Improving the Reliability of Semantic Segmentation of Medical Images by Uncertainty Modeling with Bayesian Deep Networks and Curriculum Learning

26 August 2021

Papers citing "Improving the Reliability of Semantic Segmentation of Medical Images by Uncertainty Modeling with Bayesian Deep Networks and Curriculum Learning"

3 / 3 papers shown

Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 286 1 0 25 Nov 2024
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation A. Vasiliuk Daria Frolova Mikhail Belyaev B. Shirokikh 85 2 0 01 Nov 2022
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 106 88 0 05 Oct 2022