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The cancer imaging archive (TCIA): Maintaining and operating a public information repository

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it

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2026 2 2025 2

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representative citing papers

SAMRI: Segment Any MRI

eess.IV · 2025-10-30 · conditional · novelty 6.0

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.

RA-CMF: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction

cs.CV · 2026-04-28 · unverdicted · novelty 5.0

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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Showing 4 of 4 citing papers.

  • SAMRI: Segment Any MRI eess.IV · 2025-10-30 · conditional · none · ref 65

    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.

  • Deep Learning for MRI Slice Interpolation: The Critical Role of Problem Formulation eess.IV · 2026-05-15 · unverdicted · none · ref 1

    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: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction cs.CV · 2026-04-28 · unverdicted · none · ref 37

    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.

  • In search of truth: Evaluating concordance of AI-based anatomy segmentation models eess.IV · 2025-12-17 · unverdicted · none · ref 38

    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.