Trustworthy Multi-phase Liver Tumor Segmentation via Evidence-based Uncertainty

• URL: http://arxiv.org/abs/2305.05344v2
• Date: Tue, 20 Jun 2023 14:00:31 GMT
• Title: Trustworthy Multi-phase Liver Tumor Segmentation via Evidence-based Uncertainty
• Authors: Chuanfei Hu, Tianyi Xia, Ying Cui, Quchen Zou, Yuancheng Wang, Wenbo Xiao, Shenghong Ju, Xinde Li
• Abstract summary: Multi-phase liver tumor segmentation (MPLiTS)-based methods suffer from redundancy and weak interpretability. We propose a novel trustworthy multi-phase liver tumor segmentation (TMPLiTS) TMPLiTS is a unified framework jointly conducting segmentation and uncertainty estimation.
• Score: 6.631670005069929
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multi-phase liver contrast-enhanced computed tomography (CECT) images convey the complementary multi-phase information for liver tumor segmentation (LiTS), which are crucial to assist the diagnosis of liver cancer clinically. However, the performances of existing multi-phase liver tumor segmentation (MPLiTS)-based methods suffer from redundancy and weak interpretability, % of the fused result, resulting in the implicit unreliability of clinical applications. In this paper, we propose a novel trustworthy multi-phase liver tumor segmentation (TMPLiTS), which is a unified framework jointly conducting segmentation and uncertainty estimation. The trustworthy results could assist the clinicians to make a reliable diagnosis. Specifically, Dempster-Shafer Evidence Theory (DST) is introduced to parameterize the segmentation and uncertainty as evidence following Dirichlet distribution. The reliability of segmentation results among multi-phase CECT images is quantified explicitly. Meanwhile, a multi-expert mixture scheme (MEMS) is proposed to fuse the multi-phase evidences, which can guarantee the effect of fusion procedure based on theoretical analysis. Experimental results demonstrate the superiority of TMPLiTS compared with the state-of-the-art methods. Meanwhile, the robustness of TMPLiTS is verified, where the reliable performance can be guaranteed against the perturbations.

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