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1807.01788
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MITOS-RCNN: A Novel Approach to Mitotic Figure Detection in Breast Cancer Histopathology Images using Region Based Convolutional Neural Networks
4 July 2018
S. Rao
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ArXiv (abs)
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Papers citing
"MITOS-RCNN: A Novel Approach to Mitotic Figure Detection in Breast Cancer Histopathology Images using Region Based Convolutional Neural Networks"
6 / 6 papers shown
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes
Haojue Huang
G. Zhou
Xuejun Liu
L. Deng
Chengju Wu
Dachuan Zhang
Hui Liu
MedIm
106
18
0
25 Apr 2022
OncoPetNet: A Deep Learning based AI system for mitotic figure counting on H&E stained whole slide digital images in a large veterinary diagnostic lab setting
Michael Fitzke
Derick Whitley
Wilson Yau
Fernando Rodrigues
V. Fadeev
C. Bacmeister
Chris Carter
Jeffrey Edwards
M. Lungren
Mark Parkinson
157
6
0
17 Aug 2021
Deep Learning in Computer-Aided Diagnosis and Treatment of Tumors: A Survey
Dan Zhao
Guizhi Xu
Xu Zhenghua
Thomas Lukasiewicz
Minmin Xue
Zhigang Fu
OOD
228
4
0
02 Nov 2020
Deep Feature Fusion for Mitosis Counting
R. Yancey
128
2
0
01 Feb 2020
Deep neural network models for computational histopathology: A survey
C. Srinidhi
Ozan Ciga
Anne L. Martel
AI4CE
400
653
0
28 Dec 2019
Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor Infiltrating Lymphocytes in Invasive Breast Cancer
American Journal of Pathology (Am J Pathol), 2019
H. Le
Rajarsi R. Gupta
L. Hou
Shahira Abousamra
Danielle Fassler
...
A. Dyke
Ashish Sharma
Erich Bremer
Jonas S. Almeida
Joel H. Saltz
201
109
0
26 May 2019
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