2D Shape-based Fluorescence Molecular Tomography Through Hybrid Genetic Algorithm Based Optimization
WANG Dai-fa
WANG Ling
FAN Yu-bo
LI De-yu
摘要：Fluorescence molecular tomography (FMT) aims at tomographically re-solving the fluorescent targets deeply inside small animal based on transmission boundary measurements. The image reconstruction of FMT is known to be highly ill-posed, due to the highly scattering nature of biological tissue. Hence, prior information is usually required for successful reconstruction. In this paper, a novel reconstruction method incorporating shape priors is proposed for 2D FMT. The fluorescent targets were assumed of round shape, which was practically appropriate for approximating various shapes inside diffusive medium. Compared to the traditional pixel based reconstruction, the number of unknowns was greatly reduced to a few control parameters of round shapes. A hybrid genetic algorithm was proposed to recover the shape parameters. The numerical experiments showed that the proposed method significantly improves the imaging accuracy, offering clearer target boundaries and better resolution. Comparison results also demonstrated that the hybridization of genetic algorithm and Newton-type search was pivotal and important for robustly finding the globally optimal shape parameters.
机标关键词：hybrid genetic algorithmshape parametersnumerical experimentsimage reconstructionbiological tissueround shapenature of
分类号：R318.51(医用一般科学)
论文发表日期：2016-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：7( 107-113 )
英文信息