Multimodal Registration of Retinal Images Using Domain-Specific Landmarks and Vessel Enhancement
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Abstract (arXiv)
The analysis of different image modalities is frequently performed in ophthalmology as it provides complementary information for the diagnosis and follow-up of relevant diseases, like hypertension or diabetes. This work presents a hybrid method for the multimodal registration of color fundus retinography and fluorescein angiography. The proposed method combines a feature-based approach, using domain-specific landmarks, with an intensity-based approach that employs a domain-adapted similarity metric. The methodology is tested on a dataset of 59 image pairs containing both healthy and pathological cases. The results show a satisfactory performance of the proposed combined approach in this multimodal scenario, improving the registration accuracy achieved by the feature-based and the intensity-based approaches.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Mar 2018.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 2.
4 papers.
- 2021Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registrationcited by 4
- 2023MEMO: Dataset and Methods for Robust Multimodal Retinal Image Registration with Large or Small Vessel Density Differencescited by 3
- 2024ConKeD: Multiview contrastive descriptor learning for keypoint-based retinal image registrationcited by 3
- 2024Medical Image Registration and Its Application in Retinal Images: A Reviewcited by 3
- 2024Medical Image Registration and Its Application in Retinal Images: A Review25 Mar 2024
- 2024ConKeD: Multiview contrastive descriptor learning for keypoint-based retinal image registration11 Jan 2024
- 2023MEMO: Dataset and Methods for Robust Multimodal Retinal Image Registration with Large or Small Vessel Density Differences25 Sep 2023
- 2021Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration6 Sep 2021