Challenges for machine learning in clinical translation of big data imaging studies

7 July 2021

Papers citing "Challenges for machine learning in clinical translation of big data imaging studies"

7 / 7 papers shown

Title
MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning Xiangde Luo Guotai Wang Tao Song Jingyang Zhang Michael Aertsen Jan Deprest Sebastien Ourselin Tom Kamiel Magda Vercauteren Shaoting Zhang 43 96 0 25 Apr 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 63 83 0 11 Jan 2021
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 174 1,690 0 18 Mar 2020
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning Fernando Pérez-García Rachel Sparks Sébastien Ourselin MedIm LM&MA 132 426 0 09 Mar 2020
Anatomically-Informed Data Augmentation for functional MRI with Applications to Deep Learning K. Nguyen Cherise R. Chin Fatt A. Treacher C. Mellema M. Trivedi A. Montillo MedIm 16 27 0 17 Oct 2019
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy Christian Wachinger M. Reuter T. Klein 3DV 23 330 0 27 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015