D models and their great benefit, potentially increasing surgical eligibility in liver surgery (20% of cases). From these 3D models, more than 50 interactive AR-assisted surgical procedures have been realized illustrating the potential clinical benefit of such assistance to gain safety, but also current limits that automatic augmented reality will overcome. Virtual patient modeling should be mandatory for certain interventions that have now to be defined, such as liver surgery. Augmented reality is clearly the next step of the new surgical instrumentation but remains currently limited due to the complexity of organ deformations during surgery. Intraoperative medical imaging used in new generation of automated augmented reality should solve this issue thanks to the development of Hybrid OR.
NASA Astrophysics Data System (ADS)
Hwang, Taejin; Kim, Yong Nam; Kim, Soo Kon; Kang, Sei-Kwon; Cheong, Kwang-Ho; Park, Soah; Yoon, Jai-Woong; Han, Taejin; Kim, Haeyoung; Lee, Meyeon; Kim, Kyoung-Joo; Bae, Hoonsik; Suh, Tae-Suk
2015-06-01
The dose constraint during prostate intensity-modulated radiation therapy (IMRT) optimization should be patient-specific for better rectum sparing. The aims of this study are to suggest a novel method for automatically generating a patient-specific dose constraint by using an experience-based dose volume histogram (DVH) of the rectum and to evaluate the potential of such a dose constraint qualitatively. The normal tissue complication probabilities (NTCPs) of the rectum with respect to V %ratio in our study were divided into three groups, where V %ratio was defined as the percent ratio of the rectal volume overlapping the planning target volume (PTV) to the rectal volume: (1) the rectal NTCPs in the previous study (clinical data), (2) those statistically generated by using the standard normal distribution (calculated data), and (3) those generated by combining the calculated data and the clinical data (mixed data). In the calculated data, a random number whose mean value was on the fitted curve described in the clinical data and whose standard deviation was 1% was generated by using the `randn' function in the MATLAB program and was used. For each group, we validated whether the probability density function (PDF) of the rectal NTCP could be automatically generated with the density estimation method by using a Gaussian kernel. The results revealed that the rectal NTCP probability increased in proportion to V %ratio , that the predictive rectal NTCP was patient-specific, and that the starting point of IMRT optimization for the given patient might be different. The PDF of the rectal NTCP was obtained automatically for each group except that the smoothness of the probability distribution increased with increasing number of data and with increasing window width. We showed that during the prostate IMRT optimization, the patient-specific dose constraints could be automatically generated and that our method could reduce the IMRT optimization time as well as maintain the IMRT plan quality.
"Crosstalk" technique: A comparison between two generations of cryoballoon catheter.
Yang, Jian-du; Sun, Qi; Guo, Xiao-Gang; Zhou, Gong-Bu; Liu, Xu; Luo, Bin; Wei, Hui-Qiang; Liang, Jackson J; Ma, Jian
2018-03-30
The "Crosstalk" technique: if pulmonary vein isolation (PVI) of the superior one is not achieved due to a gap in the inferior part, it could be done during inferior vein cryoablation. This maneuver minimizes the total energy delivery time and number of lesions. We aimed to correlate the likelihood of crosstalk phenomenon with certain anatomic characteristics. A total of 676 patients undergoing a first ablation procedure for paroxysmal or persistent atrial fibrillation (470 first-generation cryoballoon [CB] and 206 second-generation CB) between June 2014 and December 2016 were included. "Crosstalk" phenomenon occurred in 32 patients (18 first-generation CB, 14 second-generation CB). Compared to 54 control patients without crosstalk, the angle between left superior pulmonary vein (LSPV) and left atrial (LA) roof-plane, left pulmonary common ostia were significant parameters associated with crosstalk (odds ratio [OR] = 1.20, ±95% confidence interval [CI]: 1.11-1.31, P < 0.001; OR = 5.67, ±95% CI: 1.08-28.69, P = 0.04). As for angle between LSPV and LA roof-plane, the cut-off value was 28.68° with a sensitivity of 72.22%, a specificity of 81.25%, and an area under the receiver operating characteristic curve of 0.87 to predict the possibility of crosstalk technique application to get isolated in LSPV. Among the crosstalk group, there was no statistical difference between first-generation CB and second-generation CB in pulmonary anatomic characteristics. Crosstalk technique can be effective in patients with AF undergoing CB ablation using with both first and second-generation CBs. Anatomic characteristics predictive of crosstalk include a left common ostia and smaller angle between the LSPV and LA roof-plane. © 2018 Wiley Periodicals, Inc.
NASA Technical Reports Server (NTRS)
Cohen, Gerald C. (Inventor); McMann, Catherine M. (Inventor)
1991-01-01
An improved method and system for automatically generating reliability models for use with a reliability evaluation tool is described. The reliability model generator of the present invention includes means for storing a plurality of low level reliability models which represent the reliability characteristics for low level system components. In addition, the present invention includes means for defining the interconnection of the low level reliability models via a system architecture description. In accordance with the principles of the present invention, a reliability model for the entire system is automatically generated by aggregating the low level reliability models based on the system architecture description.
A knowledge-base generating hierarchical fuzzy-neural controller.
Kandadai, R M; Tien, J M
1997-01-01
We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.
Atlas-guided cluster analysis of large tractography datasets.
Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer
2013-01-01
Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.
Skeletal Muscle Fascicle Arrangements Can Be Reconstructed Using a Laplacian Vector Field Simulation
Choi, Hon Fai; Blemker, Silvia S.
2013-01-01
Skeletal muscles are characterized by a large diversity in anatomical architecture and function. Muscle force and contraction are generated by contractile fiber cells grouped in fascicle bundles, which transmit the mechanical action between origin and insertion attachments of the muscle. Therefore, an adequate representation of fascicle arrangements in computational models of skeletal muscles is important, especially when investigating three-dimensional muscle deformations in finite element models. However, obtaining high resolution in vivo measurements of fascicle arrangements in skeletal muscles is currently still challenging. This motivated the development of methods in previous studies to generate numerical representations of fascicle trajectories using interpolation templates. Here, we present an alternative approach based on the hypothesis of a rotation and divergence free (Laplacian) vector field behavior which reflects observed physical characteristics of fascicle trajectories. To obtain this representation, the Laplace equation was solved in anatomical reconstructions of skeletal muscle shapes based on medical images using a uniform flux boundary condition on the attachment areas. Fascicle tracts were generated through a robust flux based tracing algorithm. The concept of this approach was demonstrated in two-dimensional synthetic examples of typical skeletal muscle architectures. A detailed evaluation was performed in an example of the anatomical human tibialis anterior muscle which showed an overall agreement with measurements from the literature. The utility and capability of the proposed method was further demonstrated in other anatomical examples of human skeletal muscles with a wide range of muscle shapes and attachment morphologies. PMID:24204878
Creating a medical dictionary using word alignment: the influence of sources and resources.
Nyström, Mikael; Merkel, Magnus; Petersson, Håkan; Ahlfeldt, Hans
2007-11-23
Automatic word alignment of parallel texts with the same content in different languages is among other things used to generate dictionaries for new translations. The quality of the generated word alignment depends on the quality of the input resources. In this paper we report on automatic word alignment of the English and Swedish versions of the medical terminology systems ICD-10, ICF, NCSP, KSH97-P and parts of MeSH and how the terminology systems and type of resources influence the quality. We automatically word aligned the terminology systems using static resources, like dictionaries, statistical resources, like statistically derived dictionaries, and training resources, which were generated from manual word alignment. We varied which part of the terminology systems that we used to generate the resources, which parts that we word aligned and which types of resources we used in the alignment process to explore the influence the different terminology systems and resources have on the recall and precision. After the analysis, we used the best configuration of the automatic word alignment for generation of candidate term pairs. We then manually verified the candidate term pairs and included the correct pairs in an English-Swedish dictionary. The results indicate that more resources and resource types give better results but the size of the parts used to generate the resources only partly affects the quality. The most generally useful resources were generated from ICD-10 and resources generated from MeSH were not as general as other resources. Systematic inter-language differences in the structure of the terminology system rubrics make the rubrics harder to align. Manually created training resources give nearly as good results as a union of static resources, statistical resources and training resources and noticeably better results than a union of static resources and statistical resources. The verified English-Swedish dictionary contains 24,000 term pairs in base forms. More resources give better results in the automatic word alignment, but some resources only give small improvements. The most important type of resource is training and the most general resources were generated from ICD-10.
Creating a medical dictionary using word alignment: The influence of sources and resources
Nyström, Mikael; Merkel, Magnus; Petersson, Håkan; Åhlfeldt, Hans
2007-01-01
Background Automatic word alignment of parallel texts with the same content in different languages is among other things used to generate dictionaries for new translations. The quality of the generated word alignment depends on the quality of the input resources. In this paper we report on automatic word alignment of the English and Swedish versions of the medical terminology systems ICD-10, ICF, NCSP, KSH97-P and parts of MeSH and how the terminology systems and type of resources influence the quality. Methods We automatically word aligned the terminology systems using static resources, like dictionaries, statistical resources, like statistically derived dictionaries, and training resources, which were generated from manual word alignment. We varied which part of the terminology systems that we used to generate the resources, which parts that we word aligned and which types of resources we used in the alignment process to explore the influence the different terminology systems and resources have on the recall and precision. After the analysis, we used the best configuration of the automatic word alignment for generation of candidate term pairs. We then manually verified the candidate term pairs and included the correct pairs in an English-Swedish dictionary. Results The results indicate that more resources and resource types give better results but the size of the parts used to generate the resources only partly affects the quality. The most generally useful resources were generated from ICD-10 and resources generated from MeSH were not as general as other resources. Systematic inter-language differences in the structure of the terminology system rubrics make the rubrics harder to align. Manually created training resources give nearly as good results as a union of static resources, statistical resources and training resources and noticeably better results than a union of static resources and statistical resources. The verified English-Swedish dictionary contains 24,000 term pairs in base forms. Conclusion More resources give better results in the automatic word alignment, but some resources only give small improvements. The most important type of resource is training and the most general resources were generated from ICD-10. PMID:18036221
Demonstration of Automatically-Generated Adjoint Code for Use in Aerodynamic Shape Optimization
NASA Technical Reports Server (NTRS)
Green, Lawrence; Carle, Alan; Fagan, Mike
1999-01-01
Gradient-based optimization requires accurate derivatives of the objective function and constraints. These gradients may have previously been obtained by manual differentiation of analysis codes, symbolic manipulators, finite-difference approximations, or existing automatic differentiation (AD) tools such as ADIFOR (Automatic Differentiation in FORTRAN). Each of these methods has certain deficiencies, particularly when applied to complex, coupled analyses with many design variables. Recently, a new AD tool called ADJIFOR (Automatic Adjoint Generation in FORTRAN), based upon ADIFOR, was developed and demonstrated. Whereas ADIFOR implements forward-mode (direct) differentiation throughout an analysis program to obtain exact derivatives via the chain rule of calculus, ADJIFOR implements the reverse-mode counterpart of the chain rule to obtain exact adjoint form derivatives from FORTRAN code. Automatically-generated adjoint versions of the widely-used CFL3D computational fluid dynamics (CFD) code and an algebraic wing grid generation code were obtained with just a few hours processing time using the ADJIFOR tool. The codes were verified for accuracy and were shown to compute the exact gradient of the wing lift-to-drag ratio, with respect to any number of shape parameters, in about the time required for 7 to 20 function evaluations. The codes have now been executed on various computers with typical memory and disk space for problems with up to 129 x 65 x 33 grid points, and for hundreds to thousands of independent variables. These adjoint codes are now used in a gradient-based aerodynamic shape optimization problem for a swept, tapered wing. For each design iteration, the optimization package constructs an approximate, linear optimization problem, based upon the current objective function, constraints, and gradient values. The optimizer subroutines are called within a design loop employing the approximate linear problem until an optimum shape is found, the design loop limit is reached, or no further design improvement is possible due to active design variable bounds and/or constraints. The resulting shape parameters are then used by the grid generation code to define a new wing surface and computational grid. The lift-to-drag ratio and its gradient are computed for the new design by the automatically-generated adjoint codes. Several optimization iterations may be required to find an optimum wing shape. Results from two sample cases will be discussed. The reader should note that this work primarily represents a demonstration of use of automatically- generated adjoint code within an aerodynamic shape optimization. As such, little significance is placed upon the actual optimization results, relative to the method for obtaining the results.
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI.
Alansary, Amir; Rajchl, Martin; McDonagh, Steven G; Murgasova, Maria; Damodaram, Mellisa; Lloyd, David F A; Davidson, Alice; Rutherford, Mary; Hajnal, Joseph V; Rueckert, Daniel; Kainz, Bernhard
2017-10-01
In this paper, we present a novel method for the correction of motion artifacts that are present in fetal magnetic resonance imaging (MRI) scans of the whole uterus. Contrary to current slice-to-volume registration (SVR) methods, requiring an inflexible anatomical enclosure of a single investigated organ, the proposed patch-to-volume reconstruction (PVR) approach is able to reconstruct a large field of view of non-rigidly deforming structures. It relaxes rigid motion assumptions by introducing a specific amount of redundant information that is exploited with parallelized patchwise optimization, super-resolution, and automatic outlier rejection. We further describe and provide an efficient parallel implementation of PVR allowing its execution within reasonable time on commercially available graphics processing units, enabling its use in the clinical practice. We evaluate PVR's computational overhead compared with standard methods and observe improved reconstruction accuracy in the presence of affine motion artifacts compared with conventional SVR in synthetic experiments. Furthermore, we have evaluated our method qualitatively and quantitatively on real fetal MRI data subject to maternal breathing and sudden fetal movements. We evaluate peak-signal-to-noise ratio, structural similarity index, and cross correlation with respect to the originally acquired data and provide a method for visual inspection of reconstruction uncertainty. We further evaluate the distance error for selected anatomical landmarks in the fetal head, as well as calculating the mean and maximum displacements resulting from automatic non-rigid registration to a motion-free ground truth image. These experiments demonstrate a successful application of PVR motion compensation to the whole fetal body, uterus, and placenta.
The use of automatic programming techniques for fault tolerant computing systems
NASA Technical Reports Server (NTRS)
Wild, C.
1985-01-01
It is conjectured that the production of software for ultra-reliable computing systems such as required by Space Station, aircraft, nuclear power plants and the like will require a high degree of automation as well as fault tolerance. In this paper, the relationship between automatic programming techniques and fault tolerant computing systems is explored. Initial efforts in the automatic synthesis of code from assertions to be used for error detection as well as the automatic generation of assertions and test cases from abstract data type specifications is outlined. Speculation on the ability to generate truly diverse designs capable of recovery from errors by exploring alternate paths in the program synthesis tree is discussed. Some initial thoughts on the use of knowledge based systems for the global detection of abnormal behavior using expectations and the goal-directed reconfiguration of resources to meet critical mission objectives are given. One of the sources of information for these systems would be the knowledge captured during the automatic programming process.
Automatic Generation of Rasch-Calibrated Items: Figural Matrices Test GEOM and Endless-Loops Test EC
ERIC Educational Resources Information Center
Arendasy, Martin
2005-01-01
The future of test construction for certain psychological ability domains that can be analyzed well in a structured manner may lie--at the very least for reasons of test security--in the field of automatic item generation. In this context, a question that has not been explicitly addressed is whether it is possible to embed an item response theory…
Esophagus segmentation in CT via 3D fully convolutional neural network and random walk.
Fechter, Tobias; Adebahr, Sonja; Baltas, Dimos; Ben Ayed, Ismail; Desrosiers, Christian; Dolz, Jose
2017-12-01
Precise delineation of organs at risk is a crucial task in radiotherapy treatment planning for delivering high doses to the tumor while sparing healthy tissues. In recent years, automated segmentation methods have shown an increasingly high performance for the delineation of various anatomical structures. However, this task remains challenging for organs like the esophagus, which have a versatile shape and poor contrast to neighboring tissues. For human experts, segmenting the esophagus from CT images is a time-consuming and error-prone process. To tackle these issues, we propose a random walker approach driven by a 3D fully convolutional neural network (CNN) to automatically segment the esophagus from CT images. First, a soft probability map is generated by the CNN. Then, an active contour model (ACM) is fitted to the CNN soft probability map to get a first estimation of the esophagus location. The outputs of the CNN and ACM are then used in conjunction with a probability model based on CT Hounsfield (HU) values to drive the random walker. Training and evaluation were done on 50 CTs from two different datasets, with clinically used peer-reviewed esophagus contours. Results were assessed regarding spatial overlap and shape similarity. The esophagus contours generated by the proposed algorithm showed a mean Dice coefficient of 0.76 ± 0.11, an average symmetric square distance of 1.36 ± 0.90 mm, and an average Hausdorff distance of 11.68 ± 6.80, compared to the reference contours. These results translate to a very good agreement with reference contours and an increase in accuracy compared to existing methods. Furthermore, when considering the results reported in the literature for the publicly available Synapse dataset, our method outperformed all existing approaches, which suggests that the proposed method represents the current state-of-the-art for automatic esophagus segmentation. We show that a CNN can yield accurate estimations of esophagus location, and that the results of this model can be refined by a random walk step taking pixel intensities and neighborhood relationships into account. One of the main advantages of our network over previous methods is that it performs 3D convolutions, thus fully exploiting the 3D spatial context and performing an efficient volume-wise prediction. The whole segmentation process is fully automatic and yields esophagus delineations in very good agreement with the gold standard, showing that it can compete with previously published methods. © 2017 American Association of Physicists in Medicine.
Automatic Generation of English-Japanese Translation Pattern Utilizing Genetic Programming Technique
NASA Astrophysics Data System (ADS)
Matsumura, Koki; Tamekuni, Yuji; Kimura, Shuhei
There are a lot of constructional differences in an English-Japanese phrase template, and that often makes the act of translation difficult. Moreover, there exist various and tremendous phrase templates and sentence to be refered to. It is not easy to prepare the corpus that covers the all. Therefore, it is very significant to generate the translation pattern of the sentence pattern automatically from a viewpoint of the translation success rate and the capacity of the pattern dictionary. Then, for the purpose of realizing the automatic generation of the translation pattern, this paper proposed the new method for the generation of the translation pattern by using the genetic programming technique (GP). The technique tries to generate the translation pattern of various sentences which are not registered in the phrase template dictionary automatically by giving the genetic operation to the parsing tree of a basic pattern. The tree consists of the pair of the English-Japanese sentence generated as the first stage population. The analysis tree data base with 50,100,150,200 pairs was prepared as the first stage population. And this system was applied and executed for an English input of 1,555 sentences. As a result, the analysis tree increases from 200 to 517, and the accuracy rate of the translation pattern has improved from 42.57% to 70.10%. And, 86.71% of the generated translations was successfully done, whose meanings are enough acceptable and understandable. It seemed that this proposal technique became a clue to raise the translation success rate, and to find the possibility of the reduction of the analysis tree data base.
