This data-centric AI repository implements a robust deep learning method (LFBNet) for fully automated tumor segmentation in whole-body [18]F-FDG PET/CT images.
This repository employs a deep-learning method for the automated segmentation of total metabolic tumor volume (TMTV) in whole-body [18]F-FDG PET/CT images, with an emphasis on multi-center generalizability.
nnU-Net-based Lymphoma Total Metabolic Tumor Volume Segmentation
Free, open-source oncology clinical decision support: a deterministic, source-cited rule engine drafts two treatment plans for a clinician to verify — no LLM picks the regimen. Runs offline + as an MCP server for Claude/Cursor. Not a medical device.
Automated Deauville Score computation from PET/CT images
Personalized lymphoma therapy design with Gemma 4, AlphaFold, RFdiffusion. Kaggle Gemma 4 Good Hackathon submission.
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