Author

Mithat Gonen

2 papers indexed here

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Preprint Sep 2026

Spectral Adapters for Segment Anything Model-based Segmentation of Colorectal Liver Metastases in Computed Tomography

Accurate segmentation of colorectal liver metastases (CRLM) in contrast-enhanced computed tomography (CT) is important for response assessment, surgical planning, and follow-up. We propose two parameter-efficient spectral adapters for the Segment Anything Model (SAM): the Directional Spectral Adapter (DiSECT) and Spect...

R. Mojtahedi, Mohammad Hamghalam, Jacob J. Peoples et al. · 0 citations

Open access Jul 2026

Improving preoperative risk stratification in colorectal liver metastases: a multi-institutional evaluation of multimodal prediction models.

Reliable prognostic models of death or liver recurrence following resection of colorectal liver metastases are critical to stratify patients for treatment. The study aimed to develop models incorporating clinical and imaging data into multimodal preoperative prediction models of hepatic disease-free survival and overal...

Kaitlyn Kobayashi, R. Mojtahedi, E. C. Bunker et al. · Scientific Reports · 0 citations