ERIC Educational Resources Information Center
Noël, Geoffroy P. J. C.; Connolly, Ciaran C.
2016-01-01
The correct tracking and monitoring of anatomical specimens is not only imperative in any modern body donation programs but also in any universities for which teaching the next generation of health care professionals is the primary mission. This has long been an arduous process for anatomy institutions across the world, and the recent focus of new…
Geometry modeling and multi-block grid generation for turbomachinery configurations
NASA Technical Reports Server (NTRS)
Shih, Ming H.; Soni, Bharat K.
1992-01-01
An interactive 3D grid generation code, Turbomachinery Interactive Grid genERation (TIGER), was developed for general turbomachinery configurations. TIGER features the automatic generation of multi-block structured grids around multiple blade rows for either internal, external, or internal-external turbomachinery flow fields. Utilization of the Bezier's curves achieves a smooth grid and better orthogonality. TIGER generates the algebraic grid automatically based on geometric information provided by its built-in pseudo-AI algorithm. However, due to the large variation of turbomachinery configurations, this initial grid may not always be as good as desired. TIGER therefore provides graphical user interactions during the process which allow the user to design, modify, as well as manipulate the grid, including the capability of elliptic surface grid generation.
An Interactive Decision Support System for Scheduling Fighter Pilot Training
2002-03-26
Deitel , H.M. and Deitel , P.J. C: How to Program , 2nd ed., Prentice Hall, 1994. 8. Deitel , H.M. and Deitel , P.J. How to Program Java...Visual Basic Programming language, the Excel tool is modified in several ways. Scheduling Dispatch rules are implemented to automatically generate... programming language, the Excel tool was modified in several ways. Scheduling dispatch rules are implemented to automatically generate
QA-driven Guidelines Generation for Bacteriotherapy
Pasche, Emilie; Teodoro, Douglas; Gobeill, Julien; Ruch, Patrick; Lovis, Christian
2009-01-01
PURPOSE We propose a question-answering (QA) driven generation approach for automatic acquisition of structured rules that can be used in a knowledge authoring tool for antibiotic prescription guidelines management. METHODS: The rule generation is seen as a question-answering problem, where the parameters of the questions are known items of the rule (e.g. an infectious disease, caused by a given bacterium) and answers (e.g. some antibiotics) are obtained by a question-answering engine. RESULTS: When looking for a drug given a pathogen and a disease, top-precision of 0.55 is obtained by the combination of the Boolean engine (PubMed) and the relevance-driven engine (easyIR), which means that for more than half of our evaluation benchmark at least one of the recommended antibiotics was automatically acquired by the rule generation method. CONCLUSION: These results suggest that such an automatic text mining approach could provide a useful tool for guidelines management, by improving knowledge update and discovery. PMID:20351908
A semi-automatic computer-aided method for surgical template design
NASA Astrophysics Data System (ADS)
Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan
2016-02-01
This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method.
Intelligent automated surface grid generation
NASA Technical Reports Server (NTRS)
Yao, Ke-Thia; Gelsey, Andrew
1995-01-01
The goal of our research is to produce a flexible, general grid generator for automated use by other programs, such as numerical optimizers. The current trend in the gridding field is toward interactive gridding. Interactive gridding more readily taps into the spatial reasoning abilities of the human user through the use of a graphical interface with a mouse. However, a sometimes fruitful approach to generating new designs is to apply an optimizer with shape modification operators to improve an initial design. In order for this approach to be useful, the optimizer must be able to automatically grid and evaluate the candidate designs. This paper describes and intelligent gridder that is capable of analyzing the topology of the spatial domain and predicting approximate physical behaviors based on the geometry of the spatial domain to automatically generate grids for computational fluid dynamics simulators. Typically gridding programs are given a partitioning of the spatial domain to assist the gridder. Our gridder is capable of performing this partitioning. This enables the gridder to automatically grid spatial domains of wide range of configurations.
NASA Technical Reports Server (NTRS)
Cross, James H., II; Morrison, Kelly I.; May, Charles H., Jr.; Waddel, Kathryn C.
1989-01-01
The first phase of a three-phase effort to develop a new graphically oriented specification language which will facilitate the reverse engineering of Ada source code into graphical representations (GRs) as well as the automatic generation of Ada source code is described. A simplified view of the three phases of Graphical Representations for Algorithms, Structure, and Processes for Ada (GRASP/Ada) with respect to three basic classes of GRs is presented. Phase 1 concentrated on the derivation of an algorithmic diagram, the control structure diagram (CSD) (CRO88a) from Ada source code or Ada PDL. Phase 2 includes the generation of architectural and system level diagrams such as structure charts and data flow diagrams and should result in a requirements specification for a graphically oriented language able to support automatic code generation. Phase 3 will concentrate on the development of a prototype to demonstrate the feasibility of this new specification language.
A semi-automatic computer-aided method for surgical template design
Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan
2016-01-01
This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method. PMID:26843434
A semi-automatic computer-aided method for surgical template design.
Chen, Xiaojun; Xu, Lu; Yang, Yue; Egger, Jan
2016-02-04
This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method.
Automatic Evolution of Molecular Nanotechnology Designs
NASA Technical Reports Server (NTRS)
Globus, Al; Lawton, John; Wipke, Todd; Saini, Subhash (Technical Monitor)
1998-01-01
This paper describes strategies for automatically generating designs for analog circuits at the molecular level. Software maps out the edges and vertices of potential nanotechnology systems on graphs, then selects appropriate ones through evolutionary or genetic paradigms.
Yeo, Lami; Romero, Roberto
2013-09-01
To describe a novel method (Fetal Intelligent Navigation Echocardiography (FINE)) for visualization of standard fetal echocardiography views from volume datasets obtained with spatiotemporal image correlation (STIC) and application of 'intelligent navigation' technology. We developed a method to: 1) demonstrate nine cardiac diagnostic planes; and 2) spontaneously navigate the anatomy surrounding each of the nine cardiac diagnostic planes (Virtual Intelligent Sonographer Assistance (VIS-Assistance®)). The method consists of marking seven anatomical structures of the fetal heart. The following echocardiography views are then automatically generated: 1) four chamber; 2) five chamber; 3) left ventricular outflow tract; 4) short-axis view of great vessels/right ventricular outflow tract; 5) three vessels and trachea; 6) abdomen/stomach; 7) ductal arch; 8) aortic arch; and 9) superior and inferior vena cava. The FINE method was tested in a separate set of 50 STIC volumes of normal hearts (18.6-37.2 weeks of gestation), and visualization rates for fetal echocardiography views using diagnostic planes and/or VIS-Assistance® were calculated. To examine the feasibility of identifying abnormal cardiac anatomy, we tested the method in four cases with proven congenital heart defects (coarctation of aorta, tetralogy of Fallot, transposition of great vessels and pulmonary atresia with intact ventricular septum). In normal cases, the FINE method was able to generate nine fetal echocardiography views using: 1) diagnostic planes in 78-100% of cases; 2) VIS-Assistance® in 98-100% of cases; and 3) a combination of diagnostic planes and/or VIS-Assistance® in 98-100% of cases. In all four abnormal cases, the FINE method demonstrated evidence of abnormal fetal cardiac anatomy. The FINE method can be used to visualize nine standard fetal echocardiography views in normal hearts by applying 'intelligent navigation' technology to STIC volume datasets. This method can simplify examination of the fetal heart and reduce operator dependency. The observation of abnormal echocardiography views in the diagnostic planes and/or VIS-Assistance® should raise the index of suspicion for congenital heart disease. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
NASA Astrophysics Data System (ADS)
Rieder, Christian; Wirtz, Stefan; Strehlow, Jan; Zidowitz, Stephan; Bruners, Philipp; Isfort, Peter; Mahnken, Andreas H.; Peitgen, Heinz-Otto
2012-02-01
Image-guided radiofrequency ablation (RFA) is becoming a standard procedure for minimally invasive tumor treatment in clinical practice. To verify the treatment success of the therapy, reliable post-interventional assessment of the ablation zone (coagulation) is essential. Typically, pre- and post-interventional CT images have to be aligned to compare the shape, size, and position of tumor and coagulation zone. In this work, we present an automatic workflow for masking liver tissue, enabling a rigid registration algorithm to perform at least as accurate as experienced medical experts. To minimize the effect of global liver deformations, the registration is computed in a local region of interest around the pre-interventional lesion and post-interventional coagulation necrosis. A registration mask excluding lesions and neighboring organs is calculated to prevent the registration algorithm from matching both lesion shapes instead of the surrounding liver anatomy. As an initial registration step, the centers of gravity from both lesions are aligned automatically. The subsequent rigid registration method is based on the Local Cross Correlation (LCC) similarity measure and Newton-type optimization. To assess the accuracy of our method, 41 RFA cases are registered and compared with the manually aligned cases from four medical experts. Furthermore, the registration results are compared with ground truth transformations based on averaged anatomical landmark pairs. In the evaluation, we show that our method allows to automatic alignment of the data sets with equal accuracy as medical experts, but requiring significancy less time consumption and variability.
An automatic markerless registration method for neurosurgical robotics based on an optical camera.
Meng, Fanle; Zhai, Fangwen; Zeng, Bowei; Ding, Hui; Wang, Guangzhi
2018-02-01
Current markerless registration methods for neurosurgical robotics use the facial surface to match the robot space with the image space, and acquisition of the facial surface usually requires manual interaction and constrains the patient to a supine position. To overcome these drawbacks, we propose a registration method that is automatic and does not constrain patient position. An optical camera attached to the robot end effector captures images around the patient's head from multiple views. Then, high coverage of the head surface is reconstructed from the images through multi-view stereo vision. Since the acquired head surface point cloud contains color information, a specific mark that is manually drawn on the patient's head prior to the capture procedure can be extracted to automatically accomplish coarse registration rather than using facial anatomic landmarks. Then, fine registration is achieved by registering the high coverage of the head surface without relying solely on the facial region, thus eliminating patient position constraints. The head surface was acquired by the camera with a good repeatability accuracy. The average target registration error of 8 different patient positions measured with targets inside a head phantom was [Formula: see text], while the mean surface registration error was [Formula: see text]. The method proposed in this paper achieves automatic markerless registration in multiple patient positions and guarantees registration accuracy inside the head. This method provides a new approach for establishing the spatial relationship between the image space and the robot space.
Thai Automatic Speech Recognition
2005-01-01
used in an external DARPA evaluation involving medical scenarios between an American Doctor and a naïve monolingual Thai patient. 2. Thai Language... dictionary generation more challenging, and (3) the lack of word segmentation, which calls for automatic segmentation approaches to make n-gram language...requires a dictionary and provides various segmentation algorithms to automatically select suitable segmentations. Here we used a maximal matching
Ballyns, Jeffery J; Gleghorn, Jason P; Niebrzydowski, Vicki; Rawlinson, Jeremy J; Potter, Hollis G; Maher, Suzanne A; Wright, Timothy M; Bonassar, Lawrence J
2008-07-01
This study demonstrates for the first time the development of engineered tissues based on anatomic geometries derived from widely used medical imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). Computer-aided design and tissue injection molding techniques have demonstrated the ability to generate living implants of complex geometry. Due to its complex geometry, the meniscus of the knee was used as an example of this technique's capabilities. MRI and microcomputed tomography (microCT) were used to design custom-printed molds that enabled the generation of anatomically shaped constructs that retained shape throughout 8 weeks of culture. Engineered constructs showed progressive tissue formation indicated by increases in extracellular matrix content and mechanical properties. The paradigm of interfacing tissue injection molding technology can be applied to other medical imaging techniques that render 3D models of anatomy, demonstrating the potential to apply the current technique to engineering of many tissues and organs.
Post, Richard F.
2005-02-22
A motor/generator having its stationary portion, i.e., the stator, positioned concentrically within its rotatable element, i.e., the rotor, along its axis of rotation. The rotor includes a Halbach array. The stator windings are switched or commutated to provide a DC motor/generator much the same as in a conventional DC motor/generator. The voltage and power are automatically regulated by using centrifugal force to change the diameter of the rotor, and thereby vary the radial gap in between the stator and the rotating Halbach array, as a function of the angular velocity of the rotor.
Frequency control of wind turbine in power system
NASA Astrophysics Data System (ADS)
Xu, Huawei
2018-06-01
In order to improve the stability of the overall frequency of the power system, automatic power generation control and secondary frequency adjustment were applied. Automatic power generation control was introduced into power generation planning. A dual-fed wind generator power regulation model suitable for secondary frequency regulation was established. The results showed that this method satisfied the basic requirements of frequency regulation control of large-scale wind power access power systems and improved the stability and reliability of power system operation. Therefore, this system frequency control method and strategy is relatively simple. The effect is significant. The system frequency can quickly reach a steady state. It is worth applying and promoting.
ELECTROMAGNETIC AND ELECTROSTATIC GENERATORS: ANNOTATED BIBLIOGRAPHY.
generator with split poles, ultrasonic-frequency generator, unipolar generator, single-phase micromotors , synchronous motor, asynchronous motor...asymmetrical rotor, magnetic circuit, dc micromotors , circuit for the automatic control of synchronized induction motors, induction torque micromotors , electric
Dai, Weiying; Soman, Salil; Hackney, David B.; Wong, Eric T.; Robson, Philip M.; Alsop, David C.
2017-01-01
Functional imaging provides hemodynamic and metabolic information and is increasingly being incorporated into clinical diagnostic and research studies. Typically functional images have reduced signal-to-noise ratio and spatial resolution compared to other non-functional cross sectional images obtained as part of a routine clinical protocol. We hypothesized that enhancing visualization and interpretation of functional images with anatomic information could provide preferable quality and superior diagnostic value. In this work, we implemented five methods (frequency addition, frequency multiplication, wavelet transform, non-subsampled contourlet transform and intensity-hue-saturation) and a newly proposed ShArpening by Local Similarity with Anatomic images (SALSA) method to enhance the visualization of functional images, while preserving the original functional contrast and quantitative signal intensity characteristics over larger spatial scales. Arterial spin labeling blood flow MR images of the brain were visualization enhanced using anatomic images with multiple contrasts. The algorithms were validated on a numerical phantom and their performance on images of brain tumor patients were assessed by quantitative metrics and neuroradiologist subjective ratings. The frequency multiplication method had the lowest residual error for preserving the original functional image contrast at larger spatial scales (55%–98% of the other methods with simulated data and 64%–86% with experimental data). It was also significantly more highly graded by the radiologists (p<0.005 for clear brain anatomy around the tumor). Compared to other methods, the SALSA provided 11%–133% higher similarity with ground truth images in the simulation and showed just slightly lower neuroradiologist grading score. Most of these monochrome methods do not require any prior knowledge about the functional and anatomic image characteristics, except the acquired resolution. Hence, automatic implementation on clinical images should be readily feasible. PMID:27723582
van Tellingen, C.
2009-01-01
The development in cardiovascular anatomy and physiology is described from a Dutch perspective. The newly formed Republic in the 17th century, with its pragmatism and business-like character, became an ideal breeding ground for Descartes' new philosophy. His separation of body and soul provided a mechanistic model of body structure and formed a firm basis for anatomical and physiological research to become catalysts for a tempestuous growth and progress in medicine. (Neth Heart J 2009;17:130-5.19421357) PMID:19421357
Automatic mediastinal lymph node detection in chest CT
NASA Astrophysics Data System (ADS)
Feuerstein, Marco; Deguchi, Daisuke; Kitasaka, Takayuki; Iwano, Shingo; Imaizumi, Kazuyoshi; Hasegawa, Yoshinori; Suenaga, Yasuhito; Mori, Kensaku
2009-02-01
Computed tomography (CT) of the chest is a very common staging investigation for the assessment of mediastinal, hilar, and intrapulmonary lymph nodes in the context of lung cancer. In the current clinical workflow, the detection and assessment of lymph nodes is usually performed manually, which can be error-prone and timeconsuming. We therefore propose a method for the automatic detection of mediastinal, hilar, and intrapulmonary lymph node candidates in contrast-enhanced chest CT. Based on the segmentation of important mediastinal anatomy (bronchial tree, aortic arch) and making use of anatomical knowledge, we utilize Hessian eigenvalues to detect lymph node candidates. As lymph nodes can be characterized as blob-like structures of varying size and shape within a specific intensity interval, we can utilize these characteristics to reduce the number of false positive candidates significantly. We applied our method to 5 cases suspected to have lung cancer. The processing time of our algorithm did not exceed 6 minutes, and we achieved an average sensitivity of 82.1% and an average precision of 13.3%.
Concept and development of a computerized positioning of prosthetic teeth for complete dentures.
Busch, M; Kordass, B
2006-04-01
To date, CAD/CAM technology has made no noteworthy inroads into removable dentures. We want to present a new area of application for this in our study. Models of the maxilla and edentulous mandible were 3D scanned. The software detects and automatically reconstructs the reference structures that are anatomically important for the set-up of artificial teeth, such as the alveolar ridge centerlines and the interalveolar relations between the alveolar ridges. In a further step, the occlusal plane is semiautomatically defined and the front dental arch is designed. After these design features have been determined, artificial teeth are selected from a database and set up automatically. The dental technician can assess the esthetics and function of the suggested dental set-up on the computer screen and make slight corrections if necessary. Summarizing: The interplay of hardware and software components within on integrated solution including conversion of the "virtual" into a real positioning of prosthetic teeth is presented.
Interactive surface correction for 3D shape based segmentation
NASA Astrophysics Data System (ADS)
Schwarz, Tobias; Heimann, Tobias; Tetzlaff, Ralf; Rau, Anne-Mareike; Wolf, Ivo; Meinzer, Hans-Peter
2008-03-01
Statistical shape models have become a fast and robust method for segmentation of anatomical structures in medical image volumes. In clinical practice, however, pathological cases and image artifacts can lead to local deviations of the detected contour from the true object boundary. These deviations have to be corrected manually. We present an intuitively applicable solution for surface interaction based on Gaussian deformation kernels. The method is evaluated by two radiological experts on segmentations of the liver in contrast-enhanced CT images and of the left heart ventricle (LV) in MRI data. For both applications, five datasets are segmented automatically using deformable shape models, and the resulting surfaces are corrected manually. The interactive correction step improves the average surface distance against ground truth from 2.43mm to 2.17mm for the liver, and from 2.71mm to 1.34mm for the LV. We expect this method to raise the acceptance of automatic segmentation methods in clinical application.
McBride, Dawn M; Anne Dosher, Barbara
2002-09-01
Four experiments were conducted to evaluate explanations of picture superiority effects previously found for several tasks. In a process dissociation procedure (Jacoby, 1991) with word stem completion, picture fragment completion, and category production tasks, conscious and automatic memory processes were compared for studied pictures and words with an independent retrieval model and a generate-source model. The predictions of a transfer appropriate processing account of picture superiority were tested and validated in "process pure" latent measures of conscious and unconscious, or automatic and source, memory processes. Results from both model fits verified that pictures had a conceptual (conscious/source) processing advantage over words for all tasks. The effects of perceptual (automatic/word generation) compatibility depended on task type, with pictorial tasks favoring pictures and linguistic tasks favoring words. Results show support for an explanation of the picture superiority effect that involves an interaction of encoding and retrieval processes.
