A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology
A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology
ABSTRACT BackgroundImage-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power. MethodsWe have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis. ResultsBy segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy. ConclusionThe ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.
Alpers Charles E.、Wang Xiaoxin X.、Levi Moshe、Han Seung Seok、Rosenberg Avi Z.、Lutnick Brendon、Manthey David、Becker Jan U.、Ginley Brandon、Myakala Komuraiah、Jones Bryce A.、Moos Katharina、Barisoni Laura、Yoshida Teruhiko、Kopp Jeffrey B.、Sarder Pinaki、for the Kidney Precision Medicine Project、Rodrigues Luis、Gallan Alexander J.、Zuckerman Jonathan E.、Jain Sanjay、Jen Kuang Yu.
Department of Laboratory Medicine and Pathology, University of WashingtonDepartments of Biochemistry and Molecular & Cellular Biology, Georgetown UniversityDepartments of Biochemistry and Molecular & Cellular Biology, Georgetown UniversityDepartment of Internal Medicine, Seoul National University College of MedicineDepartment of Pathology, Johns Hopkins UniversityDepartment of Pathology and Anatomical SciencesKitware IncorporatedInstitute of Pathology, University Hospital CologneDepartment of Pathology and Anatomical SciencesDepartments of Biochemistry and Molecular & Cellular Biology, Georgetown UniversityDepartment of Pharmacology and Physiology, Georgetown UniversityInstitute of Pathology, University Hospital CologneDepartments of Pathology and Medicine, Duke UniversityKidney Disease SectionKidney Disease SectionDepartment of Pathology and Anatomical SciencesUniversity Clinic of Nephrology, Faculty of Medicine, University of CoimbraDepartment of Pathology, Medical College of WisconsinDepartment of Pathology and Laboratory Medicine, University of California at Los AngelesDepartment of Medicine, Nephrology, Washington University School of MedicineDepartment of Pathology and Laboratory Medicine, University of California at Davis
医学研究方法生物科学研究方法、生物科学研究技术计算技术、计算机技术
Image SegmentationEnd-User SoftwareMachine LearningCloud based AnnotationChronic Kidney Disease
Alpers Charles E.,Wang Xiaoxin X.,Levi Moshe,Han Seung Seok,Rosenberg Avi Z.,Lutnick Brendon,Manthey David,Becker Jan U.,Ginley Brandon,Myakala Komuraiah,Jones Bryce A.,Moos Katharina,Barisoni Laura,Yoshida Teruhiko,Kopp Jeffrey B.,Sarder Pinaki,for the Kidney Precision Medicine Project,Rodrigues Luis,Gallan Alexander J.,Zuckerman Jonathan E.,Jain Sanjay,Jen Kuang Yu..A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology[EB/OL].(2025-03-28)[2025-04-27].https://www.biorxiv.org/content/10.1101/2021.08.16.456524.点此复制
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