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1. Application of clustering strategy for automatic segmentation of tissue regions in mass spectrometry imaging.

2. A joint brain extraction and image quality assessment framework for fetal brain MRI slices.

3. Developing an AI-empowered head-only ultra-high-performance gradient MRI system for high spatiotemporal neuroimaging.

4. Cellular nucleus image-based smarter microscope system for single cell analysis.

5. Neural blind deconvolution for deblurring and supersampling PSMA PET.

6. A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions.

7. Deep learning-based image annotation for leukocyte segmentation and classification of blood cell morphology.

8. Photophysical image analysis: Unsupervised probabilistic thresholding for images from electron-multiplying charge-coupled devices.

9. AI and augmented reality for 3D Indian dance pose reconstruction cultural revival.

10. Registered multi-device/staining histology image dataset for domain-agnostic machine learning models.

11. Cross noise level PET denoising with continuous adversarial domain generalization.

12. IWNeXt: an image-wavelet domain ConvNeXt-based network for self-supervised multi-contrast MRI reconstruction.

13. XTransCT: ultra-fast volumetric CT reconstruction using two orthogonal x-ray projections for image-guided radiation therapy via a transformer network.

14. Hybrid-supervised deep learning for domain transfer 3D protoacoustic image reconstruction.

15. Hierarchical decomposed dual-domain deep learning for sparse-view CT reconstruction.

16. Semi-supervised iterative adaptive network for low-dose CT sinogram recovery.

17. Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

18. A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images.

19. Spectrum learning for super-resolution tomographic reconstruction.

20. Establishing ground truth of polyp size, morphology, and volume using three-dimensional scanning.

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