Automatic textual annotation of video news based on semantic visual object extraction
NASA Astrophysics Data System (ADS)
Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem
2003-12-01
In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.
Kim, Yong-Il; Im, Hyung-Jun; Paeng, Jin Chul; Lee, Jae Sung; Eo, Jae Seon; Kim, Dong Hyun; Kim, Euishin E; Kang, Keon Wook; Chung, June-Key; Lee, Dong Soo
2012-12-01
(18)F-FP-CIT positron emission tomography (PET) is an effective imaging for dopamine transporters. In usual clinical practice, (18)F-FP-CIT PET is analyzed visually or quantified using manual delineation of a volume of interest (VOI) for the striatum. In this study, we suggested and validated two simple quantitative methods based on automatic VOI delineation using statistical probabilistic anatomical mapping (SPAM) and isocontour margin setting. Seventy-five (18)F-FP-CIT PET images acquired in routine clinical practice were used for this study. A study-specific image template was made and the subject images were normalized to the template. Afterwards, uptakes in the striatal regions and cerebellum were quantified using probabilistic VOI based on SPAM. A quantitative parameter, QSPAM, was calculated to simulate binding potential. Additionally, the functional volume of each striatal region and its uptake were measured in automatically delineated VOI using isocontour margin setting. Uptake-volume product (QUVP) was calculated for each striatal region. QSPAM and QUVP were compared with visual grading and the influence of cerebral atrophy on the measurements was tested. Image analyses were successful in all the cases. Both the QSPAM and QUVP were significantly different according to visual grading (P < 0.001). The agreements of QUVP or QSPAM with visual grading were slight to fair for the caudate nucleus (κ = 0.421 and 0.291, respectively) and good to perfect to the putamen (κ = 0.663 and 0.607, respectively). Also, QSPAM and QUVP had a significant correlation with each other (P < 0.001). Cerebral atrophy made a significant difference in QSPAM and QUVP of the caudate nuclei regions with decreased (18)F-FP-CIT uptake. Simple quantitative measurements of QSPAM and QUVP showed acceptable agreement with visual grading. Although QSPAM in some group may be influenced by cerebral atrophy, these simple methods are expected to be effective in the quantitative analysis of (18)F-FP-CIT PET in usual clinical practice.
Fully automatic adjoints: a robust and efficient mechanism for generating adjoint ocean models
NASA Astrophysics Data System (ADS)
Ham, D. A.; Farrell, P. E.; Funke, S. W.; Rognes, M. E.
2012-04-01
The problem of generating and maintaining adjoint models is sufficiently difficult that typically only the most advanced and well-resourced community ocean models achieve it. There are two current technologies which each suffer from their own limitations. Algorithmic differentiation, also called automatic differentiation, is employed by models such as the MITGCM [2] and the Alfred Wegener Institute model FESOM [3]. This technique is very difficult to apply to existing code, and requires a major initial investment to prepare the code for automatic adjoint generation. AD tools may also have difficulty with code employing modern software constructs such as derived data types. An alternative is to formulate the adjoint differential equation and to discretise this separately. This approach, known as the continuous adjoint and employed in ROMS [4], has the disadvantage that two different model code bases must be maintained and manually kept synchronised as the model develops. The discretisation of the continuous adjoint is not automatically consistent with that of the forward model, producing an additional source of error. The alternative presented here is to formulate the flow model in the high level language UFL (Unified Form Language) and to automatically generate the model using the software of the FEniCS project. In this approach it is the high level code specification which is differentiated, a task very similar to the formulation of the continuous adjoint [5]. However since the forward and adjoint models are generated automatically, the difficulty of maintaining them vanishes and the software engineering process is therefore robust. The scheduling and execution of the adjoint model, including the application of an appropriate checkpointing strategy is managed by libadjoint [1]. In contrast to the conventional algorithmic differentiation description of a model as a series of primitive mathematical operations, libadjoint employs a new abstraction of the simulation process as a sequence of discrete equations which are assembled and solved. It is the coupling of the respective abstractions employed by libadjoint and the FEniCS project which produces the adjoint model automatically, without further intervention from the model developer. This presentation will demonstrate this new technology through linear and non-linear shallow water test cases. The exceptionally simple model syntax will be highlighted and the correctness of the resulting adjoint simulations will be demonstrated using rigorous convergence tests.
Elleithy, Khaled; Elleithy, Abdelrahman
2018-01-01
Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue for detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc, and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This paper proposes an automated retinal fundus image segmentation system composed of three segmentation subsystems follow same core segmentation algorithm. Despite of broad difference in features and characteristics; retinal vessels, optic disc, and exudate lesions are extracted by each subsystem without the need for texture analysis or synthesis. For sake of compact diagnosis and complete clinical insight, our proposed system can detect these anatomical structures in one session with high accuracy even in pathological retina images. The proposed system uses a robust hybrid segmentation algorithm combines adaptive fuzzy thresholding and mathematical morphology. The proposed system is validated using four benchmark datasets: DRIVE and STARE (vessels), DRISHTI-GS (optic disc), and DIARETDB1 (exudates lesions). Competitive segmentation performance is achieved, outperforming a variety of up-to-date systems and demonstrating the capacity to deal with other heterogeneous anatomical structures. PMID:29888146
Effectiveness of an automatic tracking software in underwater motion analysis.
Magalhaes, Fabrício A; Sawacha, Zimi; Di Michele, Rocco; Cortesi, Matteo; Gatta, Giorgio; Fantozzi, Silvia
2013-01-01
Tracking of markers placed on anatomical landmarks is a common practice in sports science to perform the kinematic analysis that interests both athletes and coaches. Although different software programs have been developed to automatically track markers and/or features, none of them was specifically designed to analyze underwater motion. Hence, this study aimed to evaluate the effectiveness of a software developed for automatic tracking of underwater movements (DVP), based on the Kanade-Lucas-Tomasi feature tracker. Twenty-one video recordings of different aquatic exercises (n = 2940 markers' positions) were manually tracked to determine the markers' center coordinates. Then, the videos were automatically tracked using DVP and a commercially available software (COM). Since tracking techniques may produce false targets, an operator was instructed to stop the automatic procedure and to correct the position of the cursor when the distance between the calculated marker's coordinate and the reference one was higher than 4 pixels. The proportion of manual interventions required by the software was used as a measure of the degree of automation. Overall, manual interventions were 10.4% lower for DVP (7.4%) than for COM (17.8%). Moreover, when examining the different exercise modes separately, the percentage of manual interventions was 5.6% to 29.3% lower for DVP than for COM. Similar results were observed when analyzing the type of marker rather than the type of exercise, with 9.9% less manual interventions for DVP than for COM. In conclusion, based on these results, the developed automatic tracking software presented can be used as a valid and useful tool for underwater motion analysis. Key PointsThe availability of effective software for automatic tracking would represent a significant advance for the practical use of kinematic analysis in swimming and other aquatic sports.An important feature of automatic tracking software is to require limited human interventions and supervision, thus allowing short processing time.When tracking underwater movements, the degree of automation of the tracking procedure is influenced by the capability of the algorithm to overcome difficulties linked to the small target size, the low image quality and the presence of background clutters.The newly developed feature-tracking algorithm has shown a good automatic tracking effectiveness in underwater motion analysis with significantly smaller percentage of required manual interventions when compared to a commercial software.
Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.
Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping
2014-01-01
The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.
Automatic Title Generation for Spoken Broadcast News
2001-01-01
degrades much less with speech -recognized transcripts. Meanwhile, even though KNN performance not as well as TF.IDF and NBL in terms of F1 metric, it...test corpus of 1006 broadcast news documents, comparing the results over manual transcription to the results over automatically recognized speech . We...use both F1 and the average number of correct title words in the correct order as metric. Overall, the results show that title generation for speech
Automatic Generation of Heuristics for Scheduling
NASA Technical Reports Server (NTRS)
Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.
1997-01-01
This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.
Using automatic generation of Labanotation to protect folk dance
NASA Astrophysics Data System (ADS)
Wang, Jiaji; Miao, Zhenjiang; Guo, Hao; Zhou, Ziming; Wu, Hao
2017-01-01
Labanotation uses symbols to describe human motion and is an effective means of protecting folk dance. We use motion capture data to automatically generate Labanotation. First, we convert the motion capture data of the biovision hierarchy file into three-dimensional coordinate data. Second, we divide human motion into element movements. Finally, we analyze each movement and find the corresponding notation. Our work has been supervised by an expert in Labanotation to ensure the correctness of the results. At present, the work deals with a subset of symbols in Labanotation that correspond to several basic movements. Labanotation contains many symbols and several new symbols may be introduced for improvement in the future. We will refine our work to handle more symbols. The automatic generation of Labanotation can greatly improve the work efficiency of documenting movements. Thus, our work will significantly contribute to the protection of folk dance and other action arts.
Automatic and hierarchical segmentation of the human skeleton in CT images.
Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan
2017-04-07
Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.
Automatic and hierarchical segmentation of the human skeleton in CT images
NASA Astrophysics Data System (ADS)
Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan
2017-04-01
Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.
NASA Technical Reports Server (NTRS)
kaul, Upender K.
2008-01-01
A procedure for generating smooth uniformly clustered single-zone grids using enhanced elliptic grid generation has been demonstrated here for the Mars Science Laboratory (MSL) geometries such as aeroshell and canopy. The procedure obviates the need for generating multizone grids for such geometries, as reported in the literature. This has been possible because the enhanced elliptic grid generator automatically generates clustered grids without manual prescription of decay parameters needed with the conventional approach. In fact, these decay parameters are calculated as decay functions as part of the solution, and they are not constant over a given boundary. Since these decay functions vary over a given boundary, orthogonal grids near any arbitrary boundary can be clustered automatically without having to break up the boundaries and the corresponding interior domains into various zones for grid generation.
NASA Astrophysics Data System (ADS)
Han, Minah; Baek, Jongduk
2017-03-01
We investigate location dependent lesion detectability of cone beam computed tomography images for different background types (i.e., uniform and anatomical), image planes (i.e., transverse and longitudinal) and slice thicknesses. Anatomical backgrounds are generated using a power law spectrum of breast anatomy, 1/f3. Spherical object with a 5mm diameter is used as a signal. CT projection data are acquired by the forward projection of uniform and anatomical backgrounds with and without the signal. Then, projection data are reconstructed using the FDK algorithm. Detectability is evaluated by a channelized Hotelling observer with dense difference-of-Gaussian channels. For uniform background, off-centered images yield higher detectability than iso-centered images for the transverse plane, while for the longitudinal plane, detectability of iso-centered and off-centered images are similar. For anatomical background, off-centered images yield higher detectability for the transverse plane, while iso-centered images yield higher detectability for the longitudinal plane, when the slice thickness is smaller than 1.9mm. The optimal slice thickness is 3.8mm for all tasks, and the transverse plane at the off-center (iso-center and off-center) produces the highest detectability for uniform (anatomical) background.
Dedicated ultrasound speckle tracking to study tendon displacement
NASA Astrophysics Data System (ADS)
Korstanje, Jan-Wiebe H.; Selles, Ruud W.; Stam, Henk J.; Hovius, Steven E. R.; Bosch, Johan G.
2009-02-01
Ultrasound can be used to study tendon and muscle movement. However, quantization is mostly based on manual tracking of anatomical landmarks such as the musculotendinous junction, limiting the applicability to a small number of muscle-tendon units. The aim of this study is to quantify tendon displacement without employing anatomical landmarks, using dedicated speckle tracking in long B-mode image sequences. We devised a dedicated two-dimensional multikernel block-matching scheme with subpixel accuracy to handle large displacements over long sequences. Images were acquired with a Philips iE33 with a 7 MHz linear array and a VisualSonics Vevo 770 using a 40 MHz mechanical probe. We displaced the flexor digitorum superficialis of two pig cadaver forelegs with three different velocities (4,10 and 16 mm/s) over 3 distances (5, 10, 15 mm). As a reference, we manually determined the total displacement of an injected hyperechogenic bullet in the tendons. We automatically tracked tendon parts with and without markers and compared results to the true displacement. Using the iE33, mean tissue displacement underestimations for the three different velocities were 2.5 +/- 1.0%, 1.7 +/- 1.1% and 0.7 +/- 0.4%. Using the Vevo770, mean tissue displacement underestimations were 0.8 +/- 1.3%, 0.6 +/- 0.3% and 0.6 +/- 0.3%. Marker tracking displacement underestimations were only slightly smaller, showing limited tracking drift for non-marker tendon tissue as well as for markers. This study showed that our dedicated speckle tracking can quantify extensive tendon displacement with physiological velocities without anatomical landmarks with good accuracy for different types of ultrasound configurations. This technique allows tracking of a much larger range of muscle-tendon units than by using anatomical landmarks.
Atlas-Guided Cluster Analysis of Large Tractography Datasets
Ros, Christian; Güllmar, Daniel; Stenzel, Martin; Mentzel, Hans-Joachim; Reichenbach, Jürgen Rainer
2013-01-01
Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment. PMID:24386292
Atlas-based automatic measurements of the morphology of the tibiofemoral joint
NASA Astrophysics Data System (ADS)
Brehler, M.; Thawait, G.; Shyr, W.; Ramsay, J.; Siewerdsen, J. H.; Zbijewski, W.
2017-03-01
Purpose: Anatomical metrics of the tibiofemoral joint support assessment of joint stability and surgical planning. We propose an automated, atlas-based algorithm to streamline the measurements in 3D images of the joint and reduce userdependence of the metrics arising from manual identification of the anatomical landmarks. Methods: The method is initialized with coarse registrations of a set of atlas images to the fixed input image. The initial registrations are then refined separately for the tibia and femur and the best matching atlas is selected. Finally, the anatomical landmarks of the best matching atlas are transformed onto the input image by deforming a surface model of the atlas to fit the shape of the tibial plateau in the input image (a mesh-to-volume registration). We apply the method to weight-bearing volumetric images of the knee obtained from 23 subjects using an extremity cone-beam CT system. Results of the automated algorithm were compared to an expert radiologist for measurements of Static Alignment (SA), Medial Tibial Slope (MTS) and Lateral Tibial Slope (LTS). Results: Intra-reader variability as high as 10% for LTS and 7% for MTS (ratio of standard deviation to the mean in repeated measurements) was found for expert radiologist, illustrating the potential benefits of an automated approach in improving the precision of the metrics. The proposed method achieved excellent registration of the atlas mesh to the input volumes. The resulting automated measurements yielded high correlations with expert radiologist, as indicated by correlation coefficients of 0.72 for MTS, 0.8 for LTS, and 0.89 for SA. Conclusions: The automated method for measurement of anatomical metrics of the tibiofemoral joint achieves high correlation with expert radiologist without the need for time consuming and error prone manual selection of landmarks.
Atlas-based automatic measurements of the morphology of the tibiofemoral joint.
Brehler, M; Thawait, G; Shyr, W; Ramsay, J; Siewerdsen, J H; Zbijewski, W
2017-02-11
Anatomical metrics of the tibiofemoral joint support assessment of joint stability and surgical planning. We propose an automated, atlas-based algorithm to streamline the measurements in 3D images of the joint and reduce user-dependence of the metrics arising from manual identification of the anatomical landmarks. The method is initialized with coarse registrations of a set of atlas images to the fixed input image. The initial registrations are then refined separately for the tibia and femur and the best matching atlas is selected. Finally, the anatomical landmarks of the best matching atlas are transformed onto the input image by deforming a surface model of the atlas to fit the shape of the tibial plateau in the input image (a mesh-to-volume registration). We apply the method to weight-bearing volumetric images of the knee obtained from 23 subjects using an extremity cone-beam CT system. Results of the automated algorithm were compared to an expert radiologist for measurements of Static Alignment (SA), Medial Tibial Slope (MTS) and Lateral Tibial Slope (LTS). Intra-reader variability as high as ~10% for LTS and 7% for MTS (ratio of standard deviation to the mean in repeated measurements) was found for expert radiologist, illustrating the potential benefits of an automated approach in improving the precision of the metrics. The proposed method achieved excellent registration of the atlas mesh to the input volumes. The resulting automated measurements yielded high correlations with expert radiologist, as indicated by correlation coefficients of 0.72 for MTS, 0.8 for LTS, and 0.89 for SA. The automated method for measurement of anatomical metrics of the tibiofemoral joint achieves high correlation with expert radiologist without the need for time consuming and error prone manual selection of landmarks.
Verhaart, René F; Fortunati, Valerio; Verduijn, Gerda M; van Walsum, Theo; Veenland, Jifke F; Paulides, Margarethus M
2014-04-01
Clinical trials have shown that hyperthermia, as adjuvant to radiotherapy and/or chemotherapy, improves treatment of patients with locally advanced or recurrent head and neck (H&N) carcinoma. Hyperthermia treatment planning (HTP) guided H&N hyperthermia is being investigated, which requires patient specific 3D patient models derived from Computed Tomography (CT)-images. To decide whether a recently developed automatic-segmentation algorithm can be introduced in the clinic, we compared the impact of manual- and automatic normal-tissue-segmentation variations on HTP quality. CT images of seven patients were segmented automatically and manually by four observers, to study inter-observer and intra-observer geometrical variation. To determine the impact of this variation on HTP quality, HTP was performed using the automatic and manual segmentation of each observer, for each patient. This impact was compared to other sources of patient model uncertainties, i.e. varying gridsizes and dielectric tissue properties. Despite geometrical variations, manual and automatic generated 3D patient models resulted in an equal, i.e. 1%, variation in HTP quality. This variation was minor with respect to the total of other sources of patient model uncertainties, i.e. 11.7%. Automatically generated 3D patient models can be introduced in the clinic for H&N HTP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Evaluation of the efficiency and fault density of software generated by code generators
NASA Technical Reports Server (NTRS)
Schreur, Barbara
1993-01-01
Flight computers and flight software are used for GN&C (guidance, navigation, and control), engine controllers, and avionics during missions. The software development requires the generation of a considerable amount of code. The engineers who generate the code make mistakes and the generation of a large body of code with high reliability requires considerable time. Computer-aided software engineering (CASE) tools are available which generates code automatically with inputs through graphical interfaces. These tools are referred to as code generators. In theory, code generators could write highly reliable code quickly and inexpensively. The various code generators offer different levels of reliability checking. Some check only the finished product while some allow checking of individual modules and combined sets of modules as well. Considering NASA's requirement for reliability, an in house manually generated code is needed. Furthermore, automatically generated code is reputed to be as efficient as the best manually generated code when executed. In house verification is warranted.
