Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation

28 April 2020

Papers citing "Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation"

8 / 8 papers shown

Title
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation? Kumar Abhishek J. Kawahara Ghassan Hamarneh 61 0 0 12 Aug 2025
Segmentation Style Discovery: Application to Skin Lesion Images Kumar Abhishek J. Kawahara Ghassan Hamarneh 154 2 0 05 Aug 2024
Exploring Intrinsic Properties of Medical Images for Self-Supervised Binary Semantic Segmentation P. Singh Jacopo Cirrone 220 0 0 04 Feb 2024
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries Shuai Wang Tengjin Weng Jingyi Wang Yang Shen Zhidong Zhao Yixiu Liu Pengfei Jiao Zhiming Cheng Yaqi Wang 100 1 0 17 Nov 2023
Test-Time Selection for Robust Skin Lesion Analysis Alceu Bissoto Catarina Barata Eduardo Valle Sandra Avila 73 1 0 10 Aug 2023
A Survey on Deep Learning for Skin Lesion Segmentation Z. Mirikharaji Kumar Abhishek Alceu Bissoto Catarina Barata Sandra Avila Eduardo Valle M. Celebi Ghassan Hamarneh 330 124 0 01 Jun 2022
Towards Single Stage Weakly Supervised Semantic Segmentation Peri Akiva Kristin J. Dana 168 9 0 18 Jun 2021
D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation Z. Mirikharaji Kumar Abhishek S. Izadi Ghassan Hamarneh 166 34 0 14 Dec 2020