Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation

13 April 2021

Papers citing "Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation"

10 / 10 papers shown

Title
Artificially Generated Visual Scanpath Improves Multi-label Thoracic Disease Classification in Chest X-Ray Images Ashish Verma Aupendu Kar Krishnendu Ghosh S. K. Dhara Debashis Sen P. Biswas MedIm 44 0 0 01 Mar 2025
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks Lorenz Linhardt Klaus-Robert Muller G. Montavon AAML 26 7 0 12 Apr 2023
Deep Active Learning Using Barlow Twins J. Mandivarapu Blake Camp Rolando Estrada SSL 27 0 0 30 Dec 2022
Cyclic Generative Adversarial Networks With Congruent Image-Report Generation For Explainable Medical Image Analysis Dwarikanath Mahapatra GAN MedIm 16 0 0 16 Nov 2022
Improved Super Resolution of MR Images Using CNNs and Vision Transformers Dwarikanath Mahapatra SupR ViT MedIm 27 5 0 24 Jul 2022
Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification Dwarikanath Mahapatra MedIm 20 2 0 04 Apr 2022
CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis Dwarikanath Mahapatra Ankur Singh 30 8 0 15 Jun 2021
Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance Dwarikanath Mahapatra Behzad Bozorgtabar Jean-Philippe Thiran Ling Shao MedIm 13 46 0 05 Aug 2020
CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation D. Jin Ziyue Xu Youbao Tang Adam P. Harrison D. Mollura MedIm 55 185 0 11 Jun 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,684 0 28 Feb 2017