Automatic structured grid generation using Gridgen (some restrictions apply)
NASA Technical Reports Server (NTRS)
Chawner, John R.; Steinbrenner, John P.
1995-01-01
The authors have noticed in the recent grid generation literature an emphasis on the automation of structured grid generation. The motivation behind such work is clear; grid generation is easily the most despised task in the grid-analyze-visualize triad of computational analysis (CA). However, because grid generation is closely coupled to both the design and analysis software and because quantitative measures of grid quality are lacking, 'push button' grid generation usually results in a compromise between speed, control, and quality. Overt emphasis on automation obscures the substantive issues of providing users with flexible tools for generating and modifying high quality grids in a design environment. In support of this paper's tongue-in-cheek title, many features of the Gridgen software are described. Gridgen is by no stretch of the imagination an automatic grid generator. Despite this fact, the code does utilize many automation techniques that permit interesting regenerative features.
NASA Technical Reports Server (NTRS)
Macala, G. A.
1983-01-01
A computer program is described that can automatically generate symbolic equations of motion for systems of hinge-connected rigid bodies with tree topologies. The dynamical formulation underlying the program is outlined, and examples are given to show how a symbolic language is used to code the formulation. The program is applied to generate the equations of motion for a four-body model of the Galileo spacecraft. The resulting equations are shown to be a factor of three faster in execution time than conventional numerical subroutines.
Model-Based GUI Testing Using Uppaal at Novo Nordisk
NASA Astrophysics Data System (ADS)
Hjort, Ulrik H.; Illum, Jacob; Larsen, Kim G.; Petersen, Michael A.; Skou, Arne
This paper details a collaboration between Aalborg University and Novo Nordiskin developing an automatic model-based test generation tool for system testing of the graphical user interface of a medical device on an embedded platform. The tool takes as input an UML Statemachine model and generates a test suite satisfying some testing criterion, such as edge or state coverage, and converts the individual test case into a scripting language that can be automatically executed against the target. The tool has significantly reduced the time required for test construction and generation, and reduced the number of test scripts while increasing the coverage.
Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan
A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hui, Cheukkai; Suh, Yelin; Robertson, Daniel
Purpose: The purpose of this study was to develop a novel algorithm to create a robust internal respiratory signal (IRS) for retrospective sorting of four-dimensional (4D) computed tomography (CT) images. Methods: The proposed algorithm combines information from the Fourier transform of the CT images and from internal anatomical features to form the IRS. The algorithm first extracts potential respiratory signals from low-frequency components in the Fourier space and selected anatomical features in the image space. A clustering algorithm then constructs groups of potential respiratory signals with similar temporal oscillation patterns. The clustered group with the largest number of similar signalsmore » is chosen to form the final IRS. To evaluate the performance of the proposed algorithm, the IRS was computed and compared with the external respiratory signal from the real-time position management (RPM) system on 80 patients. Results: In 72 (90%) of the 4D CT data sets tested, the IRS computed by the authors’ proposed algorithm matched with the RPM signal based on their normalized cross correlation. For these data sets with matching respiratory signals, the average difference between the end inspiration times (Δt{sub ins}) in the IRS and RPM signal was 0.11 s, and only 2.1% of Δt{sub ins} were more than 0.5 s apart. In the eight (10%) 4D CT data sets in which the IRS and the RPM signal did not match, the average Δt{sub ins} was 0.73 s in the nonmatching couch positions, and 35.4% of them had a Δt{sub ins} greater than 0.5 s. At couch positions in which IRS did not match the RPM signal, a correlation-based metric indicated poorer matching of neighboring couch positions in the RPM-sorted images. This implied that, when IRS did not match the RPM signal, the images sorted using the IRS showed fewer artifacts than the clinical images sorted using the RPM signal. Conclusions: The authors’ proposed algorithm can generate robust IRSs that can be used for retrospective sorting of 4D CT data. The algorithm is completely automatic and requires very little processing time. The algorithm is cost efficient and can be easily adopted for everyday clinical use.« less
Design automation techniques for custom LSI arrays
NASA Technical Reports Server (NTRS)
Feller, A.
1975-01-01
The standard cell design automation technique is described as an approach for generating random logic PMOS, CMOS or CMOS/SOS custom large scale integration arrays with low initial nonrecurring costs and quick turnaround time or design cycle. The system is composed of predesigned circuit functions or cells and computer programs capable of automatic placement and interconnection of the cells in accordance with an input data net list. The program generates a set of instructions to drive an automatic precision artwork generator. A series of support design automation and simulation programs are described, including programs for verifying correctness of the logic on the arrays, performing dc and dynamic analysis of MOS devices, and generating test sequences.
Generating Models of Surgical Procedures using UMLS Concepts and Multiple Sequence Alignment
Meng, Frank; D’Avolio, Leonard W.; Chen, Andrew A.; Taira, Ricky K.; Kangarloo, Hooshang
2005-01-01
Surgical procedures can be viewed as a process composed of a sequence of steps performed on, by, or with the patient’s anatomy. This sequence is typically the pattern followed by surgeons when generating surgical report narratives for documenting surgical procedures. This paper describes a methodology for semi-automatically deriving a model of conducted surgeries, utilizing a sequence of derived Unified Medical Language System (UMLS) concepts for representing surgical procedures. A multiple sequence alignment was computed from a collection of such sequences and was used for generating the model. These models have the potential of being useful in a variety of informatics applications such as information retrieval and automatic document generation. PMID:16779094
Activity classification using realistic data from wearable sensors.
Pärkkä, Juha; Ermes, Miikka; Korpipää, Panu; Mäntyjärvi, Jani; Peltola, Johannes; Korhonen, Ilkka
2006-01-01
Automatic classification of everyday activities can be used for promotion of health-enhancing physical activities and a healthier lifestyle. In this paper, methods used for classification of everyday activities like walking, running, and cycling are described. The aim of the study was to find out how to recognize activities, which sensors are useful and what kind of signal processing and classification is required. A large and realistic data library of sensor data was collected. Sixteen test persons took part in the data collection, resulting in approximately 31 h of annotated, 35-channel data recorded in an everyday environment. The test persons carried a set of wearable sensors while performing several activities during the 2-h measurement session. Classification results of three classifiers are shown: custom decision tree, automatically generated decision tree, and artificial neural network. The classification accuracies using leave-one-subject-out cross validation range from 58 to 97% for custom decision tree classifier, from 56 to 97% for automatically generated decision tree, and from 22 to 96% for artificial neural network. Total classification accuracy is 82 % for custom decision tree classifier, 86% for automatically generated decision tree, and 82% for artificial neural network.
Bone morphology of the hind limbs in two caviomorph rodents.
de Araújo, F A P; Sesoko, N F; Rahal, S C; Teixeira, C R; Müller, T R; Machado, M R F
2013-04-01
In order to evaluate the hind limbs of caviomorph rodents a descriptive analysis of the Cuniculus paca (Linnaeus, 1766) and Hydrochoerus hydrochaeris (Linnaeus, 1766) was performed using anatomical specimens, radiography, computed tomography (CT) and full-coloured prototype models to generate bone anatomy data. The appendicular skeleton of the two largest rodents of Neotropical America was compared with the previously reported anatomical features of Rattus norvegicus (Berkenhout, 1769) and domestic Cavia porcellus (Linnaeus, 1758). The structures were analyzed macroscopically and particular findings of each species reported. Features including the presence of articular fibular projection and lunulae were observed in the stifle joint of all rodents. Imaging aided in anatomical description and, specifically in the identification of bone structures in Cuniculus paca and Hydrochoerus hydrochaeris. The imaging findings were correlated with the anatomical structures observed. The data may be used in future studies comparing these animals to other rodents and mammalian species. © 2012 Blackwell Verlag GmbH.
Automatic target validation based on neuroscientific literature mining for tractography
Vasques, Xavier; Richardet, Renaud; Hill, Sean L.; Slater, David; Chappelier, Jean-Cedric; Pralong, Etienne; Bloch, Jocelyne; Draganski, Bogdan; Cif, Laura
2015-01-01
Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/. PMID:26074781
Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery.
Ketcha, M D; De Silva, T; Uneri, A; Kleinszig, G; Vogt, S; Wolinsky, J-P; Siewerdsen, J H
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.
Rise and fall of the two visual systems theory.
Rossetti, Yves; Pisella, Laure; McIntosh, Robert D
2017-06-01
Among the many dissociations describing the visual system, the dual theory of two visual systems, respectively dedicated to perception and action, has yielded a lot of support. There are psychophysical, anatomical and neuropsychological arguments in favor of this theory. Several behavioral studies that used sensory and motor psychophysical parameters observed differences between perceptive and motor responses. The anatomical network of the visual system in the non-human primate was very readily organized according to two major pathways, dorsal and ventral. Neuropsychological studies, exploring optic ataxia and visual agnosia as characteristic deficits of these two pathways, led to the proposal of a functional double dissociation between visuomotor and visual perceptual functions. After a major wave of popularity that promoted great advances, particularly in knowledge of visuomotor functions, the guiding theory is now being reconsidered. Firstly, the idea of a double dissociation between optic ataxia and visual form agnosia, as cleanly separating visuomotor from visual perceptual functions, is no longer tenable; optic ataxia does not support a dissociation between perception and action and might be more accurately viewed as a negative image of action blindsight. Secondly, dissociations between perceptive and motor responses highlighted in the framework of this theory concern a very elementary level of action, even automatically guided action routines. Thirdly, the very rich interconnected network of the visual brain yields few arguments in favor of a strict perception/action dissociation. Overall, the dissociation between motor function and perceptive function explored by these behavioral and neuropsychological studies can help define an automatic level of action organization deficient in optic ataxia and preserved in action blindsight, and underlines the renewed need to consider the perception-action circle as a functional ensemble. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Automatic masking for robust 3D-2D image registration in image-guided spine surgery
NASA Astrophysics Data System (ADS)
Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.
2016-03-01
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.
Ross, Douglas H.; Clark, Mark E.; Godara, Pooja; Huisingh, Carrie; McGwin, Gerald; Owsley, Cynthia; Litts, Katie M.; Spaide, Richard F.; Sloan, Kenneth R.; Curcio, Christine A.
2015-01-01
Purpose. To validate a model-driven method (RefMoB) of automatically describing the four outer retinal hyperreflective bands revealed by spectral-domain optical coherence tomography (SDOCT), for comparison with histology of normal macula; to report thickness and position of bands, particularly band 2 (ellipsoid zone [EZ], commonly called IS/OS). Methods. Foveal and superior perifoveal scans of seven SDOCT volumes of five individuals aged 28 to 69 years with healthy maculas were used (seven eyes for validation, five eyes for measurement). RefMoB determines band thickness and position by a multistage procedure that models reflectivities as a summation of Gaussians. Band thickness and positions were compared with those obtained by manual evaluators for the same scans, and compared with an independent published histological dataset. Results. Agreement among manual evaluators was moderate. Relative to manual evaluation, RefMoB reported reduced thickness and vertical shifts in band positions in a band-specific manner for both simulated and empirical data. In foveal and perifoveal scans, band 1 was thick relative to the anatomical external limiting membrane, band 2 aligned with the outer one-third of the anatomical IS ellipsoid, and band 3 (IZ, interdigitation of retinal pigment epithelium and photoreceptors) was cleanly delineated. Conclusions. RefMoB is suitable for automatic description of the location and thickness of the four outer retinal hyperreflective bands. Initial results suggest that band 2 aligns with the outer ellipsoid, thus supporting its recent designation as EZ. Automated and objective delineation of band 3 will help investigations of structural biomarkers of dark-adaptation changes in aging. PMID:26132776
Chen, Jiang-Hong; Jin, Er-Hu; He, Wen; Zhao, Li-Qin
2014-01-01
Objective To reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM). Methods Patients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded. Results Increased NI was associated with increased subjective and objective image noise results (P<0.001), and SNR decreased with increasing NI (P<0.001). These values improved with increased ASIR levels (P<0.001). Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79±1.17, 1.69±0.59, 0.74±0.29, and 0.37±0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively. Conclusions Using NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED. PMID:24691208
Chen, Jiang-Hong; Jin, Er-Hu; He, Wen; Zhao, Li-Qin
2014-01-01
To reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM). Patients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded. Increased NI was associated with increased subjective and objective image noise results (P<0.001), and SNR decreased with increasing NI (P<0.001). These values improved with increased ASIR levels (P<0.001). Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79 ± 1.17, 1.69 ± 0.59, 0.74 ± 0.29, and 0.37 ± 0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively. Using NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.
Cerveri, Pietro; Marchente, Mario; Bartels, Ward; Corten, Kristoff; Simon, Jean-Pierre; Manzotti, Alfonso
2010-09-01
The femoral shaft (FDA) and transepicondylar (TA), anterior-posterior (WL) and posterior condylar (PCL) axes are fundamental quantities in planning knee arthroplasty surgery. As an alternative to the TA, we introduce the anatomical flexion axis (AFA). Obtaining such axes from image data without any manual supervision remains a practical objective. We propose a novel method that automatically computes the axes of the distal femur by processing the femur mesh surface. Surface data were processed by exploiting specific geometric, anatomical and functional properties. Robust ellipse fitting of the two-dimensional (2D) condylar profiles was utilized to determine the AFA alternative to the TA. The repeatability of the method was tested upon 20 femur surfaces reconstructed from CT scans taken on cadavers. At the highest surface resolutions, the relative median error in the direction of the FDA, AFA, PCL, WL and TA was < 0.50 degrees, 1.20 degrees, 1.0 degrees, 1.30 degrees and 1.50 degrees, respectively. As expected, at the lowest surface resolution, the repeatability decreased to 1.20 degrees, 2.70 degrees, 3.30 degrees, 3.0 degrees and 4.70 degrees, respectively. The computed directions of the FDA, PCL, WL and TA were in agreement (0.60 degrees, 1.55 degrees, 1.90 degrees, 2.40 degrees) with the corresponding reference parameters manually identified in the original CT images by medical experts and with the literature. The proposed method proved that: (a) the AFA can be robustly computed by a geometrical analysis of the posterior profiles of the two condyles and can be considered a useful alternative to the TA; (b) higher surface resolutions leads to higher repeatability of all computed quantities; (c) the TA is less repeatable than the other axes. Copyright 2010 John Wiley & Sons, Ltd.
Automatic generation of pictorial transcripts of video programs
NASA Astrophysics Data System (ADS)
Shahraray, Behzad; Gibbon, David C.
1995-03-01
An automatic authoring system for the generation of pictorial transcripts of video programs which are accompanied by closed caption information is presented. A number of key frames, each of which represents the visual information in a segment of the video (i.e., a scene), are selected automatically by performing a content-based sampling of the video program. The textual information is recovered from the closed caption signal and is initially segmented based on its implied temporal relationship with the video segments. The text segmentation boundaries are then adjusted, based on lexical analysis and/or caption control information, to account for synchronization errors due to possible delays in the detection of scene boundaries or the transmission of the caption information. The closed caption text is further refined through linguistic processing for conversion to lower- case with correct capitalization. The key frames and the related text generate a compact multimedia presentation of the contents of the video program which lends itself to efficient storage and transmission. This compact representation can be viewed on a computer screen, or used to generate the input to a commercial text processing package to generate a printed version of the program.
Representation of research hypotheses
2011-01-01
Background Hypotheses are now being automatically produced on an industrial scale by computers in biology, e.g. the annotation of a genome is essentially a large set of hypotheses generated by sequence similarity programs; and robot scientists enable the full automation of a scientific investigation, including generation and testing of research hypotheses. Results This paper proposes a logically defined way for recording automatically generated hypotheses in machine amenable way. The proposed formalism allows the description of complete hypotheses sets as specified input and output for scientific investigations. The formalism supports the decomposition of research hypotheses into more specialised hypotheses if that is required by an application. Hypotheses are represented in an operational way – it is possible to design an experiment to test them. The explicit formal description of research hypotheses promotes the explicit formal description of the results and conclusions of an investigation. The paper also proposes a framework for automated hypotheses generation. We demonstrate how the key components of the proposed framework are implemented in the Robot Scientist “Adam”. Conclusions A formal representation of automatically generated research hypotheses can help to improve the way humans produce, record, and validate research hypotheses. Availability http://www.aber.ac.uk/en/cs/research/cb/projects/robotscientist/results/ PMID:21624164
Run-Time Support for Rapid Prototyping
1988-12-01
prototyping. One such system is the Computer-Aided Proto- typing System (CAPS). It combines rapid prototypng with automatic program generation. Some of the...a design database, and a design management system [Ref. 3:p. 66. By using both rapid prototyping and automatic program genera- tion. CAPS will be...Most proto- typing systems perform these functions. CAPS is different in that it combines rapid prototyping with a variant of automatic program
Mento, Giovanni
2017-12-01
A main distinction has been proposed between voluntary and automatic mechanisms underlying temporal orienting (TO) of selective attention. Voluntary TO implies the endogenous directing of attention induced by symbolic cues. Conversely, automatic TO is exogenously instantiated by the physical properties of stimuli. A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli. In this study a group of healthy adults underwent a cued reaction time task purposely designed to assess both voluntary and automatic TO. During the task, both post-cue and post-target event-related potentials (ERPs) were recorded by means of a high spatial resolution EEG system. In the results of the post-cue analysis, the P3a and P3b were identified as two distinct ERP markers showing distinguishable spatiotemporal features and reflecting automatic and voluntary a priori expectancy generation, respectively. The brain source reconstruction further revealed that distinct cortical circuits supported these two temporally dissociable components. Namely, the voluntary P3b was supported by a left sensorimotor network, while the automatic P3a was generated by a more distributed frontoparietal circuit. Additionally, post-cue contingent negative variation (CNV) and post-target P3 modulations were observed as common markers of voluntary and automatic expectancy implementation and response selection, although partially dissociable neural networks subserved these two mechanisms. Overall, these results provide new electrophysiological evidence suggesting that distinct neural substrates can be recruited depending on the voluntary or automatic cognitive nature of the cognitive mechanisms subserving TO. Copyright © 2017 Elsevier Ltd. All rights reserved.
Applying reliability analysis to design electric power systems for More-electric aircraft
NASA Astrophysics Data System (ADS)
Zhang, Baozhu
The More-Electric Aircraft (MEA) is a type of aircraft that replaces conventional hydraulic and pneumatic systems with electrically powered components. These changes have significantly challenged the aircraft electric power system design. This thesis investigates how reliability analysis can be applied to automatically generate system topologies for the MEA electric power system. We first use a traditional method of reliability block diagrams to analyze the reliability level on different system topologies. We next propose a new methodology in which system topologies, constrained by a set reliability level, are automatically generated. The path-set method is used for analysis. Finally, we interface these sets of system topologies with control synthesis tools to automatically create correct-by-construction control logic for the electric power system.
