3D choroid neovascularization growth prediction with combined hyperelastic biomechanical model and reaction-diffusion model

Abstract

Choroid neovascularization (CNV) usually causes varying degrees of irreversible retinal degradation, central scotoma, metamorphopsia or permanent visual lose. If early prediction can be achieved, timely clinical treatment can be applied to prevent further deterioration. In this paper, a CNV growth prediction framework based on physiological structure revealed in noninvasive optical coherence tomography (OCT) images is proposed. The method consists of three steps: pre-processing, CNV growth modeling and prediction. For growth modeling, a new combination model is proposed. The hyperelastic biomechanical model and reaction-diffusion model with treatment factor are combined through mass effect. For parameter optimization, the genetic algorithm is applied. The proposed method was tested on a data set with 6 subjects, each with 12 longitudinal 3-D images. The experimental results showed that the average TPVF, FPVF and Dice coefficient of 80.0 ± 7.62%, 23.4 ± 8.36% and 78.9 ± 7.54% could be achieved, respectively.