ArticleAdvances in neural information processing systems2024
Topology-Aware Uncertainty for Image Segmentation.
Article in Advances in neural information processing systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Self-supervised small vessel segmentation with shape-aware geometric models and attention.Medical image analysis · 2026Article
- Uncertainty Quantification in Medical Image Segmentation: A Comprehensive Survey.Journal of imaging · 2026Review
- Real-Time Topology-Aware Branch Segmentation for UAV Perception in Natural Environments.Sensors (Basel, Switzerland) · 2026Article
- Rethinking deep learning in bioimaging through a data centric lens.Npj imaging · 2025Article
- Masked Vascular Structure Segmentation and Completion in Retinal Images.IEEE transactions on medical imaging · 2025Article
- Quantifying the Unknowns of Plaque Morphology: The Role of Topological Uncertainty in Coronary Artery Disease.Mayo Clinic proceedings. Digital health · 2025Article
- Article
- TOPODIFFUSIONNET: A TOPOLOGY-AWARE DIFFUSION MODEL.... International Conference on Learning Representations · 2025Article
- Universal Vessel Segmentation for Multi-Modality Retinal Images.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2025Article
- TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs.Medical image analysis · 2025Article
- Position: Topological Deep Learning is the New Frontier for Relational Learning.Proceedings of machine learning research · 2024Article
- Projected pooling loss for red nucleus segmentation with soft topology constraints.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- The Future of Material Scientists in an Age of Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Topology-based segmentation of 3D confocal images of emerging hematopoietic stem cells in the zebrafish embryo.Biological imaging · 2024Article
- Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency.Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision · 2024Article
- Automatic vectorization of historical maps: A benchmark.PloS one · 2024Article
- Morphological multiparameter filtration and persistent homology in mitochondrial image analysis.PloS one · 2024Article
- Article
- Topological Learning and Its Application to Multimodal Brain Network Integration.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology. To facilitate and accelerate large scale annotation, one has to adopt semi-automatic approaches such as proofreading by experts. In this work, we focus on uncertainty estimation for such tasks, so that highly uncertain, and thus error-prone structures can be identified for human annotators to verify. Unlike most existing works, which provide pixel-wise uncertainty maps, we stipulate it is crucial to estimate uncertainty in the units of topological structures, e.g., small pieces of connections and branches. To achieve this, we leverage tools from topological data analysis, specifically discrete Morse theory (DMT), to first capture the structures, and then reason about their uncertainties. To model the uncertainty, we (1) propose a joint prediction model that estimates the uncertainty of a structure while taking the neighboring structures into consideration (inter-structural uncertainty); (2) propose a novel Probabilistic DMT to model the inherent uncertainty within each structure (intra-structural uncertainty) by sampling its representations via a perturb- and-walk scheme. On various 2D and 3D datasets, our method produces better structure-wise uncertainty maps compared to existing works. Code available at https://github.com/Saumya-Gupta-26/struct-uncertainty.
Identifiers
39484069PMC11526043What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.