1 INTRODUCTION
2 BACKGROUND
2.1 Hand-Crafted Approaches
2.2 CNN-based Methods
2.3 Transformers
3 MEDICAL IMAGE SEGMENTATION
3.1 Organ-Specific Segmentation
3.2 Multi-organ Segmentation
3.3 Discussion
4 MEDICAL IMAGE CLASSIFICATION
4.1 COVID-19 Diagnosis
4.2 Tumor Classification
4.3 Retinal Disease Classification
4.4 Discussion
5 MEDICAL IMAGE DETECTION
5.1 Discussion
6 MEDICAL IMAGE RECONSTRUCTION
6.1 Medical Image Enhancement
6.2 Medical Image Restoration
6.3 Discussion
7 MEDICAL IMAGE SYNTHESIS
7.1 Intra-Modality Approaches
7.2 Inter-Modality Approaches
7.3 Discussion
8 MEDICAL IMAGE REGISTRATION
8.1 Discussion
9 CLINICAL REPORT GENERATION
9.1 Reinforcement Learning Based Approaches
9.2 Supervised and Unsupervised Approaches
9.3 Discussion
10 OTHER APPLICATIONS
11 OPEN CHALLENGES AND FUTURE DIRECTIONS
11.1 Pre-training
11.2 Interpretability
11.3 Adversarial Robustness
11.4 ViTs for Medical Imaging on Edge Devices
11.5 Decentralized Medical Imaging Solutions using ViTs
11.6 Domain Adaptation and Out-of-Distribution Detection
12 DISCUSSION AND CONCLUSION