Fat Quantitation in Liver Biopsies Using a Pretrained Classification Based System

Non-Alcoholic Fatty Liver Disease (NAFLD) is a common syndrome that mainly leads to fat accumulation in liver and steatohepatitis. It is targeted as a severe medical condition ranging from 20% to 40% in adult populations of the Western World. Its effect is identified through insulin resistance, which places patients at high mortality rates. An increased fat aggregation rate, can dramatically increase the development of liver steatosis, which in later stages may advance into fibrosis and cirrhosis. During recent years, new studies have focused on building new methodologies capable of detecting fat cells, based on the histology method with digital image processing techniques. The current study, expands previous work on the detection of fatty liver, by identifying once more a number of diverse histological findings. It is a combined study of both image analysis and supervised learning of fat droplet features, with a specific goal to exclude other findings from fat ratio calculation. The method is evaluated in a total set of 40 liver biopsy images with different magnification capabilities, performing satisfyingly (1.95% absolute error)

Detection and Spatial Analysis of Hepatic Steatosis in Histopathology Images using Sparse Linear Models

International audienceHepatic steatosis is a defining feature of nonalco-holic fatty liver disease, emerging with the increasing incidence of obesity and metabolic syndrome. The research in image-based analysis of hepatic steatosis mostly focuses on the quantification of fat in biopsy images. This work furthers the image-based analysis of hepatic steatosis by exploring the spatial characteristics of fat globules in whole slide biopsy images after performing fat detection. An algorithm based on morphological filtering and sparse linear models is presented for fat detection. Then the spatial properties of detected fat globules in relation to the hepatic anatomical structures of central veins and portal tracts are explored. The test dataset consists of 38 high resolution images from 21 patients. The experimental results provide an insight into the size distributions of fat globules and their location with respect to the anatomical structures

Fat Quantitation in Liver Biopsies Using a Pretrained Classification Based System

Non-Alcoholic Fatty Liver Disease (NAFLD) is a common syndrome that mainly leads to fat accumulation in liver and steatohepatitis. It is targeted as a severe medical condition ranging from 20% to 40% in adult populations of the Western World. Its effect is identified through insulin resistance, which places patients at high mortality rates. An increased fat aggregation rate, can dramatically increase the development of liver steatosis, which in later stages may advance into fibrosis and cirrhosis. During recent years, new studies have focused on building new methodologies capable of detecting fat cells, based on the histology method with digital image processing techniques. The current study, expands previous work on the detection of fatty liver, by identifying once more a number of diverse histological findings. It is a combined study of both image analysis and supervised learning of fat droplet features, with a specific goal to exclude other findings from fat ratio calculation. The method is evaluated in a total set of 40 liver biopsy images with different magnification capabilities, performing satisfyingly (1.95% absolute error)

Automated analysis of necrosis and steatosis in histological images : Practical solutions for coping with heterogeneity and variability

Pathological examination of histological tissue sections is essential for the diagnosis of many life-threatening diseases. Demographic change and the growing importance of precision medicine require pathology to become more efficient, reproducible and quantitative. Automated histological image analysis is an important tool to meet these demands. This thesis is based on five research papers that consider specific problems in histological image analysis. The problems are related either to the quantification of necrosis or to the quantification of steatosis in histological sections of liver tissue. Both are typical applications in which tissue structures or cellular structures must be identified and quantitatively analyzed. In this context, the papers address important general challenges in histological image analysis and present broadly applicable solutions. One challenge is spatial heterogeneity of tissue properties, which can make their quantification sensitive to tissue sampling and image analysis errors. As a solution, the papers present novel scores that enable reliable measurement of heterogeneously distributed tissue properties. Another challenge is the huge variability of histological images, which can make machine learning-based analysis methods require large amounts of training data to work robustly. As a solution, the papers show how interactive training can produce accurate results with little training effort. Finally, a practical challenge is achieving a good trade-off between accuracy, efficiency, and simplicity. In this regard, the papers describe pragmatic approaches to enable accurate and fast analysis of gigapixel images on standard computers

Focal Spot, Winter 2006/2007

https://digitalcommons.wustl.edu/focal_spot_archives/1104/thumbnail.jp

Perspective review on solid-organ transplant: Needs in point-of-care optical biomarkers

