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Evaluation of Uncertainty-Aware Multi-Software Ensembles for Hippocampal Segmentation

Paper recorded by Signals 4 on 2026-10-22 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-22 on arXiv · recorded by Signals 4 on 2026-10-23

Category: cs.CV · 计算机视觉 · first seen 2026-10-23

Abstract

Accurate hippocampal segmentation can be a useful tool for diagnosing and monitoring neurological conditions such as Alzheimer's disease and epilepsy. While numerous automated segmentation methods exist, their clinical adoption remains limited. Reliable uncertainty assessment can enhance trust and facilitate clinical translation. This study evaluates ensembles of five heterogeneous hippocampal seg

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#186 most recent of 756 cs.CV papers we have recorded · ↑ newer: Diffusion-Based Synthesis of Complete 3D Biparametric Prostate MRI · ↓ older: AgentVQA: A Unified Benchmark for Agentic Visual Understanding
Cite this page: Evaluation of Uncertainty-Aware Multi-Software Ensembles for Hippocampal Segmentation: the #186 most recent of 756 cs.CV papers we have recorded (as of 2026-10-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/evaluation-of-uncertainty-aware-multi-software-ensembles-for-hippocampal-segment.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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