snmjournals.org

End-to-End PET/CT Interpretation and Quantification with an LLM-Orchestrated AI Agent: A Real-World Pilot Study

Journal of Nuclear Medicine June 2026, jnumed.126.272362; DOI: https://doi.org/10.2967/jnumed.126.272362 This retrospective single-center study used clinical PET/CT ...
The Lancet

Development and validation of a deep learning-based framework for automated lung CT segmentation and acute respiratory distress syndrome prediction: a multicenter cohort study

aDepartment of Critical Care Medicine, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China bDepartment of Critical Care Medicine, Shanghai Sixth People's Hospital ...
GitHub

ProtoSAM - One shot segmentation with foundational models

Link to our paper here. This work is the successor of DINOv2-based-Self-Supervised-Learning (Link to Paper). This work introduces a new framework, ProtoSAM, for one-shot image segmentation. It ...
Frontiers

NephroNet: a calibration-aware, patient-disjoint benchmark for multiclass kidney CT classification with a compact depthwise-separable CNN

Computed tomography (CT) remains the primary cross-sectional modality for evaluating kidney pathology across three clinically salient tasks: (i) characterization of solid renal masses (benign vs.
Frontiers

Lesion feature enhancement and boundary-aware fusion for pulmonary embolism recognition on CT images

Artificial Intelligence-Assisted Medical Imaging Solutions for Integrating Pathology and Radiology Automated Systems - Volume III ...
GitHub

RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translation

Official research codebase for “RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translation”. file_dataset/ trainA/ # domain A, e.g., CBCT slices xxx_0001.nii.gz xxx_0002.nii.gz trainB ...