DCAN: Deep contour-aware networks for object instance segmentation from histology images-Reference-Cited by-同舟云学术

DCAN: Deep contour-aware networks for object instance segmentation from histology images

Published:2017-02 Issue: Volume:36 Page:135-146
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Chen Hao^ORCID,Qi Xiaojuan,Yu Lequan,Dou Qi,Qin Jing,Heng Pheng-Ann

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference78 articles.

1. Improved automatic detection and segmentation of cell nuclei in histopathology images;Al-Kofahi;IEEE Trans. Biomed. Eng.,2010

2. Color graphs for automated cancer diagnosis and grading;Altunbay;IEEE Trans. Biomed. Eng.,2010

3. Bayesian belief networks in quantitative histopathology;Bartels;Anal. Quant. Cytol. Histol./Int. Acad. Cytol. Am. Soc. Cytol.,1992

4. High-for-low and low-for-high: efficient boundary detection from deep object features and its applications to high-level vision;Bertasius,2015

5. Semantic segmentation with boundary neural fields;Bertasius;CoRR,2015

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