TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT
Abstract
Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly in low-resource settings across Africa and Asia where contrast agents are frequently unavailable. Progress has been limited by the absence of annotated NCCT benchmarks. Here we describe the TriALS challenge for automated liver lesion segmentation under contrast-limited conditions, supported by a multi-centre dataset of 150 cases with four-phase CT acquisitions (600 volumes) from Egyptian and Chinese institutions. Algorithms were evaluated on 70 cases from three institutions, including an independent external cohort. The top-performing method achieved a mean venous-phase Dice of 0.754, consistent with human-level performance, yet dropped to 0.57 on NCCT. On external validation, the leading method outperformed off-the-shelf models by up to 28% in Dice on NCCT. Algorithm performance was most strongly predicted by training data scale and pre-training strategy. A cross-year comparison exposed a persistent perceptual barrier on NCCT that scaling pre-training alone cannot overcome. Data, annotations, and code are available at https://github.com/xmed-lab/TriALS.
Keywords
Cite
@article{arxiv.2605.16572,
title = {TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT},
author = {Marawan Elbatel and Mohamed Ghonim and Jiaji Mao and Zhuosheng Lin and Katharina Eckstein and Andrés Martínez Mora and Jonathan Deissler and Maximilian Rokuss and Constantin Ulrich and Zdravko Marinov and Wenhui Deng and Baoxun Li and Huijun Hu and Jun Shen and Mohanad Ghonim and Khadiga Omar Nassar and Mariam Elbakry and Menna Dyab and Amr Muhammad Abdo Salem and Nouran Elghitany and Noha Elghitany and Yi Qin and Xuanqi Huang and Haonan Wang and Shao-Woo Yen and Ahmed Elghamry Saba and Salma Ahmad and Xinyan Fang and Jiahao Zhang and Xiaodi Wang and Xinghua Ma and Gongning Luo and Jessica C. Delmoral and João Manuel R. S. Tavares and Ankan Deria and Adinath Dukre and Yutong Xie and Imran Razzak and Dongwook Kim and Matthew Choi and Hanxiao Zhang and Minghui Zhang and Xin You and Abdul Qayyum and Steven A. Niederer and Moona Mazher and Rachika E. Hamadache and Ricardo Montoya-del-Angel and Robert Martí and Xavier Lladó and Toufiq Musah and Livingstone Eli Ayivor and Enrique Almar-Munoz and Agnes Mayr and Kaouther Mouheb and Esther E. Bron and Stefan Klein and Ahmed Abouelhoda and Amira Adel and Susan Adil Ali and Rainer Stiefelhagen and Klaus H. Maier-Hein and Fabian Isensee and Aya Yassin and Xiaomeng Li},
journal= {arXiv preprint arXiv:2605.16572},
year = {2026}
}
Comments
TriALS challenge paper across MICCAI 2024 and 2025; data and code at https://github.com/xmed-lab/TriALS