Medical Image Registration and Its Application in Retinal Images: A Review
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929287667384320 |
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| author | Nie, Qiushi Zhang, Xiaoqing Hu, Yan Gong, Mingdao Liu, Jiang |
| author_facet | Nie, Qiushi Zhang, Xiaoqing Hu, Yan Gong, Mingdao Liu, Jiang |
| contents | Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities. Although several surveys have reviewed the development of medical image registration, these surveys have not systematically summarized methodologies of existing medical image registration methods. To this end, we provide a comprehensive review of these methods from traditional and deep learning-based directions, aiming to help audiences understand the development of medical image registration quickly. In particular, we review recent advances in retinal image registration at the end of each section, which has not attracted much attention. Additionally, we also discuss the current challenges of retinal image registration and provide insights and prospects for future research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16502 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Medical Image Registration and Its Application in Retinal Images: A Review Nie, Qiushi Zhang, Xiaoqing Hu, Yan Gong, Mingdao Liu, Jiang Computer Vision and Pattern Recognition Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities. Although several surveys have reviewed the development of medical image registration, these surveys have not systematically summarized methodologies of existing medical image registration methods. To this end, we provide a comprehensive review of these methods from traditional and deep learning-based directions, aiming to help audiences understand the development of medical image registration quickly. In particular, we review recent advances in retinal image registration at the end of each section, which has not attracted much attention. Additionally, we also discuss the current challenges of retinal image registration and provide insights and prospects for future research. |
| title | Medical Image Registration and Its Application in Retinal Images: A Review |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2403.16502 |