Die Starter: A New System to Manage Early Feasibility in Sheet Metal Forming
NASA Astrophysics Data System (ADS)
Narainen, Rodrigue; Porzner, Harald
2016-08-01
Die Starter, a new system developed by ESI Group, allows the user to drastically reduce the number of iterations during the early tool process feasibility. This innovative system automatically designs the first quick die face, generating binder and addendum surfaces (NURBS surfaces) by taking account the full die process. Die Starter also improves the initial die face based on feasibility criteria (avoiding splits, wrinkles) by automatically generating the geometrical modifications of the binder and addendum and the bead restraining forces with minimal material usage. This paper presents a description of the new system and the methodology of Die Starter. Some industrial examples are presented from the part geometry to final die face including automatic developed flanges, part on binder and inner binder.
Blacker, Teddy D.
1994-01-01
An automatic quadrilateral surface discretization method and apparatus is provided for automatically discretizing a geometric region without decomposing the region. The automated quadrilateral surface discretization method and apparatus automatically generates a mesh of all quadrilateral elements which is particularly useful in finite element analysis. The generated mesh of all quadrilateral elements is boundary sensitive, orientation insensitive and has few irregular nodes on the boundary. A permanent boundary of the geometric region is input and rows are iteratively layered toward the interior of the geometric region. Also, an exterior permanent boundary and an interior permanent boundary for a geometric region may be input and the rows are iteratively layered inward from the exterior boundary in a first counter clockwise direction while the rows are iteratively layered from the interior permanent boundary toward the exterior of the region in a second clockwise direction. As a result, a high quality mesh for an arbitrary geometry may be generated with a technique that is robust and fast for complex geometric regions and extreme mesh gradations.
Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel
2013-04-15
In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.
2013-01-01
Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394
Segmentation and feature extraction of cervical spine x-ray images
NASA Astrophysics Data System (ADS)
Long, L. Rodney; Thoma, George R.
1999-05-01
As part of an R&D project in mixed text/image database design, the National Library of Medicine has archived a collection of 17,000 digitized x-ray images of the cervical and lumbar spine which were collected as part of the second National Health and Nutrition Examination Survey (NHANES II). To make this image data available and usable to a wide audience, we are investigating techniques for indexing the image content by automated or semi-automated means. Indexing of the images by features of interest to researchers in spine disease and structure requires effective segmentation of the vertebral anatomy. This paper describes work in progress toward this segmentation of the cervical spine images into anatomical components of interest, including anatomical landmarks for vertebral location, and segmentation and identification of individual vertebrae. Our work includes developing a reliable method for automatically fixing an anatomy-based coordinate system in the images, and work to adaptively threshold the images, using methods previously applied by researchers in cardioangiography. We describe the motivation for our work and present our current results in both areas.
On describing human white matter anatomy: the white matter query language.
Wassermann, Demian; Makris, Nikos; Rathi, Yogesh; Shenton, Martha; Kikinis, Ron; Kubicki, Marek; Westin, Carl-Fredrik
2013-01-01
The main contribution of this work is the careful syntactical definition of major white matter tracts in the human brain based on a neuroanatomist's expert knowledge. We present a technique to formally describe white matter tracts and to automatically extract them from diffusion MRI data. The framework is based on a novel query language with a near-to-English textual syntax. This query language allows us to construct a dictionary of anatomical definitions describing white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This enables automated coherent labeling of white matter anatomy across subjects. We use our method to encode anatomical knowledge in human white matter describing 10 association and 8 projection tracts per hemisphere and 7 commissural tracts. The technique is shown to be comparable in accuracy to manual labeling. We present results applying this framework to create a white matter atlas from 77 healthy subjects, and we use this atlas in a proof-of-concept study to detect tract changes specific to schizophrenia.
Interactive-rate Motion Planning for Concentric Tube Robots.
Torres, Luis G; Baykal, Cenk; Alterovitz, Ron
2014-05-01
Concentric tube robots may enable new, safer minimally invasive surgical procedures by moving along curved paths to reach difficult-to-reach sites in a patient's anatomy. Operating these devices is challenging due to their complex, unintuitive kinematics and the need to avoid sensitive structures in the anatomy. In this paper, we present a motion planning method that computes collision-free motion plans for concentric tube robots at interactive rates. Our method's high speed enables a user to continuously and freely move the robot's tip while the motion planner ensures that the robot's shaft does not collide with any anatomical obstacles. Our approach uses a highly accurate mechanical model of tube interactions, which is important since small movements of the tip position may require large changes in the shape of the device's shaft. Our motion planner achieves its high speed and accuracy by combining offline precomputation of a collision-free roadmap with online position control. We demonstrate our interactive planner in a simulated neurosurgical scenario where a user guides the robot's tip through the environment while the robot automatically avoids collisions with the anatomical obstacles.
Different Manhattan project: automatic statistical model generation
NASA Astrophysics Data System (ADS)
Yap, Chee Keng; Biermann, Henning; Hertzmann, Aaron; Li, Chen; Meyer, Jon; Pao, Hsing-Kuo; Paxia, Salvatore
2002-03-01
We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.
NASA Astrophysics Data System (ADS)
van de Water, Steven; Albertini, Francesca; Weber, Damien C.; Heijmen, Ben J. M.; Hoogeman, Mischa S.; Lomax, Antony J.
2018-01-01
The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 ‘synthetic’ CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system ‘Erasmus-iCycle’ was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 GyRBE treatment, assuming each synthetic CT to correspond to a 2 GyRBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V95% ⩾ 98% and V107% ⩽ 2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 GyRBE (20%) higher when using SFUD optimization and on average 3.6 GyRBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and OAR doses compared with conventional SFUD optimization. OAR doses can be further reduced by using online plan adaptation.
A whole brain atlas with sub-parcellation of cortical gyri using resting fMRI
NASA Astrophysics Data System (ADS)
Joshi, Anand A.; Choi, Soyoung; Sonkar, Gaurav; Chong, Minqi; Gonzalez-Martinez, Jorge; Nair, Dileep; Shattuck, David W.; Damasio, Hanna; Leahy, Richard M.
2017-02-01
The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex. Anatomical labeling was performed manually on coronal single-slice images guided by sulcal and gyral landmarks to generate the original (non-hybrid) BCI-DNI atlas. Functional sub-parcellations of the gyral ROIs were then generated from 40 minimally preprocessed resting fMRI datasets from the HCP database. Gyral ROIs were transferred from the BCI-DNI atlas to the 40 subjects using the HCP grayordinate space as a reference. For each subject, each gyral ROI was subdivided using the fMRI data by applying spectral clustering to a similarity matrix computed from the fMRI time-series correlations between each vertex pair. The sub-parcellations were then transferred back to the original cortical mesh to create the subparcellated hBCI-DNI atlas with a total of 67 cortical regions per hemisphere. To assess the stability of the gyral subdivisons, a separate set of 60 HCP datasets were processed as follows: 1) coregistration of the structural scans to the hBCI-DNI atlas; 2) coregistration of the anatomical BCI-DNI atlas without functional subdivisions, followed by sub-parcellation of each subject's resting fMRI data as described above. We then computed consistency between the anatomically-driven delineation of each gyral subdivision and that obtained per subject using individual fMRI data. The gyral sub-parcellations generated by atlas-based registration show variable but generally good overlap of the confidence intervals with the resting fMRI-based subdivisions. These consistency measures will provide a quantitative measure of reliability of each subdivision to users of the atlas.
Nagarajan, Mahesh B; Raman, Steven S; Lo, Pechin; Lin, Wei-Chan; Khoshnoodi, Pooria; Sayre, James W; Ramakrishna, Bharath; Ahuja, Preeti; Huang, Jiaoti; Margolis, Daniel J A; Lu, David S K; Reiter, Robert E; Goldin, Jonathan G; Brown, Matthew S; Enzmann, Dieter R
2018-02-19
We present a method for generating a T2 MR-based probabilistic model of tumor occurrence in the prostate to guide the selection of anatomical sites for targeted biopsies and serve as a diagnostic tool to aid radiological evaluation of prostate cancer. In our study, the prostate and any radiological findings within were segmented retrospectively on 3D T2-weighted MR images of 266 subjects who underwent radical prostatectomy. Subsequent histopathological analysis determined both the ground truth and the Gleason grade of the tumors. A randomly chosen subset of 19 subjects was used to generate a multi-subject-derived prostate template. Subsequently, a cascading registration algorithm involving both affine and non-rigid B-spline transforms was used to register the prostate of every subject to the template. Corresponding transformation of radiological findings yielded a population-based probabilistic model of tumor occurrence. The quality of our probabilistic model building approach was statistically evaluated by measuring the proportion of correct placements of tumors in the prostate template, i.e., the number of tumors that maintained their anatomical location within the prostate after their transformation into the prostate template space. Probabilistic model built with tumors deemed clinically significant demonstrated a heterogeneous distribution of tumors, with higher likelihood of tumor occurrence at the mid-gland anterior transition zone and the base-to-mid-gland posterior peripheral zones. Of 250 MR lesions analyzed, 248 maintained their original anatomical location with respect to the prostate zones after transformation to the prostate. We present a robust method for generating a probabilistic model of tumor occurrence in the prostate that could aid clinical decision making, such as selection of anatomical sites for MR-guided prostate biopsies.
Automatic computation and solution of generalized harmonic balance equations
NASA Astrophysics Data System (ADS)
Peyton Jones, J. C.; Yaser, K. S. A.; Stevenson, J.
2018-02-01
Generalized methods are presented for generating and solving the harmonic balance equations for a broad class of nonlinear differential or difference equations and for a general set of harmonics chosen by the user. In particular, a new algorithm for automatically generating the Jacobian of the balance equations enables efficient solution of these equations using continuation methods. Efficient numeric validation techniques are also presented, and the combined algorithm is applied to the analysis of dc, fundamental, second and third harmonic response of a nonlinear automotive damper.
Automatic item generation implemented for measuring artistic judgment aptitude.
Bezruczko, Nikolaus
2014-01-01
Automatic item generation (AIG) is a broad class of methods that are being developed to address psychometric issues arising from internet and computer-based testing. In general, issues emphasize efficiency, validity, and diagnostic usefulness of large scale mental testing. Rapid prominence of AIG methods and their implicit perspective on mental testing is bringing painful scrutiny to many sacred psychometric assumptions. This report reviews basic AIG ideas, then presents conceptual foundations, image model development, and operational application to artistic judgment aptitude testing.
Nondestructive Vibratory Testing and Evaluation Procedure for Military Roads and Streets.
1984-07-01
the addition of an auto- matic data acquisition system to the instrumentation control panel. This system , presently available, would automatically ...the data used to further develop and define the basic correlations. c. Consideration be given to installing an automatic data acquisi- tion system to...glows red any time the force generator is not fully elevated. Depressing this switch will stop the automatic cycle at any point and clear all system
Haneder, Stefan; Siedek, Florian; Doerner, Jonas; Pahn, Gregor; Grosse Hokamp, Nils; Maintz, David; Wybranski, Christian
2018-01-01
Background A novel, multi-energy, dual-layer spectral detector computed tomography (SDCT) is commercially available now with the vendor's claim that it yields the same or better quality of polychromatic, conventional CT images like modern single-energy CT scanners without any radiation dose penalty. Purpose To intra-individually compare the quality of conventional polychromatic CT images acquired with a dual-layer spectral detector (SDCT) and the latest generation 128-row single-energy-detector (CT128) from the same manufacturer. Material and Methods Fifty patients underwent portal-venous phase, thoracic-abdominal CT scans with the SDCT and prior CT128 imaging. The SDCT scanning protocol was adapted to yield a similar estimated dose length product (DLP) as the CT128. Patient dose optimization by automatic tube current modulation and CT image reconstruction with a state-of-the-art iterative algorithm were identical on both scanners. CT image contrast-to-noise ratio (CNR) was compared between the SDCT and CT128 in different anatomic structures. Image quality and noise were assessed independently by two readers with 5-point-Likert-scales. Volume CT dose index (CTDI vol ), and DLP were recorded and normalized to 68 cm acquisition length (DLP 68 ). Results The SDCT yielded higher mean CNR values of 30.0% ± 2.0% (26.4-32.5%) in all anatomic structures ( P < 0.001) and excellent scores for qualitative parameters surpassing the CT128 (all P < 0.0001) with substantial inter-rater agreement (κ ≥ 0.801). Despite adapted scan protocols the SDCT yielded lower values for CTDI vol (-10.1 ± 12.8%), DLP (-13.1 ± 13.9%), and DLP 68 (-15.3 ± 16.9%) than the CT128 (all P < 0.0001). Conclusion The SDCT scanner yielded better CT image quality compared to the CT128 and lower radiation dose parameters.
SU-E-T-362: Automatic Catheter Reconstruction of Flap Applicators in HDR Surface Brachytherapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buzurovic, I; Devlin, P; Hansen, J
2014-06-01
Purpose: Catheter reconstruction is crucial for the accurate delivery of radiation dose in HDR brachytherapy. The process becomes complicated and time-consuming for large superficial clinical targets with a complex topology. A novel method for the automatic catheter reconstruction of flap applicators is proposed in this study. Methods: We have developed a program package capable of image manipulation, using C++class libraries of The-Visualization-Toolkit(VTK) software system. The workflow for automatic catheter reconstruction is: a)an anchor point is placed in 3D or in the axial view of the first slice at the tip of the first, last and middle points for the curvedmore » surface; b)similar points are placed on the last slice of the image set; c)the surface detection algorithm automatically registers the points to the images and applies the surface reconstruction filter; d)then a structured grid surface is generated through the center of the treatment catheters placed at a distance of 5mm from the patient's skin. As a result, a mesh-style plane is generated with the reconstructed catheters placed 10mm apart. To demonstrate automatic catheter reconstruction, we used CT images of patients diagnosed with cutaneous T-cell-lymphoma and imaged with Freiburg-Flap-Applicators (Nucletron™-Elekta, Netherlands). The coordinates for each catheter were generated and compared to the control points selected during the manual reconstruction for 16catheters and 368control point Results: The variation of the catheter tip positions between the automatically and manually reconstructed catheters was 0.17mm(SD=0.23mm). The position difference between the manually selected catheter control points and the corresponding points obtained automatically was 0.17mm in the x-direction (SD=0.23mm), 0.13mm in the y-direction (SD=0.22mm), and 0.14mm in the z-direction (SD=0.24mm). Conclusion: This study shows the feasibility of the automatic catheter reconstruction of flap applicators with a high level of positioning accuracy. Implementation of this technique has potential to decrease the planning time and may improve overall quality in superficial brachytherapy.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gerhard, M.A.; Sommer, S.C.
1995-04-01
AUTOCASK (AUTOmatic Generation of 3-D CASK models) is a microcomputer-based system of computer programs and databases developed at the Lawrence Livermore National Laboratory (LLNL) for the structural analysis of shipping casks for radioactive material. Model specification is performed on the microcomputer, and the analyses are performed on an engineering workstation or mainframe computer. AUTOCASK is based on 80386/80486 compatible microcomputers. The system is composed of a series of menus, input programs, display programs, a mesh generation program, and archive programs. All data is entered through fill-in-the-blank input screens that contain descriptive data requests.
Automatic Generation of Supervisory Control System Software Using Graph Composition
NASA Astrophysics Data System (ADS)
Nakata, Hideo; Sano, Tatsuro; Kojima, Taizo; Seo, Kazuo; Uchida, Tomoyuki; Nakamura, Yasuaki
This paper describes the automatic generation of system descriptions for SCADA (Supervisory Control And Data Acquisition) systems. The proposed method produces various types of data and programs for SCADA systems from equipment definitions using conversion rules. At first, this method makes directed graphs, which represent connections between the equipment, from equipment definitions. System descriptions are generated using the conversion rules, by analyzing these directed graphs, and finding the groups of equipment that involve similar operations. This method can make the conversion rules multi levels by using the composition of graphs, and can reduce the number of rules. The developer can define and manage these rules efficiently.
Automatic generation of stop word lists for information retrieval and analysis
Rose, Stuart J
2013-01-08
Methods and systems for automatically generating lists of stop words for information retrieval and analysis. Generation of the stop words can include providing a corpus of documents and a plurality of keywords. From the corpus of documents, a term list of all terms is constructed and both a keyword adjacency frequency and a keyword frequency are determined. If a ratio of the keyword adjacency frequency to the keyword frequency for a particular term on the term list is less than a predetermined value, then that term is excluded from the term list. The resulting term list is truncated based on predetermined criteria to form a stop word list.
Algorithms for the automatic generation of 2-D structured multi-block grids
NASA Technical Reports Server (NTRS)
Schoenfeld, Thilo; Weinerfelt, Per; Jenssen, Carl B.
1995-01-01
Two different approaches to the fully automatic generation of structured multi-block grids in two dimensions are presented. The work aims to simplify the user interactivity necessary for the definition of a multiple block grid topology. The first approach is based on an advancing front method commonly used for the generation of unstructured grids. The original algorithm has been modified toward the generation of large quadrilateral elements. The second method is based on the divide-and-conquer paradigm with the global domain recursively partitioned into sub-domains. For either method each of the resulting blocks is then meshed using transfinite interpolation and elliptic smoothing. The applicability of these methods to practical problems is demonstrated for typical geometries of fluid dynamics.
Automated Sequence Generation Process and Software
NASA Technical Reports Server (NTRS)
Gladden, Roy
2007-01-01
"Automated sequence generation" (autogen) signifies both a process and software used to automatically generate sequences of commands to operate various spacecraft. The autogen software comprises the autogen script plus the Activity Plan Generator (APGEN) program. APGEN can be used for planning missions and command sequences.
Automated location detection of injection site for preclinical stereotactic neurosurgery procedure
NASA Astrophysics Data System (ADS)
Abbaszadeh, Shiva; Wu, Hemmings C. H.
2017-03-01
Currently, during stereotactic neurosurgery procedures, the manual task of locating the proper area for needle insertion or implantation of electrode/cannula/optic fiber can be time consuming. The requirement of the task is to quickly and accurately find the location for insertion. In this study we investigate an automated method to locate the entry point of region of interest. This method leverages a digital image capture system, pattern recognition, and motorized stages. Template matching of known anatomical identifiable regions is used to find regions of interest (e.g. Bregma) in rodents. For our initial study, we tackle the problem of automatically detecting the entry point.
Decomposing phenotype descriptions for the human skeletal phenome.
Groza, Tudor; Hunter, Jane; Zankl, Andreas
2013-01-01
Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. The intrinsic value and knowledge captured within such descriptions can only be expressed by taking advantage of their inner structure that implicitly combines qualities and anatomical entities. We present a meta-model (the Phenotype Fragment Ontology) and a processing pipeline that enable together the automatic decomposition and conceptualization of phenotype descriptions for the human skeletal phenome. We use this approach to showcase the usefulness of the generic concept of phenotype decomposition by performing an experimental study on all skeletal phenotype concepts defined in the Human Phenotype Ontology.
Segmentation of stereo terrain images
NASA Astrophysics Data System (ADS)
George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.
