Image registration literature review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging MRI , computed tomography CT , and ultrasound and major anatomical structures of interest ventricles, atria, and vessels. In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches scarcity of labels, model generalizability across different domains, interpretability and suggest potential directions for future research. About The number is still increasing annually.
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Medical image registration: a review

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Vascular Image Registration Techniques: A Living Review

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Image registration

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