Solid-organ transplant is one of the most complex areas of modern medicine involving surgery. There are challenging opportunities in solid-organ transplant, specifically regarding the deficiencies in pathology workflow or gaps in pathology support, which may await alleviations or even de novo solutions, by means of point-of-care, or point-of-procedure optical biomarkers. Focusing the discussions of pathology workflow on donor liver assessment, we analyze the undermet need for intraoperative, real-time, and nondestructive assessment of the donor injuries (such as fibrosis, steatosis, and necrosis) that are the most significant predictors of post-transplant viability. We also identify an unmet need for real-time and nondestructive characterization of ischemia or irreversible injuries to the donor liver, earlier than appearing on morphological histology examined with light microscopy. Point-of-procedure laparoscopic optical biomarkers of liver injuries and tissue ischemia may also facilitate post-transplant management that is currently difficult for or devoid of pathological consultation due to lack of tools. The potential and pitfalls of point-of-procedure optical biomarkers for liver assessment are exemplified in breadth for steatosis. The more general and overarching challenges of point-of-procedure optical biomarkers for liver transplant pathology, including the shielding effect of the liver capsule that was quantitated only recently, are projected. The technological and presentational benchmarks that a candidate technology of point-of-procedure optical biomarkers for transplant pathology must demonstrate to motivate clinical translation are also foreseen.Electrical and Computer Engineerin

Ultrasound Imaging

This book provides an overview of ultrafast ultrasound imaging, 3D high-quality ultrasonic imaging, correction of phase aberrations in medical ultrasound images, etc. Several interesting medical and clinical applications areas are also discussed in the book, like the use of three dimensional ultrasound imaging in evaluation of Asherman's syndrome, the role of 3D ultrasound in assessment of endometrial receptivity and follicular vascularity to predict the quality oocyte, ultrasound imaging in vascular diseases and the fetal palate, clinical application of ultrasound molecular imaging, Doppler abdominal ultrasound in small animals and so on

Program and Proceedings: The Nebraska Academy of Sciences 1880-2013

PROGRAM FRIDAY, APRIL 19, 2013 REGISTRATION FOR ACADEMY, Lobby of Lecture wing, Olin Hall Aeronautics and Space Science, Session A, Olin 249 Aeronautics and Space Science, Session B, Olin 224 Collegiate Academy, Biology Session A, Olin B Biological and Medical Sciences, Session A, Olin 112 Biological and Medical Sciences, Session B, Smith Callen Conference Center NE Chapter, Nat\u27l Council For Geographic Education, Olin 325 Junior Academy, Judges Check-In, Olin 219 Junior Academy, Senior High REGISTRATION, Olin Hall Lobby Chemistry and Physics, Section A, Chemistry, Olin A Chemistry and Physics, Section B, Physics, Planetarium Collegiate Academy, Chemistry and Physics, Session A, Olin 324 Junior Academy, Senior High Competition, Olin 124, Olin 131 Aeronautics and Space Science, Poster Session, Olin 249 Anthropology, Olin 111 NWU Health and Sciences Graduate School Fair, Olin and Smith Curtiss Halls Aeronautics and Space Science, Poster Session, Olin 249 MAIBEN MEMORIAL LECTURE, OLIN B Bob Feurer, North Bend High School, Making People Smarter Using Habits of Mind LUNCH, PATIO ROOM, STORY STUDENT CENTER (pay and carry tray through cafeteria line, or pay at NAS registration desk) Aeronautics Group, Sunflower Room Biological and Medical Sciences, Session C, Olin 112 Biological and Medical Sciences, Session D, Smith Callen Conference Center Chemistry and Physics, Section A, Chemistry, Olin A Collegiate Academy, Biology Session A, Olin B Collegiate Academy, Biology Session B, Olin 249 Collegiate Academy, Chemistry and Physics, Session B, Olin 324 Junior Academy, Judges Check-In, Olin 219 Junior Academy, Junior High REGISTRATION, Olin Hall Lobby Junior Academy, Senior High Competition, (Final), Olin 110 Anthropology, Olin 111 Teaching of Science and Math, Olin 224 Applied Science and Technology, Olin 325 Junior Academy, Junior High Competition, Olin 124, Olin 131 NJAS Board/Teacher Meeting, Olin 219 BUSINESS MEETING, OLIN B AWARDS RECEPTION for NJAS, Scholarships, Members, Spouses, and Guests First United Methodist Church, 2723 N 50th Street, Lincoln, N