2000-06-01
We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.
Evolution of illustrations in anatomy: a study from the classical period in Europe to modern times.
Ghosh, Sanjib Kumar
2015-01-01
Illustrations constitute an essential element of learning anatomy in modern times. However it required a significant evolutionary process spread over centuries, for illustrations to achieve the present status in the subject of anatomy. This review article attempts to outline the evolutionary process by highlighting on the works of esteemed anatomists in a chronological manner. Available literature suggests that illustrations were not used in anatomy during the classical period when the subject was dominated by the descriptive text of Galen. Guido da Vigevano was first to use illustrations in anatomy during the Late Middle Ages and this concept developed further during the Renaissance period when Andreas Vesalius pioneered in illustrations becoming an indispensable tool in conveying anatomical details. Toward later stages of the Renaissance period, Fabricius ab Aquapendente endeavored to restrict dramatization of anatomical illustrations which was a prevalent trend in early Renaissance. During the 18th century, anatomical artwork was characterized by the individual styles of prominent anatomists leading to suppression of anatomical details. In the 19th century, Henry Gray used illustrations in his anatomical masterpiece that focused on depicting anatomical structures and were free from any artistic style. From early part of the 20th century medical images and photographs started to complement traditional handmade anatomical illustrations. Computer technology and advanced software systems played a key role in the evolution of anatomical illustrations during the late 20th century resulting in new generation 3D image datasets that are being used in the 21st century in innovative formats for teaching and learning anatomy. © 2014 American Association of Anatomists.
NASA Astrophysics Data System (ADS)
Buerger, C.; Lorenz, C.; Babic, D.; Hoppenbrouwers, J.; Homan, R.; Nachabe, R.; Racadio, J. M.; Grass, M.
2017-03-01
Spinal fusion is a common procedure to stabilize the spinal column by fixating parts of the spine. In such procedures, metal screws are inserted through the patients back into a vertebra, and the screws of adjacent vertebrae are connected by metal rods to generate a fixed bridge. In these procedures, 3D image guidance for intervention planning and outcome control is required. Here, for anatomical guidance, an automated approach for vertebra segmentation from C-arm CT images of the spine is introduced and evaluated. As a prerequisite, 3D C-arm CT images are acquired covering the vertebrae of interest. An automatic model-based segmentation approach is applied to delineate the outline of the vertebrae of interest. The segmentation approach is based on 24 partial models of the cervical, thoracic and lumbar vertebrae which aggregate information about (i) the basic shape itself, (ii) trained features for image based adaptation, and (iii) potential shape variations. Since the volume data sets generated by the C-arm system are limited to a certain region of the spine the target vertebra and hence initial model position is assigned interactively. The approach was trained and tested on 21 human cadaver scans. A 3-fold cross validation to ground truth annotations yields overall mean segmentation errors of 0.5 mm for T1 to 1.1 mm for C6. The results are promising and show potential to support the clinician in pedicle screw path and rod planning to allow accurate and reproducible insertions.
The guitar chord-generating algorithm based on complex network
NASA Astrophysics Data System (ADS)
Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais
2016-02-01
This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.
NASA Astrophysics Data System (ADS)
Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao
2018-02-01
Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.
Automated Guidance for Student Inquiry
ERIC Educational Resources Information Center
Gerard, Libby F.; Ryoo, Kihyun; McElhaney, Kevin W.; Liu, Ou Lydia; Rafferty, Anna N.; Linn, Marcia C.
2016-01-01
In 4 classroom experiments we investigated uses for technologies that automatically score student generated essays, concept diagrams, and drawings in inquiry curricula. We used the automatic scores to assign typical and research-based guidance and studied the impact of the guidance on student progress. Seven teachers and their 897 students…
Automatic, nondestructive test monitors in-process weld quality
NASA Technical Reports Server (NTRS)
Deal, F. C.
1968-01-01
Instrument automatically and nondestructively monitors the quality of welds produced in microresistance welding. It measures the infrared energy generated in the weld as the weld is made and compares this energy with maximum and minimum limits of infrared energy values previously correlated with acceptable weld-strength tolerances.
DOT National Transportation Integrated Search
2014-09-09
Automatic Dependent Surveillance-Broadcast (ADS-B) In technology supports the display of traffic data on Cockpit Displays of Traffic Information (CDTIs). The data are used by flightcrews to perform defined self-separation procedures, such as the in-t...
NASA Astrophysics Data System (ADS)
Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang
2018-05-01
Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.
Improved automatic optic nerve radius estimation from high resolution MRI
NASA Astrophysics Data System (ADS)
Harrigan, Robert L.; Smith, Alex K.; Mawn, Louise A.; Smith, Seth A.; Landman, Bennett A.
2017-02-01
The optic nerve (ON) is a vital structure in the human visual system and transports all visual information from the retina to the cortex for higher order processing. Due to the lack of redundancy in the visual pathway, measures of ON damage have been shown to correlate well with visual deficits. These measures are typically taken at an arbitrary anatomically defined point along the nerve and do not characterize changes along the length of the ON. We propose a fully automated, three-dimensionally consistent technique building upon a previous independent slice-wise technique to estimate the radius of the ON and surrounding cerebrospinal fluid (CSF) on high-resolution heavily T2-weighted isotropic MRI. We show that by constraining results to be three-dimensionally consistent this technique produces more anatomically viable results. We compare this technique with the previously published slice-wise technique using a short-term reproducibility data set, 10 subjects, follow-up <1 month, and show that the new method is more reproducible in the center of the ON. The center of the ON contains the most accurate imaging because it lacks confounders such as motion and frontal lobe interference. Long-term reproducibility, 5 subjects, follow-up of approximately 11 months, is also investigated with this new technique and shown to be similar to short-term reproducibility, indicating that the ON does not change substantially within 11 months. The increased accuracy of this new technique provides increased power when searching for anatomical changes in ON size amongst patient populations.
Improved Automatic Optic Nerve Radius Estimation from High Resolution MRI.
Harrigan, Robert L; Smith, Alex K; Mawn, Louise A; Smith, Seth A; Landman, Bennett A
2017-02-11
The optic nerve (ON) is a vital structure in the human visual system and transports all visual information from the retina to the cortex for higher order processing. Due to the lack of redundancy in the visual pathway, measures of ON damage have been shown to correlate well with visual deficits. These measures are typically taken at an arbitrary anatomically defined point along the nerve and do not characterize changes along the length of the ON. We propose a fully automated, three-dimensionally consistent technique building upon a previous independent slice-wise technique to estimate the radius of the ON and surrounding cerebrospinal fluid (CSF) on high-resolution heavily T2-weighted isotropic MRI. We show that by constraining results to be three-dimensionally consistent this technique produces more anatomically viable results. We compare this technique with the previously published slice-wise technique using a short-term reproducibility data set, 10 subjects, follow-up <1 month, and show that the new method is more reproducible in the center of the ON. The center of the ON contains the most accurate imaging because it lacks confounders such as motion and frontal lobe interference. Long-term reproducibility, 5 subjects, follow-up of approximately 11 months, is also investigated with this new technique and shown to be similar to short-term reproducibility, indicating that the ON does not change substantially within 11 months. The increased accuracy of this new technique provides increased power when searching for anatomical changes in ON size amongst patient populations.
Validation of hand and foot anatomical feature measurements from smartphone images
NASA Astrophysics Data System (ADS)
Amini, Mohammad; Vasefi, Fartash; MacKinnon, Nicholas
2018-02-01
A smartphone mobile medical application, previously presented as a tool for individuals with hand arthritis to assess and monitor the progress of their disease, has been modified and expanded to include extraction of anatomical features from the hand (joint/finger width, and angulation) and foot (length, width, big toe angle, and arch height index) from smartphone camera images. Image processing algorithms and automated measurements were validated by performing tests on digital hand models, rigid plastic hand models, and real human hands and feet to determine accuracy and reproducibility compared to conventional measurement tools such as calipers, rulers, and goniometers. The mobile application was able to provide finger joint width measurements with accuracy better than 0.34 (+/-0.25) millimeters. Joint angulation measurement accuracy was better than 0.50 (+/-0.45) degrees. The automatically calculated foot length accuracy was 1.20 (+/-1.27) millimeters and the foot width accuracy was 1.93 (+/-1.92) millimeters. Hallux valgus angle (used in assessing bunions) accuracy was 1.30 (+/-1.29) degrees. Arch height index (AHI) measurements had an accuracy of 0.02 (+/-0.01). Combined with in-app documentation of symptoms, treatment, and lifestyle factors, the anatomical feature measurements can be used by both healthcare professionals and manufacturers. Applications include: diagnosing hand osteoarthritis; providing custom finger splint measurements; providing compression glove measurements for burn and lymphedema patients; determining foot dimensions for custom shoe sizing, insoles, orthotics, or foot splints; and assessing arch height index and bunion treatment effectiveness.
Reproducibility Between Brain Uptake Ratio Using Anatomic Standardization and Patlak-Plot Methods.
Shibutani, Takayuki; Onoguchi, Masahisa; Noguchi, Atsushi; Yamada, Tomoki; Tsuchihashi, Hiroko; Nakajima, Tadashi; Kinuya, Seigo
2015-12-01
The Patlak-plot and conventional methods of determining brain uptake ratio (BUR) have some problems with reproducibility. We formulated a method of determining BUR using anatomic standardization (BUR-AS) in a statistical parametric mapping algorithm to improve reproducibility. The objective of this study was to demonstrate the inter- and intraoperator reproducibility of mean cerebral blood flow as determined using BUR-AS in comparison to the conventional-BUR (BUR-C) and Patlak-plot methods. The images of 30 patients who underwent brain perfusion SPECT were retrospectively used in this study. The images were reconstructed using ordered-subset expectation maximization and processed using an automatic quantitative analysis for cerebral blood flow of ECD tool. The mean SPECT count was calculated from axial basal ganglia slices of the normal side (slices 31-40) drawn using a 3-dimensional stereotactic region-of-interest template after anatomic standardization. The mean cerebral blood flow was calculated from the mean SPECT count. Reproducibility was evaluated using coefficient of variation and Bland-Altman plotting. For both inter- and intraoperator reproducibility, the BUR-AS method had the lowest coefficient of variation and smallest error range about the Bland-Altman plot. Mean CBF obtained using the BUR-AS method had the highest reproducibility. Compared with the Patlak-plot and BUR-C methods, the BUR-AS method provides greater inter- and intraoperator reproducibility of cerebral blood flow measurement. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vásquez Osorio, Eliana M., E-mail: e.vasquezosorio@erasmusmc.nl; Kolkman-Deurloo, Inger-Karine K.; Schuring-Pereira, Monica
Purpose: In the treatment of cervical cancer, large anatomical deformations, caused by, e.g., tumor shrinkage, bladder and rectum filling changes, organ sliding, and the presence of the brachytherapy (BT) applicator, prohibit the accumulation of external beam radiotherapy (EBRT) and BT dose distributions. This work proposes a structure-wise registration with vector field integration (SW+VF) to map the largely deformed anatomies between EBRT and BT, paving the way for 3D dose accumulation between EBRT and BT. Methods: T2w-MRIs acquired before EBRT and as a part of the MRI-guided BT procedure for 12 cervical cancer patients, along with the manual delineations of themore » bladder, cervix-uterus, and rectum-sigmoid, were used for this study. A rigid transformation was used to align the bony anatomy in the MRIs. The proposed SW+VF method starts by automatically segmenting features in the area surrounding the delineated organs. Then, each organ and feature pair is registered independently using a feature-based nonrigid registration algorithm developed in-house. Additionally, a background transformation is calculated to account for areas far from all organs and features. In order to obtain one transformation that can be used for dose accumulation, the organ-based, feature-based, and the background transformations are combined into one vector field using a weighted sum, where the contribution of each transformation can be directly controlled by its extent of influence (scope size). The optimal scope sizes for organ-based and feature-based transformations were found by an exhaustive analysis. The anatomical correctness of the mapping was independently validated by measuring the residual distances after transformation for delineated structures inside the cervix-uterus (inner anatomical correctness), and for anatomical landmarks outside the organs in the surrounding region (outer anatomical correctness). The results of the proposed method were compared with the results of the rigid transformation and nonrigid registration of all structures together (AST). Results: The rigid transformation achieved a good global alignment (mean outer anatomical correctness of 4.3 mm) but failed to align the deformed organs (mean inner anatomical correctness of 22.4 mm). Conversely, the AST registration produced a reasonable alignment for the organs (6.3 mm) but not for the surrounding region (16.9 mm). SW+VF registration achieved the best results for both regions (3.5 and 3.4 mm for the inner and outer anatomical correctness, respectively). All differences were significant (p < 0.02, Wilcoxon rank sum test). Additionally, optimization of the scope sizes determined that the method was robust for a large range of scope size values. Conclusions: The novel SW+VF method improved the mapping of large and complex deformations observed between EBRT and BT for cervical cancer patients. Future studies that quantify the mapping error in terms of dose errors are required to test the clinical applicability of dose accumulation by the SW+VF method.« less
LEE, Joo-Young; PARK, Joonhee; PARK, Huiju; COCA, Aitor; KIM, Jung-Hyun; TAYLOR, Nigel A.S.; SON, Su-Young; TOCHIHARA, Yutaka
2015-01-01
The purpose of this study was to investigate smart features required for the next generation of personal protective equipment (PPE) for firefighters in Australia, Korea, Japan, and the USA. Questionnaire responses were obtained from 167 Australian, 351 Japanese, 413 Korean, and 763 U.S. firefighters (1,611 males and 61 females). Preferences concerning smart features varied among countries, with 27% of Korean and 30% of U.S. firefighters identifying ‘a location monitoring system’ as the most important element. On the other hand, 43% of Japanese firefighters preferred ‘an automatic body cooling system’ while 21% of the Australian firefighters selected equally ‘an automatic body cooling system’ and ‘a wireless communication system’. When asked to rank these elements in descending priority, responses across these countries were very similar with the following items ranked highest: ‘a location monitoring system’, ‘an automatic body cooling system’, ‘a wireless communication system’, and ‘a vision support system’. The least preferred elements were ‘an automatic body warming system’ and ‘a voice recording system’. No preferential relationship was apparent for age, work experience, gender or anthropometric characteristics. These results have implications for the development of the next generation of PPE along with the international standardisation of the smart PPE. PMID:26027710
NASA Astrophysics Data System (ADS)
Grova, C.; Jannin, P.; Biraben, A.; Buvat, I.; Benali, H.; Bernard, A. M.; Scarabin, J. M.; Gibaud, B.
2003-12-01
Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.
Generating Customized Verifiers for Automatically Generated Code
NASA Technical Reports Server (NTRS)
Denney, Ewen; Fischer, Bernd
2008-01-01
Program verification using Hoare-style techniques requires many logical annotations. We have previously developed a generic annotation inference algorithm that weaves in all annotations required to certify safety properties for automatically generated code. It uses patterns to capture generator- and property-specific code idioms and property-specific meta-program fragments to construct the annotations. The algorithm is customized by specifying the code patterns and integrating them with the meta-program fragments for annotation construction. However, this is difficult since it involves tedious and error-prone low-level term manipulations. Here, we describe an annotation schema compiler that largely automates this customization task using generative techniques. It takes a collection of high-level declarative annotation schemas tailored towards a specific code generator and safety property, and generates all customized analysis functions and glue code required for interfacing with the generic algorithm core, thus effectively creating a customized annotation inference algorithm. The compiler raises the level of abstraction and simplifies schema development and maintenance. It also takes care of some more routine aspects of formulating patterns and schemas, in particular handling of irrelevant program fragments and irrelevant variance in the program structure, which reduces the size, complexity, and number of different patterns and annotation schemas that are required. The improvements described here make it easier and faster to customize the system to a new safety property or a new generator, and we demonstrate this by customizing it to certify frame safety of space flight navigation code that was automatically generated from Simulink models by MathWorks' Real-Time Workshop.
Automatic assessment of the quality of patient positioning in mammography
NASA Astrophysics Data System (ADS)
Bülow, Thomas; Meetz, Kirsten; Kutra, Dominik; Netsch, Thomas; Wiemker, Rafael; Bergtholdt, Martin; Sabczynski, Jörg; Wieberneit, Nataly; Freund, Manuela; Schulze-Wenck, Ingrid
2013-02-01
Quality assurance has been recognized as crucial for the success of population-based breast cancer screening programs using x-ray mammography. Quality guidelines and criteria have been defined in the US as well as the European Union in order to ensure the quality of breast cancer screening. Taplin et al. report that incorrect positioning of the breast is the major image quality issue in screening mammography. Consequently, guidelines and criteria for correct positioning and for the assessment of the positioning quality in mammograms play an important role in the quality standards. In this paper we present a system for the automatic evaluation of positioning quality in mammography according to the existing standardized criteria. This involves the automatic detection of anatomic landmarks in medio- lateral oblique (MLO) and cranio-caudal (CC) mammograms, namely the pectoral muscle, the mammilla and the infra-mammary fold. Furthermore, the detected landmarks are assessed with respect to their proper presentation in the image. Finally, the geometric relations between the detected landmarks are investigated to assess the positioning quality. This includes the evaluation whether the pectoral muscle is imaged down to the mammilla level, and whether the posterior nipple line diameter of the breast is consistent between the different views (MLO and CC) of the same breast. Results of the computerized assessment are compared to ground truth collected from two expert readers.
iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization.
Blenkmann, Alejandro O; Phillips, Holly N; Princich, Juan P; Rowe, James B; Bekinschtein, Tristan A; Muravchik, Carlos H; Kochen, Silvia
2017-01-01
The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2-3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.
Kim, Sung-Chul; Lee, Hae-Kag; Lee, Yang-Sub; Cho, Jae-Hwan
2015-01-01
We found a way to optimize the image quality and reduce the exposure dose of patients through the proper activity combination of the automatic exposure control system chamber for the dose optimization when examining the pelvic anteroposterior side using the phantom of the human body standard model. We set 7 combinations of the chamber of automatic exposure control system. The effective dose was yielded by measuring five times for each according to the activity combination of the chamber for the dose measurement. Five radiologists with more than five years of experience evaluated the image through picture archiving and communication system using double blind test while classifying the 6 anatomical sites into 3-point level (improper, proper, perfect). When only one central chamber was activated, the effective dose was found to be the highest level, 0.287 mSv; and lowest when only the top left chamber was used, 0.165 mSv. After the subjective evaluation by five panel members on the pelvic image was completed, there was no statistically meaningful difference between the 7 chamber combinations, and all had good image quality. When testing the pelvic anteroposterior side with digital radiography, we were able to reduce the exposure dose of patients using the combination of the top right side of or the top two of the chamber.
Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos
2014-01-01
Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866
iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization
Blenkmann, Alejandro O.; Phillips, Holly N.; Princich, Juan P.; Rowe, James B.; Bekinschtein, Tristan A.; Muravchik, Carlos H.; Kochen, Silvia
2017-01-01
The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions. PMID:28303098
A Simple and Automatic Method for Locating Surgical Guide Hole
NASA Astrophysics Data System (ADS)
Li, Xun; Chen, Ming; Tang, Kai
2017-12-01
Restoration-driven surgical guides are widely used in implant surgery. This study aims to provide a simple and valid method of automatically locating surgical guide hole, which can reduce operator's experiences and improve the design efficiency and quality of surgical guide. Few literatures can be found on this topic and the paper proposed a novel and simple method to solve this problem. In this paper, a local coordinate system for each objective tooth is geometrically constructed in CAD system. This coordinate system well represents dental anatomical features and the center axis of the objective tooth (coincide with the corresponding guide hole axis) can be quickly evaluated in this coordinate system, finishing the location of the guide hole. The proposed method has been verified by comparing two types of benchmarks: manual operation by one skilled doctor with over 15-year experiences (used in most hospitals) and automatic way using one popular commercial package Simplant (used in few hospitals).Both the benchmarks and the proposed method are analyzed in their stress distribution when chewing and biting. The stress distribution is visually shown and plotted as a graph. The results show that the proposed method has much better stress distribution than the manual operation and slightly better than Simplant, which will significantly reduce the risk of cervical margin collapse and extend the wear life of the restoration.
Automatic measurement of prosody in behavioral variant FTD.
Nevler, Naomi; Ash, Sharon; Jester, Charles; Irwin, David J; Liberman, Mark; Grossman, Murray
2017-08-15
To help understand speech changes in behavioral variant frontotemporal dementia (bvFTD), we developed and implemented automatic methods of speech analysis for quantification of prosody, and evaluated clinical and anatomical correlations. We analyzed semi-structured, digitized speech samples from 32 patients with bvFTD (21 male, mean age 63 ± 8.5, mean disease duration 4 ± 3.1 years) and 17 matched healthy controls (HC). We automatically extracted fundamental frequency (f0, the physical property of sound most closely correlating with perceived pitch) and computed pitch range on a logarithmic scale (semitone) that controls for individual and sex differences. We correlated f0 range with neuropsychiatric tests, and related f0 range to gray matter (GM) atrophy using 3T T1 MRI. We found significantly reduced f0 range in patients with bvFTD (mean 4.3 ± 1.8 ST) compared to HC (5.8 ± 2.1 ST; p = 0.03). Regression related reduced f0 range in bvFTD to GM atrophy in bilateral inferior and dorsomedial frontal as well as left anterior cingulate and anterior insular regions. Reduced f0 range reflects impaired prosody in bvFTD. This is associated with neuroanatomic networks implicated in language production and social disorders centered in the frontal lobe. These findings support the feasibility of automated speech analysis in frontotemporal dementia and other disorders. © 2017 American Academy of Neurology.
Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras.
Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki
2016-06-24
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system.
Normalized Metadata Generation for Human Retrieval Using Multiple Video Surveillance Cameras
Jung, Jaehoon; Yoon, Inhye; Lee, Seungwon; Paik, Joonki
2016-01-01
Since it is impossible for surveillance personnel to keep monitoring videos from a multiple camera-based surveillance system, an efficient technique is needed to help recognize important situations by retrieving the metadata of an object-of-interest. In a multiple camera-based surveillance system, an object detected in a camera has a different shape in another camera, which is a critical issue of wide-range, real-time surveillance systems. In order to address the problem, this paper presents an object retrieval method by extracting the normalized metadata of an object-of-interest from multiple, heterogeneous cameras. The proposed metadata generation algorithm consists of three steps: (i) generation of a three-dimensional (3D) human model; (ii) human object-based automatic scene calibration; and (iii) metadata generation. More specifically, an appropriately-generated 3D human model provides the foot-to-head direction information that is used as the input of the automatic calibration of each camera. The normalized object information is used to retrieve an object-of-interest in a wide-range, multiple-camera surveillance system in the form of metadata. Experimental results show that the 3D human model matches the ground truth, and automatic calibration-based normalization of metadata enables a successful retrieval and tracking of a human object in the multiple-camera video surveillance system. PMID:27347961
NASA Astrophysics Data System (ADS)
Winkel, D.; Bol, G. H.; van Asselen, B.; Hes, J.; Scholten, V.; Kerkmeijer, L. G. W.; Raaymakers, B. W.
2016-12-01
To develop an automated radiotherapy treatment planning and optimization workflow to efficiently create patient specifically optimized clinical grade treatment plans for prostate cancer and to implement it in clinical practice. A two-phased planning and optimization workflow was developed to automatically generate 77Gy 5-field simultaneously integrated boost intensity modulated radiation therapy (SIB-IMRT) plans for prostate cancer treatment. A retrospective planning study (n = 100) was performed in which automatically and manually generated treatment plans were compared. A clinical pilot (n = 21) was performed to investigate the usability of our method. Operator time for the planning process was reduced to <5 min. The retrospective planning study showed that 98 plans met all clinical constraints. Significant improvements were made in the volume receiving 72Gy (V72Gy) for the bladder and rectum and the mean dose of the bladder and the body. A reduced plan variance was observed. During the clinical pilot 20 automatically generated plans met all constraints and 17 plans were selected for treatment. The automated radiotherapy treatment planning and optimization workflow is capable of efficiently generating patient specifically optimized and improved clinical grade plans. It has now been adopted as the current standard workflow in our clinic to generate treatment plans for prostate cancer.
Automatic digital surface model (DSM) generation from aerial imagery data
NASA Astrophysics Data System (ADS)
Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu
2018-04-01
Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.
Automatic Association of News Items.
ERIC Educational Resources Information Center
Carrick, Christina; Watters, Carolyn
1997-01-01
Discussion of electronic news delivery systems and the automatic generation of electronic editions focuses on the association of related items of different media type, specifically photos and stories. The goal is to be able to determine to what degree any two news items refer to the same news event. (Author/LRW)
Automatic Diagnosis of Fetal Heart Rate: Comparison of Different Methodological Approaches
2001-10-25
Apgar score). Each recording lasted at least 30 minutes and it contained both the cardiographic series and the toco trace. We focused on four...inference rules automatically generated by the learning procedure showed that n° Rules can be manually reduced to 37 without deteriorating so much the
On May 17, 2017, EPA and the California Air Resources Board (CARB) approved an emissions modification proposed by Volkswagen that will reduce NOx emissions from automatic transmission diesel Passats for model years 2012-2014.
Evaluating the Psychometric Characteristics of Generated Multiple-Choice Test Items
ERIC Educational Resources Information Center
Gierl, Mark J.; Lai, Hollis; Pugh, Debra; Touchie, Claire; Boulais, André-Philippe; De Champlain, André
2016-01-01
Item development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational testing situations. As a result, the psychometric…
Multimodal system for the planning and guidance of bronchoscopy
NASA Astrophysics Data System (ADS)
Higgins, William E.; Cheirsilp, Ronnarit; Zang, Xiaonan; Byrnes, Patrick
2015-03-01
Many technical innovations in multimodal radiologic imaging and bronchoscopy have emerged recently in the effort against lung cancer. Modern X-ray computed-tomography (CT) scanners provide three-dimensional (3D) high-resolution chest images, positron emission tomography (PET) scanners give complementary molecular imaging data, and new integrated PET/CT scanners combine the strengths of both modalities. State-of-the-art bronchoscopes permit minimally invasive tissue sampling, with vivid endobronchial video enabling navigation deep into the airway-tree periphery, while complementary endobronchial ultrasound (EBUS) reveals local views of anatomical structures outside the airways. In addition, image-guided intervention (IGI) systems have proven their utility for CT-based planning and guidance of bronchoscopy. Unfortunately, no IGI system exists that integrates all sources effectively through the complete lung-cancer staging work flow. This paper presents a prototype of a computer-based multimodal IGI system that strives to fill this need. The system combines a wide range of automatic and semi-automatic image-processing tools for multimodal data fusion and procedure planning. It also provides a flexible graphical user interface for follow-on guidance of bronchoscopy/EBUS. Human-study results demonstrate the system's potential.
Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis
Muralidharan, Prasanna; Fishbaugh, James; Kim, Eun Young; Johnson, Hans J.; Paulsen, Jane S.; Gerig, Guido; Fletcher, P. Thomas
2016-01-01
The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Bayesian mixed-effects shape model that incorporates simultaneous relationships between longitudinal shape data and multiple predictors or covariates to the model. Moreover, we place an Automatic Relevance Determination (ARD) prior on the parameters, that lets us automatically select which covariates are most relevant to the model based on observed data. We evaluate our proposed model and inference procedure on a longitudinal study of Huntington's disease from PREDICT-HD. We first show the utility of the ARD prior for model selection in a univariate modeling of striatal volume, and next we apply the full high-dimensional longitudinal shape model to putamen shapes. PMID:28090246
A method for automatic feature points extraction of human vertebrae three-dimensional model
NASA Astrophysics Data System (ADS)
Wu, Zhen; Wu, Junsheng
2017-05-01
A method for automatic extraction of the feature points of the human vertebrae three-dimensional model is presented. Firstly, the statistical model of vertebrae feature points is established based on the results of manual vertebrae feature points extraction. Then anatomical axial analysis of the vertebrae model is performed according to the physiological and morphological characteristics of the vertebrae. Using the axial information obtained from the analysis, a projection relationship between the statistical model and the vertebrae model to be extracted is established. According to the projection relationship, the statistical model is matched with the vertebrae model to get the estimated position of the feature point. Finally, by analyzing the curvature in the spherical neighborhood with the estimated position of feature points, the final position of the feature points is obtained. According to the benchmark result on multiple test models, the mean relative errors of feature point positions are less than 5.98%. At more than half of the positions, the error rate is less than 3% and the minimum mean relative error is 0.19%, which verifies the effectiveness of the method.
NASA Astrophysics Data System (ADS)
Patel, Ajay; van de Leemput, Sil C.; Prokop, Mathias; van Ginneken, Bram; Manniesing, Rashindra
2017-03-01
Segmentation of anatomical structures is fundamental in the development of computer aided diagnosis systems for cerebral pathologies. Manual annotations are laborious, time consuming and subject to human error and observer variability. Accurate quantification of cerebrospinal fluid (CSF) can be employed as a morphometric measure for diagnosis and patient outcome prediction. However, segmenting CSF in non-contrast CT images is complicated by low soft tissue contrast and image noise. In this paper we propose a state-of-the-art method using a multi-scale three-dimensional (3D) fully convolutional neural network (CNN) to automatically segment all CSF within the cranial cavity. The method is trained on a small dataset comprised of four manually annotated cerebral CT images. Quantitative evaluation of a separate test dataset of four images shows a mean Dice similarity coefficient of 0.87 +/- 0.01 and mean absolute volume difference of 4.77 +/- 2.70 %. The average prediction time was 68 seconds. Our method allows for fast and fully automated 3D segmentation of cerebral CSF in non-contrast CT, and shows promising results despite a limited amount of training data.
AIRSAR Web-Based Data Processing
NASA Technical Reports Server (NTRS)
Chu, Anhua; Van Zyl, Jakob; Kim, Yunjin; Hensley, Scott; Lou, Yunling; Madsen, Soren; Chapman, Bruce; Imel, David; Durden, Stephen; Tung, Wayne
2007-01-01
The AIRSAR automated, Web-based data processing and distribution system is an integrated, end-to-end synthetic aperture radar (SAR) processing system. Designed to function under limited resources and rigorous demands, AIRSAR eliminates operational errors and provides for paperless archiving. Also, it provides a yearly tune-up of the processor on flight missions, as well as quality assurance with new radar modes and anomalous data compensation. The software fully integrates a Web-based SAR data-user request subsystem, a data processing system to automatically generate co-registered multi-frequency images from both polarimetric and interferometric data collection modes in 80/40/20 MHz bandwidth, an automated verification quality assurance subsystem, and an automatic data distribution system for use in the remote-sensor community. Features include Survey Automation Processing in which the software can automatically generate a quick-look image from an entire 90-GB SAR raw data 32-MB/s tape overnight without operator intervention. Also, the software allows product ordering and distribution via a Web-based user request system. To make AIRSAR more user friendly, it has been designed to let users search by entering the desired mission flight line (Missions Searching), or to search for any mission flight line by entering the desired latitude and longitude (Map Searching). For precision image automation processing, the software generates the products according to each data processing request stored in the database via a Queue management system. Users are able to have automatic generation of coregistered multi-frequency images as the software generates polarimetric and/or interferometric SAR data processing in ground and/or slant projection according to user processing requests for one of the 12 radar modes.
Towards automatic planning for manufacturing generative processes
DOE Office of Scientific and Technical Information (OSTI.GOV)
CALTON,TERRI L.
2000-05-24
Generative process planning describes methods process engineers use to modify manufacturing/process plans after designs are complete. A completed design may be the result from the introduction of a new product based on an old design, an assembly upgrade, or modified product designs used for a family of similar products. An engineer designs an assembly and then creates plans capturing manufacturing processes, including assembly sequences, component joining methods, part costs, labor costs, etc. When new products originate as a result of an upgrade, component geometry may change, and/or additional components and subassemblies may be added to or are omitted from themore » original design. As a result process engineers are forced to create new plans. This is further complicated by the fact that the process engineer is forced to manually generate these plans for each product upgrade. To generate new assembly plans for product upgrades, engineers must manually re-specify the manufacturing plan selection criteria and re-run the planners. To remedy this problem, special-purpose assembly planning algorithms have been developed to automatically recognize design modifications and automatically apply previously defined manufacturing plan selection criteria and constraints.« less
Fuel cell generator energy dissipator
Veyo, Stephen Emery; Dederer, Jeffrey Todd; Gordon, John Thomas; Shockling, Larry Anthony
2000-01-01
An apparatus and method are disclosed for eliminating the chemical energy of fuel remaining in a fuel cell generator when the electrical power output of the fuel cell generator is terminated. During a generator shut down condition, electrically resistive elements are automatically connected across the fuel cell generator terminals in order to draw current, thereby depleting the fuel
Steam generator on-line efficiency monitor
DOE Office of Scientific and Technical Information (OSTI.GOV)
Johnson, R.K.; Kaya, A.; Keyes, M.A. IV
1987-08-04
This patent describes a system for automatically and continuously determining the efficiency of a combustion process in a fossil-fuel fired vapor generator for utilization by an automatic load control system that controls the distribution of a system load among a plurality of vapor generators, comprising: a first function generator, connected to an oxygen transducer for sensing the level of excess air in the flue gas, for generating a first signal indicative of the total air supplied for combustion in percent by weight; a second function generator, connected to a combustibles transducer for sensing the level of combustibles in the fluemore » gas, for generating a second signal indicative of the percent combustibles present in the flue gas; means for correcting the first signal, connected to the first and second function generators, when the oxygen transducer is of a type that operates at a temperature level sufficient to cause the unburned combustibles to react with the oxygen present in the flue gas; an ambient air temperature transducer for generating a third signal indicative of the temperature of the ambient air supplied to the vapor generator for combustion.« less
Model Checking Abstract PLEXIL Programs with SMART
NASA Technical Reports Server (NTRS)
Siminiceanu, Radu I.
2007-01-01
We describe a method to automatically generate discrete-state models of abstract Plan Execution Interchange Language (PLEXIL) programs that can be analyzed using model checking tools. Starting from a high-level description of a PLEXIL program or a family of programs with common characteristics, the generator lays the framework that models the principles of program execution. The concrete parts of the program are not automatically generated, but require the modeler to introduce them by hand. As a case study, we generate models to verify properties of the PLEXIL macro constructs that are introduced as shorthand notation. After an exhaustive analysis, we conclude that the macro definitions obey the intended semantics and behave as expected, but contingently on a few specific requirements on the timing semantics of micro-steps in the concrete executive implementation.
2005-09-01
discovery of network security threats and vulnerabilities will be done by doing penetration testing during the C&A process. This can be done on a...2.1.1; Appendix E, J COBR -1 Protection of Backup and Restoration Assets Availability 1.3.1; 2.1.3; 2.1.7; 3.1; 4.3; Appendix J, M CODB-2 Data... discovery , inventory, scanning and loading of C&A information in its central database, (2) automatic generation of the SRTM , (3) automatic generation
NASA Technical Reports Server (NTRS)
Poole, L. R.; Lecroy, S. R.; Morris, W. D.
1977-01-01
A computer program for studying linear ocean wave refraction is described. The program features random-access modular bathymetry data storage. Three bottom topography approximation techniques are available in the program which provide varying degrees of bathymetry data smoothing. Refraction diagrams are generated automatically and can be displayed graphically in three forms: Ray patterns with specified uniform deepwater ray density, ray patterns with controlled nearshore ray density, or crest patterns constructed by using a cubic polynomial to approximate crest segments between adjacent rays.
NASA Astrophysics Data System (ADS)
Nakano, Masaru; Kubota, Fumiko; Inamori, Yutaka; Mitsuyuki, Keiji
Manufacturing system designers should concentrate on designing and planning manufacturing systems instead of spending their efforts on creating the simulation models to verify the design. This paper proposes a method and its tool to navigate the designers through the engineering process and generate the simulation model automatically from the design results. The design agent also supports collaborative design projects among different companies or divisions with distributed engineering and distributed simulation techniques. The idea was implemented and applied to a factory planning process.
An engineering approach to automatic programming
NASA Technical Reports Server (NTRS)
Rubin, Stuart H.
1990-01-01
An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format.
Parallel scheduling of recursively defined arrays
NASA Technical Reports Server (NTRS)
Myers, T. J.; Gokhale, M. B.
1986-01-01
A new method of automatic generation of concurrent programs which constructs arrays defined by sets of recursive equations is described. It is assumed that the time of computation of an array element is a linear combination of its indices, and integer programming is used to seek a succession of hyperplanes along which array elements can be computed concurrently. The method can be used to schedule equations involving variable length dependency vectors and mutually recursive arrays. Portions of the work reported here have been implemented in the PS automatic program generation system.
Chae, Kum Ju; Goo, Jin Mo; Ahn, Su Yeon; Yoo, Jin Young; Yoon, Soon Ho
2018-01-01
To evaluate the preference of observers for image quality of chest radiography using the deconvolution algorithm of point spread function (PSF) (TRUVIEW ART algorithm, DRTECH Corp.) compared with that of original chest radiography for visualization of anatomic regions of the chest. Prospectively enrolled 50 pairs of posteroanterior chest radiographs collected with standard protocol and with additional TRUVIEW ART algorithm were compared by four chest radiologists. This algorithm corrects scattered signals generated by a scintillator. Readers independently evaluated the visibility of 10 anatomical regions and overall image quality with a 5-point scale of preference. The significance of the differences in reader's preference was tested with a Wilcoxon's signed rank test. All four readers preferred the images applied with the algorithm to those without algorithm for all 10 anatomical regions (mean, 3.6; range, 3.2-4.0; p < 0.001) and for the overall image quality (mean, 3.8; range, 3.3-4.0; p < 0.001). The most preferred anatomical regions were the azygoesophageal recess, thoracic spine, and unobscured lung. The visibility of chest anatomical structures applied with the deconvolution algorithm of PSF was superior to the original chest radiography.
