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1. Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution

2. Deform-Mamba Network for MRI Super-Resolution

3. Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes

4. 3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes

5. End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks

6. A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods

7. Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation

8. Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review

9. Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning

10. End-to-End Autoencoding Architecture for the Simultaneous Generation of Medical Images and Corresponding Segmentation Masks

12. A novel adversarial learning strategy for medical image classification

13. Evidence fusion with contextual discounting for multi-modality medical image segmentation

14. Application of belief functions to medical image segmentation: A review

15. A Quantitative Comparison between Shannon and Tsallis Havrda Charvat Entropies Applied to Cancer Outcome Prediction

16. Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images

17. Lymphoma segmentation from 3D PET-CT images using a deep evidential network

18. Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images

19. Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities

20. A Tri-attention Fusion Guided Multi-modal Segmentation Network

21. AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics

23. Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation

24. Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities

25. Evidential segmentation of 3D PET/CT images

26. Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities

27. Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy

28. Deep Learning Based Radiomics to Predict Treatment Response Using Multi-datasets

29. Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT

30. 3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint

31. Belief function-based semi-supervised learning for brain tumor segmentation

32. Covid-19 classification with deep neural network and belief functions

34. A review: Deep learning for medical image segmentation using multi-modality fusion

35. An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism

36. Brain tumor segmentation with missing modalities via latent multi-source correlation representation

37. RADIOGAN: Deep Convolutional Conditional Generative adversarial Network To Generate PET Images

38. Weakly Supervised PET Tumor Detection Using Class Response

39. Deep Learning Based Radiomics to Predict Treatment Response Using Multi-datasets

41. A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation

50. Une v\'eritable approche $\ell_0$ pour l'apprentissage de dictionnaire

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