Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation
for Structure-wise Quality Control

Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control

24 November 2018

Abhijit Guha Roy

Sailesh Conjeti

Nassir Navab

Christian Wachinger

Papers citing "Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control"

17 / 17 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 91 1 0 25 Nov 2024
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 18 1 0 11 Aug 2023
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation A. Vasiliuk Daria Frolova Mikhail Belyaev B. Shirokikh 28 2 0 01 Nov 2022
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture M. Jung He Zhao Joanna Dipnall Belinda Gabbe Lan Du UQCV EDL 57 12 0 06 Oct 2022
GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentation Min Seok Lee Seok Woo Yang S. W. Han 3DPC 22 21 0 02 Oct 2022
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust Benjamin Lambert Florence Forbes Senan Doyle A. Tucholka M. Dojat UQCV MedIm 6 6 0 22 Sep 2022
Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows Elena Williams Sebastian Niehaus J. Reinelt A. Merola P. Mihai ... Evelyn Medawar Daniel Lichterfeld Ingo Roeder N. Scherf Maria del C. Valdés Hernández 26 3 0 06 Dec 2021
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks Giuseppina Carannante Dimah Dera Nidhal C.Bouaynaya Hassan M. Fathallah-Shaykh Ghulam Rasool UQCV AAML OOD 27 6 0 10 Nov 2021
A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications Xinlei Zhou Han Liu Farhad Pourpanah T. Zeng Xizhao Wang UQCV UD 24 58 0 03 Nov 2021
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
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 35 1,109 0 07 Jul 2021
Deep and Statistical Learning in Biomedical Imaging: State of the Art in 3D MRI Brain Tumor Segmentation K. R. M. Fernando Cris P Tsokos 28 53 0 09 Mar 2021
Influence of segmentation accuracy in structural MR head scans on electric field computation for TMS and tES E. Rashed J. Gómez-Tames A. Hirata 13 10 0 25 Sep 2020
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation Hong Joo Lee S. T. Kim Hakmin Lee Nassir Navab Yong Man Ro UQCV 16 7 0 21 May 2020
Knowing what you know in brain segmentation using Bayesian deep neural networks Patrick McClure Nao Rho J. Lee Jakub R. Kaczmarzyk C. Zheng Satrajit S. Ghosh D. Nielson Adam G. Thomas P. Bandettini Francisco Pereira UQCV 3DV BDL 24 52 0 03 Dec 2018
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy Christian Wachinger M. Reuter T. Klein 3DV 40 330 0 27 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015