Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment

2 July 2020

Papers citing "Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment"

8 / 8 papers shown

Title
Deep neural network models for computational histopathology: A survey C. Srinidhi Ozan Ciga Anne L. Martel AI4CE 85 573 0 28 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 319 42,038 0 03 Dec 2019
Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation D. J. Ho D. V. K. Yarlagadda Timothy D’alfonso M. Hanna Anne Grabenstetter Peter Ntiamoah E. Brogi L. Tan Thomas J. Fuchs 34 107 0 29 Oct 2019
A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer Byungjae Lee K. Paeng 43 55 0 30 May 2018
Deep Learning for Identifying Metastatic Breast Cancer Dayong Wang A. Khosla Rishab Gargeya H. Irshad Andrew H. Beck MedIm 64 940 0 18 Jun 2016
Fully Convolutional Networks for Semantic Segmentation Evan Shelhamer Jonathan Long Trevor Darrell VOS SSeg 440 37,704 0 20 May 2016
Computational Pathology: Challenges and Promises for Tissue Analysis Thomas J. Fuchs J. M. Buhmann AI4CE 42 251 0 31 Dec 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.4K 76,547 0 18 May 2015