Histology segmentation using active learning on regions of interest in oral cavity squamous cell carcinoma

Histology segmentation using active learning on regions of interest in oral cavity squamous cell carcinoma

In digital pathology, deep learning has been shown to have a wide range of applications, from cancer grading to segmenting structures like glomeruli. One of the main hurdles for digital pathology to be truly effective is the size of the dataset needed for generalization to address the spectrum of po...

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Bibliographic Details
Main Authors: Jonathan Folmsbee, Lei Zhang, Xulei Lu, Jawaria Rahman, John Gentry, Brendan Conn, Marilena Vered, Paromita Roy, Ruta Gupta, Diana Lin, Shabnam Samankan, Pooja Dhorajiva, Anu Peter, Minhua Wang, Anna Israel, Margaret Brandwein-Weber, Scott Doyle
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Journal of Pathology Informatics
Subjects:
Active learning
Oral cavity cancer
Computational pathology
U-net
Digital pathology
Semantic segmentation
Online Access:http://www.sciencedirect.com/science/article/pii/S2153353922007404

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http://www.sciencedirect.com/science/article/pii/S2153353922007404

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