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Oncol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Accurate segmentation of liver tumors from 3D computed tomography (CT) volumes is essential for the clinical management of hepatocellular carcinoma (HCC), but remains challenging because of extreme lesion-scale variation, volumetric discontinuity across slices, and ambiguous tumor boundaries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We propose MemSAM-2.5D, a unified 2.5D segmentation framework built upon the MedSAM foundation model. The framework integrates a Hybrid Mamba-Adapter (HMA) for intra-slice multi-scale representation, a Z-axis State Flow (ZSF) module for continuous inter-slice dependency modeling, and a Confidence-Gated Prototype Memory (CGPM) module for uncertainty-aware boundary refinement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Extensive evaluations on MSD08, HCC-TACE-Seg, and WAW-TACE demonstrate that MemSAM-2.5D consistently outperforms representative CNN-based, Transformer-based, Mamba-based, and MedSAM-based baselines. The improvements are reflected not only in overlap-based metrics, but also in boundary-sensitive, lesion-level, and continuity-related measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These results suggest that coordinated modeling of multi-scale lesion variability, z-axis continuity, and boundary ambiguity provides an effective and transferable solution for clinically relevant HCC segmentation in CT volumes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fonc.2026.1850004","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T04:52:51Z","timestamp":1783486371000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["MemSAM-2.5D: overcoming volumetric discontinuity and boundary ambiguity for 3D liver tumor 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