Uncertainty quantification in medical image segmentation with normalizing flows

4 June 2020

Papers citing "Uncertainty quantification in medical image segmentation with normalizing flows"

4 / 4 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 96 1 0 25 Nov 2024
MSEG-VCUQ: Multimodal SEGmentation with Enhanced Vision Foundation Models, Convolutional Neural Networks, and Uncertainty Quantification for High-Speed Video Phase Detection Data Chika Maduabuchi Ericmoore Jossou Matteo Bucci 45 0 0 12 Nov 2024
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 34 81 0 05 Oct 2022
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 289 9,167 0 06 Jun 2015