Deep learning–based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study

202095 citationsJournal Articlegold Open Access

Authors

Xingyu Zhao · University of Science and Technology of China

Peiyi Xie · Sun Yat-sen University

Mengmeng Wang · Suzhou Institute of Biomedical Engineering and Technology

Wenjun Li · Sixth Affiliated Hospital of Sun Yat-sen University

Perry J. Pickhardt · University of Wisconsin–Madison

Wei Xia · Suzhou Institute of Biomedical Engineering and Technology

Fei Xiong

Abstract

This deep learning-based auto-LNDS model can achieve pelvic LNseffectively based on mpMRI for RC, and holds great potential for facilitating N-staging in clinical practice.

Topics & Keywords

Colorectal Cancer Surgical Treatments Radiomics and Machine Learning in Medical Imaging Colorectal Cancer Screening and Detection

Publication Details

Published in: EBioMedicine

Volume 56, pp. 102780-102780

DOI: 10.1016/j.ebiom.2020.102780

Field-Weighted Citation Impact: 4.69

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Deep learning–based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study

Authors

Abstract

Topics & Keywords

Publication Details