ArticleBiomedical optics express2020
Multimodal affine registration for ICGA and MCSL fundus images of high myopia.
Article in Biomedical optics express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Ultrawidefield-to-Conventional Fundus Image Translation with Scaled Feature Registration and Distorted Vessel Correction.Bioengineering (Basel, Switzerland) · 2025Article
- The role of artificial intelligence in the diagnosis of diabetic retinopathy through retinal lesion features: a narrative review.Quantitative imaging in medicine and surgery · 2025Review
- Choroidal vascular changes in early-stage myopic maculopathy from deep learning choroidal analysis: a hospital-based SS-OCT study.Eye and vision (London, England) · 2024Article
- MEMO: dataset and methods for robust multimodal retinal image registration with large or small vessel density differences.Biomedical optics express · 2024Article
- Deep learning-based affine medical image registration for multimodal minimal-invasive image-guided interventions - A comparative study on generalizability.Zeitschrift fur medizinische Physik · 2024Article
- Joint keypoint detection and description network for color fundus image registration.Quantitative imaging in medicine and surgery · 2023Article
- Chronological Registration of OCT and Autofluorescence Findings in CSCR: Two Distinct Patterns in Disease Course.Diagnostics (Basel, Switzerland) · 2022Article
- Two-Step Registration on Multi-Modal Retinal Images via Deep Neural Networks.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2022Article
- Perspective Distortion Correction for Multi-Modal Registration between Ultra-Widefield and Narrow-Angle Retinal Images.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The registration between indocyanine green angiography (ICGA) and multi-color scanning laser (MCSL) imaging fundus images is vital for the joint linear lesion segmentation in ICGA and MCSL and the evaluation whether MCSL can replace ICGA as a non-invasive diagnosis for linear lesion. To our best knowledge, there are no studies focusing on the image registration between these two modalities. In this paper, we propose a framework based on convolutional neural networks for the multimodal affine registration between ICGA and MCSL images, which contains two parts: coarse registration stage and fine registration stage. In the coarse registration stage, the optic disc is segmented and its centroid is used as a matching point to perform coarse registration. The fine registration stage regresses affine parameters directly using jointly supervised and weakly-supervised loss function. Experimental results show the effectiveness of the proposed method, which lays a sound foundation for further evaluation of non-invasive diagnosis of linear lesion based on MCSL.
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Registered trials
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