A foveated imaging geometry CT (FIGCT) with mostly low-res detectors and a seeded diffusion model (DPFSR) enables global high-resolution CT reconstruction from limited high-res data.
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
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SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.
Reformulating the input to adjacent slices for deep learning MRI interpolation yields 58% SSIM gains and 10.1% improvement over linear baseline, with problem formulation outweighing architecture choice.
RA-CMF integrates conditional MeanFlow for trajectory-based image enhancement with an RL-driven policy for tile-wise adaptive refinement budgets, achieving average PSNR of 34.23 and SSIM of 0.95 on CT images with strong tumor ROI radiomic feature consistency.
A harmonization framework enables comparison of six AI segmentation models on 31 structures in NLST CT scans, revealing strong agreement for lungs but invalid outputs for some vertebrae and ribs.
citing papers explorer
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Foveated-Imaging Geometry CT Architecture and Seeded Diffusion Model Enabling Global Super-Resolution Reconstruction
A foveated imaging geometry CT (FIGCT) with mostly low-res detectors and a seeded diffusion model (DPFSR) enables global high-resolution CT reconstruction from limited high-res data.
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SAMRI: Segment Any MRI
SAMRI fine-tunes only the mask decoder of SAM on 1.1 million MRI slices from 30 datasets to reach mean DSC 0.87 on 47 targets and strong zero-shot performance.
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Deep Learning for MRI Slice Interpolation: The Critical Role of Problem Formulation
Reformulating the input to adjacent slices for deep learning MRI interpolation yields 58% SSIM gains and 10.1% improvement over linear baseline, with problem formulation outweighing architecture choice.
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RA-CMF: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction
RA-CMF integrates conditional MeanFlow for trajectory-based image enhancement with an RL-driven policy for tile-wise adaptive refinement budgets, achieving average PSNR of 34.23 and SSIM of 0.95 on CT images with strong tumor ROI radiomic feature consistency.
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In search of truth: Evaluating concordance of AI-based anatomy segmentation models
A harmonization framework enables comparison of six AI segmentation models on 31 structures in NLST CT scans, revealing strong agreement for lungs but invalid outputs for some vertebrae and ribs.