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| 1 | Recommendations to quantify villous atrophy in video capsule endoscopy images of celiac disease patients显示文摘AIM To quantify the presence of villous atrophy in endoscopic images for improved automation.METHODS There are two main categories of quantitative descriptors helpful to detect villous atrophy:(1) Statistical and(2) Syntactic. Statistical descriptors measure the small intestinal substrate in endoscope-acquired images based on mathematical methods. Texture is the most commonly used statistical descriptor to quantify villous atrophy. Syntactic descriptors comprise a syntax, or set of rules, for analyzing and parsing the substrate into a set of objects with boundaries. The syntax is designed to identify and distinguish three-dimensional structures based on their shape.RESULTS The variance texture statistical descriptor is useful to describe the average variability in image gray level representing villous atrophy, but does not determine the range in variability and the spatial relationships between regions. Improved textural descriptors will incorporate these factors, so that areas with variability gradients and regions that are orientation dependent can be distinguished. The protrusion syntactic descriptor is useful to detect three-dimensional architectural components, but is limited to identifying objects of a certain shape. Improvement in this descriptor will require incorporating flexibility to the prototypical template, so that protrusions of any shape can be detected, measured, and distinguished.CONCLUSION Improved quantitative descriptors of villous atrophy are being developed, which will be useful in detecting subtle, varying patterns of villous atrophy in the small intestinal mucosa of suspected and known celiac disease patients. | Edward J Ciaccio Govind Bhagat Suzanne K Lewis Peter H Green | 2016 | World Journal of Gastrointestinal Endoscopy2016，8，18： | 3 |
| 2 | Implementation of a polling protocol for predicting celiac disease in videocapsule analysis显示文摘AIM: To investigate the presence of small intestinal villous atrophy in celiac disease patients from quantitative analysis of videocapsule image sequences.METHODS: Nine celiac patient data with biopsy-proven villous atrophy and seven control patient data lacking villous atrophy were used for analysis. Celiacs had biopsy-proven disease with scores of Marsh Ⅱ-Ⅲ C except in the case of one hemophiliac patient. At four small intestinal levels (duodenal bulb, distal duodenum, jejunum, and ileum), video clips of length 200 frames (100 s) were analyzed. Twenty-four measurements were used for image characterization. These measurements were determined by quantitatively processing the videocapsule images via techniques for texture analysis, motility estimation, volumetric reconstruction using shape-from-shading principles, and image transformation. Each automated measurement method, or automaton, was polled as to whether or not villous atrophy was present in the small intestine, indicating celiac disease. Each automaton's vote was determined based upon an optimized parameter threshold level, with the threshold levels being determined from prior data. A prediction of villous atrophy was made if it received the majority of votes (≥ 13), while no prediction was made for tie votes (12-12). Thus each set of images was classified as being from either a celiac disease patient or from a control patient. RESULTS: Separated by intestinal level, the overall sensitivity of automata polling for predicting villous atrophy and hence celiac disease was 83.9%, while the specificity was 92.9%, and the overall accuracy of automata-based polling was 88.1%. The method of image transformation yielded the highest sensitivity at 93.8%, while the method of texture analysis using subbands had the highest specificity at 76.0%. Similar results of prediction were observed at all four small intestinal locations, but there were more tie votes at location 4 (ileum). Incorrect prediction which reduced sensitivity occurred for two celiac patients with Marsh type Ⅱ pattern, which is characterized by crypt hyperplasia, but normal villous architecture. Pooled from all levels, there was a mean of 14.31 ± 3.28 automaton votes for celiac vs 9.67 ± 3.31 automaton votes for control when celiac patient data was analyzed (P<0.001). Pooled from all levels, there was a mean of 9.71 ± 2.8128 automaton votes for celiac vs 14.32 ± 2.7931 automaton votes for control when control patient data was analyzed (P<0.001). CONCLUSION: Automata-based polling may be useful to indicate presence of mucosal atrophy, indicative of celiac disease, across the entire small bowel, though this must be confirmed in a larger patient set. Since the method is quantitative and automated, it can potentially eliminate observer bias and enable the detectionof subtle abnormality in patients lacking a clear diagnosis. Our paradigm was found to be more efficacious at proximal small intestinal locations, which may suggest a greater presence and severity of villous atrophy at proximal as compared with distal locations. | Edward J Ciaccio Christina A Tennyson Govind Bhagat Suzanne K Lewis Peter H Green | 2013 | World Journal of Gastrointestinal Endoscopy2013，5，7： | 3 |
