Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining

8 August 2023

Papers citing "Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining"

8 / 8 papers shown

Title
Divergent Domains, Convergent Grading: Enhancing Generalization in Diabetic Retinopathy Grading Sharon Chokuwa M. H. Khan 24 0 0 04 Nov 2024
Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise Bidur Khanal Tianhong Dai Binod Bhattarai Cristian A. Linte NoLa 48 0 0 08 Jul 2024
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification Lucas Dedieu Nicolas Nerrienet A. Nivaggioli Clara Simmat Marceau Clavel Arnaud Gauthier Stéphane Sockeel Rémy Peyret NoLa 23 1 0 11 Apr 2024
QMix: Quality-aware Learning with Mixed Noise for Robust Retinal Disease Diagnosis Junlin Hou Jilan Xu Rui Feng Hao Chen 23 0 0 08 Apr 2024
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets? Bidur Khanal Binod Bhattarai Bishesh Khanal Cristian A. Linte NoLa 21 0 0 15 Jan 2024
Sample selection with noise rate estimation in noise learning of medical image analysis Maolin Li G. Tarroni OOD 32 0 0 23 Dec 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,434 0 11 Nov 2021
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 307 497 0 05 Mar 2020