Efficient deep learning model for mitosis detection using breast histopathology images-Reference-Cited by-同舟云学术

Efficient deep learning model for mitosis detection using breast histopathology images

Published:2018-03 Issue: Volume:64 Page:29-40
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Saha Monjoy,Chakraborty Chandan,Racoceanu Daniel^ORCID

Funder

Ministry of Human Resource Development (MHRD), Govt. of India

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

Reference58 articles.

1. Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images;Albarqouni;IEEE Trans. Med. Imaging,2016

2. Assessment of Mitosis Detection Algorithms 2013 (AMIDA13), 2016. http://amida13.isi.uu.nl/ (accessed 24.10.16).

3. Mitosis detection in breast cancer histological images with mathematical morphology;Aptoula,2013

4. Nuclear segmentation in H&E Sections via multi-reference graph cut (MRGC);Chang;International Symposium Biomedical Imaging,2012

5. Mitosis detection in breast cancer histology images with deep neural networks;Cireşan,2013

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