| 3 | The Asia‐Pacific consensus on ulcerative colitis显示文摘 | Choon JinOoi Kwong MingFock Govind KMakharia Khean LeeGoh Khoon LinLing IdaHilmi Wee ChianLim ThiaKelvin Peter RGibson Richard BGearry QinOuyang JoseSollano SathapornManatsathit RungsunRerknimitr Shu‐chenWei Wai KeungLeung H JanakaDe Silva Rupert WLLeong | 2010 | Journal of Gastroenterology and Hepatology2010，，3： | 1 |
| 4 | Risk tolerance and asset allocation for investors nearing retirement 显示文摘 | Govind H Kenneth S C Dale L D | 2000 | Financial Services Review2000，，9： | 1 |
| 5 | EPR and optical absorption study of Mn2+-doped zinc ammonium phosphate hexahydrate single crystals显示文摘 | Kripal R Govind H Gupta S K | 2007 | Physica B: Condensed Matter2007，392，12： | 1 |
| 6 | Identification and functional validation of a unique set of drought induced genes preferentially expressed in response to gradual water stress in peanut 显示文摘 | Govind G ThammeGowda H V Kalaiarasi P J Iyer D R Muthappa S K Nese S Makarlu U K | 2009 | Mol Genet Genomics2009，281，： | 1 |
| 7 | Neural Network Pattern Recognizer for Detection of Failure Modes in the SSME显示文摘 | Luce H Govind R | | AIAA90-18930，，： | 1 |
| 8 | Identification and functional validation of a unique set of drought induced genes preferentially expressed in response to gradual water stress in peanut显示文摘 | Govind G ThammeGowda H V Kalaiarasi P J | 2009 | Molecular Genetics and Genomics2009，281，6： | 1 |
| 9 | Netral network pattem recognizor for detection of failure modes in the SSME显示文摘 | Luce H Govind R | | AIAA9018930，，： | 1 |
| 10 | Advances in biotreatment of acid mine drainage and biorecovery of metals-2: Membrane bioreaetor system for sulfate reduction 显示文摘 | Tabak H H Govind R | 2003 | Biodegradation2003，14，： | 1 |
| 11 | Development of quantitative structure-activity relationships for predicting biodegradation kinetics显示文摘 | DESAI S GOVIND R TABAK H H | 1990 | Environ Toxicol Chem1990，9，： | 1 |
| 12 | Prediction of biodegradation kinetics using a nonlinear group contribution method显示文摘 | Henery H T Rakesh Govind | 1993 | Environ- mental Toxicology and Chemistry1993，12，： | 1 |
| 13 | Neural network pattern recognizor for detection of failure modes in the SSME 显示文摘 | Luce H Govind R | | AIAA90-18930，，： | 1 |
| 14 | Membrane Bioreactor System for Sulfate Reduction显示文摘 | Tabak H H Govind R Advances in Biotreatment of Acid Mine Drainage and Biorecovery of Metals:2 | 2003 | Biodegration2003，14，： | 1 |
| 15 | Prediction of biodegradation kinetics using a nonlinear group contribution method显示文摘 | Tabak H H Govind R | 1993 | Environmen- tal Toxicology and Chemistry1993，，12： | 1 |
| 16 | Hemolysis Interferes with the Detection of Anti-Tissue Transglutaminase Antibodies in Celiac Disease显示文摘 | Arguelles-Grande Carolina Norman Gary L Bhagat Govind Green Peter H R | 2010 | Clinical Chemistry2010，，： | 1 |
| 17 | Quantitatively probing the Al distribution in zeolites 显示文摘 | VJUNOV A FULTON J L HUTHWELKER T PIN S MEI D H SCHENTER G K GOVIND N CAMAIONI D M HU J Z LERCHER J A | 2014 | J Am Chem Soc2014，136，23： | 1 |
| 18 | Artificial Intelligence in hepatology,liver surgery and transplantation:Emerging applications and frontiers of research显示文摘The integration of artificial intelligence(AI)and augmented realities into the medical field is being attempted by various researchers across the globe.As a matter of fact,most of the advanced technologies utilized by medical providers today have been borrowed and extrapolated from other industries.The introduction of AI into the field of hepatology and liver surgery is relatively a recent phenomenon.The purpose of this narrative review is to highlight the different AI concepts which are currently being tried to improve the care of patients with liver diseases.We end with summarizing emerging trends and major challenges in the future development of AI in hepatology and liver surgery. | Fadl H Veerankutty Govind Jayan Manish Kumar Yadav Krishnan Sarojam Manoj Abhishek Yadav Sindhu Radha Sadasivan Nair T U Shabeerali Varghese Yeldho Madhu Sasidharan Shiraz Ahmad Rather | 2021 | World Journal of Hepatology2021，13，12： | 1 |
| 19 | Neural network pattern recognizer for detection of failure modes in the SSME显示文摘 | Luce H Govind R | 1993 | AIAA1993，90，： | 1 |
| 20 | Neural network pattern recognizor for detection of failure modes in the SSME显示文摘 | Luce H Govind R | | AIAA90-18930，，： | 1 |
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