Research on registration method for enface image using multi-feature fusion

• Published in: Physics in medicine & biology 2024-11, Vol.69 (21), p.215037
• Main Authors: Pan, Lingjiao, Cai, Zhongwang, Hu, Derong, Zhu, Weifang, Shi, Fei, Tao, Weige, Wu, Quanyu, Xiao, Shuyan, Chen, Xinjian
• Format: Article
• Language: English
• Subjects: combined features; coordinate simplification; CPD alignment; image processing; non-rigid alignment
• ISSN: 0031-9155; 1361-6560; 1361-6560
• DOI: 10.1088/1361-6560/ad87a5

The purpose of this work is to accurately and quickly register the OCT projection (enface) images at adjacent time points, and to solve the problem of interference caused by CNV lesions on the registration features. In this work, a multi-feature registration strategy was proposed, in which a combined feature (com-feature) containing 3D information, intersection information and SURF feature was designed. Firstly, the coordinates of all feature points were extracted as combined features, and then these feature coordinates were added to the initial vascular coordinate set simplified by the Douglas-Peucker algorithm as the point set for registration. Finally, the Coherent Point Drift (CPD) registration algorithm was used to register the enface coordinate point sets of adjacent time series. The newly designed features significantly improve the success rate of global registration of vascular networks in enface images, while the simplification step greatly improves the registration speed on the basis of preserving vascular features. The MSE, DSC and time complexity of the proposed method are 0.07993, 0.9693 and 42.7016s, respectively. CNV is a serious retinal disease in ophthalmology. The registration of OCT enface images at adjacent time points can timely monitor the progress of the disease and assist doctors in making diagnoses. The proposed method not only improves the accuracy of OCT enface image registration, but also significantly reduces the time complexity. It has good registration results in clinical routine and provides a more efficient method for clinical diagnosis and treatment.