SPLICE: Streamlining Digital Pathology Image Processing-Reference-Cited by-同舟云学术

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SPLICE: Streamlining Digital Pathology Image Processing

Published:2024-07 Issue: Volume: Page:
ISSN:0002-9440
Container-title:The American Journal of Pathology
language:en
Short-container-title:The American Journal of Pathology

Author:

Alsaafin Areej,Nejat Peyman^ORCID,Shafique Abubakr,Khan Jibran,Alfasly Saghir,Alabtah Ghazal,Tizhoosh Hamid R.^ORCID

Funder

Mayo Clinic

Publisher

Elsevier BV

Reference29 articles.

1. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning;Coudray;Nat Med,2018

2. Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features;Yu;Nat Commun,2016

3. Yottixel—an image search engine for large archives of histopathology whole slide images;Kalra;Med Image Anal,2020

4. Pathologist-level interpretable whole-slide cancer diagnosis with deep learning;Zhang;Nat Mach Intell,2019

5. Similar image search for histopathology: Smily;Hegde;NPJ Digit Med,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improving the Annotation Process in Computational Pathology: A Pilot Study with Manual and Semi-automated Approaches on Consumer and Medical Grade Devices;Journal of Imaging Informatics in Medicine;2024-09-04

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