Betts, Aislinn M; McGoldrick, Matthew T; Dethlefs, Christopher R; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W M
2017-04-25
Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.
Using CASE tools to write engineering specifications
NASA Astrophysics Data System (ADS)
Henry, James E.; Howard, Robert W.; Iveland, Scott T.
1993-08-01
There are always a wide variety of obstacles to writing and maintaining engineering documentation. To combat these problems, documentation generation can be linked to the process of engineering development. The same graphics and communication tools used for structured system analysis and design (SSA/SSD) also form the basis for the documentation. The goal is to build a living document, such that as an engineering design changes, the documentation will `automatically' revise. `Automatic' is qualified by the need to maintain textual descriptions associated with the SSA/SSD graphics, and the need to generate new documents. This paper describes a methodology and a computer aided system engineering toolset that enables a relatively seamless transition into document generation for the development engineering team.
Automatic generation of randomized trial sequences for priming experiments.
Ihrke, Matthias; Behrendt, Jörg
2011-01-01
In most psychological experiments, a randomized presentation of successive displays is crucial for the validity of the results. For some paradigms, this is not a trivial issue because trials are interdependent, e.g., priming paradigms. We present a software that automatically generates optimized trial sequences for (negative-) priming experiments. Our implementation is based on an optimization heuristic known as genetic algorithms that allows for an intuitive interpretation due to its similarity to natural evolution. The program features a graphical user interface that allows the user to generate trial sequences and to interactively improve them. The software is based on freely available software and is released under the GNU General Public License.
Unraveling the Tangled Skein: The Evolution of Transcriptional Regulatory Networks in Development.
Rebeiz, Mark; Patel, Nipam H; Hinman, Veronica F
2015-01-01
The molecular and genetic basis for the evolution of anatomical diversity is a major question that has inspired evolutionary and developmental biologists for decades. Because morphology takes form during development, a true comprehension of how anatomical structures evolve requires an understanding of the evolutionary events that alter developmental genetic programs. Vast gene regulatory networks (GRNs) that connect transcription factors to their target regulatory sequences control gene expression in time and space and therefore determine the tissue-specific genetic programs that shape morphological structures. In recent years, many new examples have greatly advanced our understanding of the genetic alterations that modify GRNs to generate newly evolved morphologies. Here, we review several aspects of GRN evolution, including their deep preservation, their mechanisms of alteration, and how they originate to generate novel developmental programs.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dowling, Jason A., E-mail: jason.dowling@csiro.au; University of Newcastle, Callaghan, New South Wales; Sun, Jidi
Purpose: To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. Patients and Methods: A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1wmore » flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. Results: The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). Conclusions: The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.« less
Semantic representation of reported measurements in radiology.
Oberkampf, Heiner; Zillner, Sonja; Overton, James A; Bauer, Bernhard; Cavallaro, Alexander; Uder, Michael; Hammon, Matthias
2016-01-22
In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-text data consists of reports covering the assessment of changes in tumor burden, which are needed for the evaluation of cancer treatment success. Any change of lesion size is a critical factor in follow-up examinations. It is difficult to retrieve specific information from unstructured reports and to compare them over time. Therefore, a prototype was implemented that demonstrates the structured representation of findings, allowing selective review in consecutive examinations and thus more efficient comparison over time. We developed a semantic Model for Clinical Information (MCI) based on existing ontologies from the Open Biological and Biomedical Ontologies (OBO) library. MCI is used for the integrated representation of measured image findings and medical knowledge about the normal size of anatomical entities. An integrated view of the radiology findings is realized by a prototype implementation of a ReportViewer. Further, RECIST (Response Evaluation Criteria In Solid Tumors) guidelines are implemented by SPARQL queries on MCI. The evaluation is based on two data sets of German radiology reports: An oncologic data set consisting of 2584 reports on 377 lymphoma patients and a mixed data set consisting of 6007 reports on diverse medical and surgical patients. All measurement findings were automatically classified as abnormal/normal using formalized medical background knowledge, i.e., knowledge that has been encoded into an ontology. A radiologist evaluated 813 classifications as correct or incorrect. All unclassified findings were evaluated as incorrect. The proposed approach allows the automatic classification of findings with an accuracy of 96.4 % for oncologic reports and 92.9 % for mixed reports. The ReportViewer permits efficient comparison of measured findings from consecutive examinations. The implementation of RECIST guidelines with SPARQL enhances the quality of the selection and comparison of target lesions as well as the corresponding treatment response evaluation. The developed MCI enables an accurate integrated representation of reported measurements and medical knowledge. Thus, measurements can be automatically classified and integrated in different decision processes. The structured representation is suitable for improved integration of clinical findings during decision-making. The proposed ReportViewer provides a longitudinal overview of the measurements.
Kim, Jinsuh; Leira, Enrique C; Callison, Richard C; Ludwig, Bryan; Moritani, Toshio; Magnotta, Vincent A; Madsen, Mark T
2010-05-01
We developed fully automated software for dynamic susceptibility contrast (DSC) MR perfusion-weighted imaging (PWI) to efficiently and reliably derive critical hemodynamic information for acute stroke treatment decisions. Brain MR PWI was performed in 80 consecutive patients with acute nonlacunar ischemic stroke within 24h after onset of symptom from January 2008 to August 2009. These studies were automatically processed to generate hemodynamic parameters that included cerebral blood flow and cerebral blood volume, and the mean transit time (MTT). To develop reliable software for PWI analysis, we used computationally robust algorithms including the piecewise continuous regression method to determine bolus arrival time (BAT), log-linear curve fitting, arrival time independent deconvolution method and sophisticated motion correction methods. An optimal arterial input function (AIF) search algorithm using a new artery-likelihood metric was also developed. Anatomical locations of the automatically determined AIF were reviewed and validated. The automatically computed BAT values were statistically compared with estimated BAT by a single observer. In addition, gamma-variate curve-fitting errors of AIF and inter-subject variability of AIFs were analyzed. Lastly, two observes independently assessed the quality and area of hypoperfusion mismatched with restricted diffusion area from motion corrected MTT maps and compared that with time-to-peak (TTP) maps using the standard approach. The AIF was identified within an arterial branch and enhanced areas of perfusion deficit were visualized in all evaluated cases. Total processing time was 10.9+/-2.5s (mean+/-s.d.) without motion correction and 267+/-80s (mean+/-s.d.) with motion correction on a standard personal computer. The MTT map produced with our software adequately estimated brain areas with perfusion deficit and was significantly less affected by random noise of the PWI when compared with the TTP map. Results of image quality assessment by two observers revealed that the MTT maps exhibited superior quality over the TTP maps (88% good rating of MTT as compared to 68% of TTP). Our software allowed fully automated deconvolution analysis of DSC PWI using proven efficient algorithms that can be applied to acute stroke treatment decisions. Our streamlined method also offers promise for further development of automated quantitative analysis of the ischemic penumbra. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.
Document Exploration and Automatic Knowledge Extraction for Unstructured Biomedical Text
NASA Astrophysics Data System (ADS)
Chu, S.; Totaro, G.; Doshi, N.; Thapar, S.; Mattmann, C. A.; Ramirez, P.
2015-12-01
We describe our work on building a web-browser based document reader with built-in exploration tool and automatic concept extraction of medical entities for biomedical text. Vast amounts of biomedical information are offered in unstructured text form through scientific publications and R&D reports. Utilizing text mining can help us to mine information and extract relevant knowledge from a plethora of biomedical text. The ability to employ such technologies to aid researchers in coping with information overload is greatly desirable. In recent years, there has been an increased interest in automatic biomedical concept extraction [1, 2] and intelligent PDF reader tools with the ability to search on content and find related articles [3]. Such reader tools are typically desktop applications and are limited to specific platforms. Our goal is to provide researchers with a simple tool to aid them in finding, reading, and exploring documents. Thus, we propose a web-based document explorer, which we called Shangri-Docs, which combines a document reader with automatic concept extraction and highlighting of relevant terms. Shangri-Docsalso provides the ability to evaluate a wide variety of document formats (e.g. PDF, Words, PPT, text, etc.) and to exploit the linked nature of the Web and personal content by performing searches on content from public sites (e.g. Wikipedia, PubMed) and private cataloged databases simultaneously. Shangri-Docsutilizes Apache cTAKES (clinical Text Analysis and Knowledge Extraction System) [4] and Unified Medical Language System (UMLS) to automatically identify and highlight terms and concepts, such as specific symptoms, diseases, drugs, and anatomical sites, mentioned in the text. cTAKES was originally designed specially to extract information from clinical medical records. Our investigation leads us to extend the automatic knowledge extraction process of cTAKES for biomedical research domain by improving the ontology guided information extraction process. We will describe our experience and implementation of our system and share lessons learned from our development. We will also discuss ways in which this could be adapted to other science fields. [1] Funk et al., 2014. [2] Kang et al., 2014. [3] Utopia Documents, http://utopiadocs.com [4] Apache cTAKES, http://ctakes.apache.org
Real-time 3D image reconstruction guidance in liver resection surgery
Nicolau, Stephane; Pessaux, Patrick; Mutter, Didier; Marescaux, Jacques
2014-01-01
Background Minimally invasive surgery represents one of the main evolutions of surgical techniques. However, minimally invasive surgery adds difficulty that can be reduced through computer technology. Methods From a patient’s medical image [US, computed tomography (CT) or MRI], we have developed an Augmented Reality (AR) system that increases the surgeon’s intraoperative vision by providing a virtual transparency of the patient. AR is based on two major processes: 3D modeling and visualization of anatomical or pathological structures appearing in the medical image, and the registration of this visualization onto the real patient. We have thus developed a new online service, named Visible Patient, providing efficient 3D modeling of patients. We have then developed several 3D visualization and surgical planning software tools to combine direct volume rendering and surface rendering. Finally, we have developed two registration techniques, one interactive and one automatic providing intraoperative augmented reality view. Results From January 2009 to June 2013, 769 clinical cases have been modeled by the Visible Patient service. Moreover, three clinical validations have been realized demonstrating the accuracy of 3D models and their great benefit, potentially increasing surgical eligibility in liver surgery (20% of cases). From these 3D models, more than 50 interactive AR-assisted surgical procedures have been realized illustrating the potential clinical benefit of such assistance to gain safety, but also current limits that automatic augmented reality will overcome. Conclusions Virtual patient modeling should be mandatory for certain interventions that have now to be defined, such as liver surgery. Augmented reality is clearly the next step of the new surgical instrumentation but remains currently limited due to the complexity of organ deformations during surgery. Intraoperative medical imaging used in new generation of automated augmented reality should solve this issue thanks to the development of Hybrid OR. PMID:24812598
Cheung, Carol C; Torlakovic, Emina E; Chow, Hung; Snover, Dale C; Asa, Sylvia L
2015-03-01
Pathologists provide diagnoses relevant to the disease state of the patient and identify specific tissue characteristics relevant to response to therapy and prognosis. As personalized medicine evolves, there is a trend for increased demand of tissue-derived parameters. Pathologists perform increasingly complex analyses on the same 'cases'. Traditional methods of workload assessment and reimbursement, based on number of cases sometimes with a modifier (eg, the relative value unit (RVU) system used in the United States), often grossly underestimate the amount of work needed for complex cases and may overvalue simple, small biopsy cases. We describe a new approach to pathologist workload measurement that aligns with this new practice paradigm. Our multisite institution with geographically diverse partner institutions has developed the Automatable Activity-Based Approach to Complexity Unit Scoring (AABACUS) model that captures pathologists' clinical activities from parameters documented in departmental laboratory information systems (LISs). The model's algorithm includes: 'capture', 'export', 'identify', 'count', 'score', 'attribute', 'filter', and 'assess filtered results'. Captured data include specimen acquisition, handling, analysis, and reporting activities. Activities were counted and complexity units (CUs) generated using a complexity factor for each activity. CUs were compared between institutions, practice groups, and practice types and evaluated over a 5-year period (2008-2012). The annual load of a clinical service pathologist, irrespective of subspecialty, was ∼40,000 CUs using relative benchmarking. The model detected changing practice patterns and was appropriate for monitoring clinical workload for anatomical pathology, neuropathology, and hematopathology in academic and community settings, and encompassing subspecialty and generalist practices. AABACUS is objective, can be integrated with an LIS and automated, is reproducible, backwards compatible, and future adaptable. It can be applied as a robust decision support tool for the assessment of overall and targeted staffing needs as well as utilization analyses for resource allocation.
Semi-Automated Trajectory Analysis of Deep Ballistic Penetrating Brain Injury
Folio, Les; Solomon, Jeffrey; Biassou, Nadia; Fischer, Tatjana; Dworzak, Jenny; Raymont, Vanessa; Sinaii, Ninet; Wassermann, Eric M.; Grafman, Jordan
2016-01-01
Background Penetrating head injuries (PHIs) are common in combat operations and most have visible wound paths on computed tomography (CT). Objective We assess agreement between an automated trajectory analysis-based assessment of brain injury and manual tracings of encephalomalacia on CT. Methods We analyzed 80 head CTs with ballistic PHI from the Institutional Review Board approved Vietnam head injury registry. Anatomic reports were generated from spatial coordinates of projectile entrance and terminal fragment location. These were compared to manual tracings of the regions of encephalomalacia. Dice’s similarity coefficients, kappa, sensitivities, and specificities were calculated to assess agreement. Times required for case analysis were also compared. Results Results show high specificity of anatomic regions identified on CT with semiautomated anatomical estimates and manual tracings of tissue damage. Radiologist’s and medical students’ anatomic region reports were similar (Kappa 0.8, t-test p < 0.001). Region of probable injury modeling of involved brain structures was sensitive (0.7) and specific (0.9) compared with manually traced structures. Semiautomated analysis was 9-fold faster than manual tracings. Conclusion Our region of probable injury spatial model approximates anatomical regions of encephalomalacia from ballistic PHI with time-saving over manual methods. Results show potential for automated anatomical reporting as an adjunct to current practice of radiologist/neurosurgical review of brain injury by penetrating projectiles. PMID:23707123
Sanniec, Kyle; Pezeshk, Ronnie; Chung, Michael
2016-01-01
Summary: Migraine headaches are a debilitating disease that causes significant socioeconomic problems. One of the speculated etiologies of the generation of migraines is peripheral nerve irritation at different trigger points. The use of Onabotulinum toxin A (BOTOX), although initially a novel approach, has now been determined to be a valid treatment for chronic headaches and migraines as described in the Phase III Research Evaluating Migraine Prophylaxis Therapy trials that prompted the approval by the Food and Drug Administration for treatment of chronic migraines. The injection paradigm established by this trial was one of a broad injection pattern across large muscle groups that did not always correspond to the anatomical locations of nerves. The senior author developed the Anatomical Regional Targeted BOTOX injection paradigm as an alternative to the current injection model. This technique targets both the anatomical location of nerves known to have causal effects with migraines and the region where the pain localizes, to provide relief across a wide distribution of the peripheral nerve. This article serves as a guide to the Anatomical Regional Targeted injection technique, which, to our knowledge, is the first comprehensive BOTOX injection paradigm described in the literature for treatment of migraines that targets nerves and nerve areas rather than purely muscle groups. This technique is based on the most up-to-date anatomical and scientific studies and large-volume migraine surgery experience. PMID:28293532
Park, Jin Seo; Shin, Dong Sun; Chung, Min Suk; Hwang, Sung Bae; Chung, Jinoh
2007-11-01
This article describes the technique of semiautomatic surface reconstruction of anatomic structures using widely available commercial software. This technique would enable researchers to promptly and objectively perform surface reconstruction, creating three-dimensional anatomic images without any assistance from computer engineers. To develop the technique, we used data from the Visible Korean Human project, which produced digitalized photographic serial images of an entire cadaver. We selected 114 anatomic structures (skin [1], bones [32], knee joint structures [7], muscles [60], arteries [7], and nerves [7]) from the 976 anatomic images which were generated from the left lower limb of the cadaver. Using Adobe Photoshop, the selected anatomic structures in each serial image were outlined, creating a segmented image. The Photoshop files were then converted into Adobe Illustrator files to prepare isolated segmented images, so that the contours of the structure could be viewed independent of the surrounding anatomy. Using Alias Maya, these isolated segmented images were then stacked to construct a contour image. Gaps between the contour lines were filled with surfaces, and three-dimensional surface reconstruction could be visualized with Rhinoceros. Surface imperfections were then corrected to complete the three-dimensional images in Alias Maya. We believe that the three-dimensional anatomic images created by these methods will have widespread application in both medical education and research. 2007 Wiley-Liss, Inc
Getting the Most from the Twin Mars Rovers
NASA Technical Reports Server (NTRS)
Laufenberg, Larry
2003-01-01
The report discusses the Mixed-initiative Activity Planning GENerator (MARGEN) automatically generates activity plans for rovers. Decision support system mixes autonomous planning/scheduling with user modifications. Accommodating change. Technology spotlight
Image based Monte Carlo Modeling for Computational Phantom
NASA Astrophysics Data System (ADS)
Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican
2014-06-01
The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.cn). The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients(Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection.
Valente, João; Vieira, Pedro M; Couto, Carlos; Lima, Carlos S
2018-02-01
Poor brain extraction in Magnetic Resonance Imaging (MRI) has negative consequences in several types of brain post-extraction such as tissue segmentation and related statistical measures or pattern recognition algorithms. Current state of the art algorithms for brain extraction work on weighted T1 and T2, being not adequate for non-whole brain images such as the case of T2*FLASH@7T partial volumes. This paper proposes two new methods that work directly in T2*FLASH@7T partial volumes. The first is an improvement of the semi-automatic threshold-with-morphology approach adapted to incomplete volumes. The second method uses an improved version of a current implementation of the fuzzy c-means algorithm with bias correction for brain segmentation. Under high inhomogeneity conditions the performance of the first method degrades, requiring user intervention which is unacceptable. The second method performed well for all volumes, being entirely automatic. State of the art algorithms for brain extraction are mainly semi-automatic, requiring a correct initialization by the user and knowledge of the software. These methods can't deal with partial volumes and/or need information from atlas which is not available in T2*FLASH@7T. Also, combined volumes suffer from manipulations such as re-sampling which deteriorates significantly voxel intensity structures making segmentation tasks difficult. The proposed method can overcome all these difficulties, reaching good results for brain extraction using only T2*FLASH@7T volumes. The development of this work will lead to an improvement of automatic brain lesions segmentation in T2*FLASH@7T volumes, becoming more important when lesions such as cortical Multiple-Sclerosis need to be detected. Copyright © 2017 Elsevier B.V. All rights reserved.