As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging

As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging

25 July 2019

Zach Eaton-Rosen

Thomas Varsavsky

Sebastien Ourselin

M. Jorge Cardoso

Papers citing "As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging"

6 / 6 papers shown

Title
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods Ling Huang S. Ruan Yucheng Xing Mengling Feng 46 20 0 09 Oct 2023
A Review of Uncertainty Estimation and its Application in Medical Imaging K. Zou Zhihao Chen Xuedong Yuan Xiaojing Shen Meng Wang Huazhu Fu UQCV 54 87 0 16 Feb 2023
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
Self-Normalized Density Map (SNDM) for Counting Microbiological Objects K. Graczyk J. Pawlowski Sylwia Majchrowska Tomasz Golan 28 9 0 15 Mar 2022
A Decoupled Uncertainty Model for MRI Segmentation Quality Estimation Richard Shaw Carole H. Sudre Sebastien Ourselin M. Jorge Cardoso H. Pemberton UQCV 27 5 0 06 Sep 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015