A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer.

ABSTRACT: Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with cancer. Accurate identification and quantification are crucial for effective patient management, including precise diagnosis, prognosis, and therapy evaluation. We present SALSA (system for automatic liver tumor segmentation and detection), a fully automated tool for liver tumor detection and delineation. Developed on 1,598 computed tomography (CT) scans and 4,908 liver tumors, SALSA demonstrates superior accuracy in tumor identification and volume quantification, outperforming state-of-the-art models and inter-reader agreement among expert radiologists. SALSA achieves a patient-wise detection precision of 99.65%, and 81.72% at lesion level, in the external validation cohorts. Additionally, it e

SUBMITTER: Balaguer-Montero M 

PROVIDER: S-EPMC12047525 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature