Cross‐cumulative residual entropy‐based medical image registration via hybrid differential search algorithm

Abstract

Image registration is the process of overlaying images of the same scene taken at different times by different sensors from different viewpoints. The cross‐cumulative residual entropy (CCRE)‐based medical image registration could achieve a high precision and a strong robustness performance. However, the optimization problem formulated by CCRE consists of some local extrema, especially for noise images. In order to address these difficulties, this article proposes a new optimization algorithm named hybrid differential search algorithm (HDSA) to optimize CCRE. As HDSA consists of simple control parameters, it is independent of the initial searching point. In addition, HDSA ameliorated the search method and the iterative conditions. As a result, the optimization process is more stable and efficient. Image registration experiments of HDSA are performed and compared with the conventional differential search algorithm (DSA) and adaptive differential evolution with optional external archive (JADE). The results show that HDSA does not only overcome the difficulties of sticking in the local extrema but also enhances the precision of registration. It is effective, robust, and fast for both the single‐mode rigid medical image registration and the multispectral‐mode rigid medical image registration.

Normal vibration distribution search-based differential evolution algorithm for multimodal biomedical image registration

“…Scatter Search(SS) 4.Coral Reef Optimization(CRO) 5. CRO-SL Tme-consuming [ 46 ] HDSA MRI/MRI Rigid CCRE Brain No 1. Differential Evolution With Optional External Archive(JADE) 2.…”

“…Recently, with the development of multimodal medical image registration, various methods that use metaheuristic algorithms for optimization purposes have been proposed. As shown in Table 1 , optimization algorithms including the coral reef optimization algorithm with substrate layers (CRO-SL) [ 42 ], the dragonfly algorithm (DA) [ 43 ], the gray wolf optimizer (GWO) [ 44 ], biography-based optimization with elite learning (BBOEL), the hybrid differential search algorithm (HDSA) [ 46 ] and the united equilibrium optimizer (UEO) [ 47 ] are applied to intensity-based medical image registration. These algorithms have demonstrated their superiority over many of the other algorithms listed above.…”

A Machine-Learning-Based Medical Imaging Fast Recognition of Injury Mechanism for Athletes of Winter Sports

“…In Ma et al ( 34 ), an unsupervised deformable image registration network was proposed for 3D medical images. In Gui et al ( 35 ), the hybrid differential search algorithm was presented to optimize the cross-cumulative residual entropy algorithm for medical image registration.…”

Open pollution routing problem of logistics distribution in medical union based on differential search algorithm

“…Moreover, some researchers have applied DSA to solve some practical problems. Gui et al 25 proposed a hybrid differential search algorithm (HDSA) to optimize the medical image alignment problem and compared the effectiveness with the standard algorithm. Chu et al 26 advanced a new model of cross-training with learning and forgetting effects, and presented an adaptive DSA to solve the problem of worker assignment across multiple units.…”