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cs.CV2026
Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT
Ramtin Mojtahedi, Mohammad Hamghalam, Jacob J. Peoples +2
We evaluated parameter-efficient fine-tuning (PEFT) of the Segment Anything Model (SAM) for liver tumor segmentation in abdominal CT of colorectal liver metastases. We compared Low…
cs.CV2026
Spectral Adapters for Segment Anything Model-based Segmentation of Colorectal Liver Metastases in Computed Tomography
Ramtin Mojtahedi, Mohammad Hamghalam, Jacob J. Peoples +6
Accurate segmentation of colorectal liver metastases (CRLM) in contrast-enhanced computed tomography (CT) is important for response assessment, surgical planning, and follow-up. We…