Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

10 June 2020

Miguel A. B. Monteiro

Loic Le Folgoc

Daniel Coelho De Castro

Nick Pawlowski

Bernardo Marques

Konstantinos Kamnitsas

Papers citing "Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty"

34 / 34 papers shown

Title
Dataset Distillation with Probabilistic Latent Features Zhe Li Sarah Cechnicka Cheng Ouyang Katharina Breininger Peter Schüffler Bernhard Kainz DD 47 0 0 10 May 2025
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection Moritz Vandenhirtz Julia E. Vogt 40 0 0 09 May 2025
L-FUSION: Laplacian Fetal Ultrasound Segmentation & Uncertainty Estimation J. Müller Robert Wright Thomas Day Lorenzo Venturini Samuel Budd Hadrien Reynaud J. Hajnal Reza Razavi B. Kainz MedIm 64 0 0 13 Mar 2025
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
Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer Sungmin Kang Jaeha Song Jihie Kim MedIm 38 2 0 01 Aug 2024
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees E. Nehme Rotem Mulayoff T. Michaeli UQCV 48 2 0 24 May 2024
Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding Lingdong Kong Xiang Xu Jun Cen Wenwei Zhang Liang Pan Kai-xiang Chen Ziwei Liu 53 5 0 25 Mar 2024
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation S. Chatterjee Franziska Gaidzik Alessandro Sciarra Hendrik Mattern G. Janiga Oliver Speck Andreas Nürnberger S. Pathiraja 52 0 0 25 Dec 2023
Uncertainty Visualization via Low-Dimensional Posterior Projections Omer Yair E. Nehme T. Michaeli UQCV 38 2 0 12 Dec 2023
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
Application-driven Validation of Posteriors in Inverse Problems T. Adler Jan-Hinrich Nolke Annika Reinke M. Tizabi Sebastian Gruber ... Lynton Ardizzone Paul F. Jaeger Florian Buettner Ullrich Kothe Lena Maier-Hein MedIm 40 1 0 18 Sep 2023
Multi-modal Learning with Missing Modality via Shared-Specific Feature Modelling Hu Wang Yuanhong Chen Congbo Ma Jodie Avery Louise Hull G. Carneiro 26 80 0 26 Jul 2023
Boundary-weighted logit consistency improves calibration of segmentation networks Neerav Karani Neel Dey Polina Golland 25 3 0 16 Jul 2023
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 25 0 0 02 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 31 80 0 05 Oct 2022
Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings Kaiwen Cai Chris Xiaoxuan Lu Xiaowei Huang 3DPC 37 2 0 29 Sep 2022
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation Jiamin Liang Yuhao Huang Haoming Li Shuangchi He Xindi Hu Zejian Chen Isabel Kaltenborn Dong Ni OOD 31 42 0 05 Aug 2022
Uncertainty-aware Multi-modal Learning via Cross-modal Random Network Prediction Hu Wang Jianpeng Zhang Yuanhong Chen Congbo Ma Jodie Avery Louise Hull G. Carneiro UQCV 21 18 0 22 Jul 2022
Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting Bohan Tang Yiqi Zhong Chenxin Xu Wei Wu Ulrich Neumann Yanfeng Wang Ya Zhang Siheng Chen 36 9 0 11 Jul 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 29 0 0 27 Jun 2022
Structured Uncertainty in the Observation Space of Variational Autoencoders James A. G. Langley M. Monteiro Charles Jones Nick Pawlowski Ben Glocker CML OOD BDL DRL 39 2 0 25 May 2022
Variational Inference for Quantifying Inter-observer Variability in Segmentation of Anatomical Structures Xiaofeng Liu Fangxu Xing Thibault Marin G. El Fakhri Jonghye Woo 36 5 0 18 Jan 2022
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels Sun-Beom Hong A. Bonkhoff Andrew Hoopes Martin Bretzner M. Schirmer A. Giese Adrian Dalca Polina Golland N. Rost UQCV 30 7 0 13 Dec 2021
Diffusion Models for Implicit Image Segmentation Ensembles J. Wolleb Robin Sandkühler Florentin Bieder Philippe Valmaggia Philippe C. Cattin DiffM MedIm VLM 24 267 0 06 Dec 2021
Exploring Feature Representation Learning for Semi-supervised Medical Image Segmentation Huimin Wu Xuelong Li Kwang-Ting Cheng 28 13 0 22 Nov 2021
Deep Classifiers with Label Noise Modeling and Distance Awareness Vincent Fortuin Mark Collier F. Wenzel J. Allingham J. Liu Dustin Tran Balaji Lakshminarayanan Jesse Berent Rodolphe Jenatton E. Kokiopoulou UQCV 34 11 0 06 Oct 2021
Using Soft Labels to Model Uncertainty in Medical Image Segmentation Joao Lourencco Silva Arlindo L. Oliveira UQCV 24 19 0 26 Sep 2021
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection H. Akrami Anand A. Joshi Sergul Aydore Richard M. Leahy UQCV 39 4 0 20 Sep 2021
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation Camila González Karol Gotkowski A. Bucher Ricarda Fischbach Isabel Kaltenborn Anirban Mukhopadhyay 24 31 0 13 Jul 2021
Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis Christoph Berger Magdalini Paschali Ben Glocker Konstantinos Kamnitsas OOD 43 42 0 06 Jul 2021
Correlated Input-Dependent Label Noise in Large-Scale Image Classification Mark Collier Basil Mustafa Efi Kokiopoulou Rodolphe Jenatton Jesse Berent NoLa 181 53 0 19 May 2021
Is segmentation uncertainty useful? Steffen Czolbe K. Arnavaz Oswin Krause Aasa Feragen UQCV 28 43 0 30 Mar 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015