An approach to multimodal biomedical image registration utilizing particle swarm optimization

By Mark Paul Wachowiak, Renata Wachowiak-Smolíková, Yufeng Zheng, J. Zurada, Adel Said Elmaghraby. IEEE Transactions on Evolutionary Computation, 2004

425 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/5ff076516bf409b55bd958089e1f0ddd524ac3a6

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Comprehensive learning particle swarm optimizer for global optimization of multimodal functions (2006, background): “Since its introduction in 1995 by Kennedy and Eberhart [1], [2], PSO has attracted a high level of interest [4]–[7].”
Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration (2016, background): “Let two 3D point-sets X = { x i } , i = 1 , ..., N and Y = { y j } , j = 1 , ..., M , where x i , y j ∈ 3 are point coordinates, be the data point-set and the model point-set respectively.”
Particle Swarm Optimization With an Aging Leader and Challengers (2013, methodology): “As PSO is simple in concept and effective to explore global solutions for some hard problems, PSO has become one of the most popular optimization techniques and has been successfully applied in many application areas such as task assignment [3], power systems [4], [5], and biomedical image registrat”
Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives (2008, positive): “It has been applied to evolve weights and structure of neural networks [38–40], analyze human tremor [41], register 3Dto-3D biomedical image [42], play games [43], control reactive power and voltage [44, 45], pattern recognition [46], etc.”
A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications (2008, background): “Wachowiak et al. (2004) developed a bespoke PSO system, in which a third social influence was added, to optimize the global search element of biomedical image registration .”
Go-ICP: Solving 3D Registration Efficiently and Globally Optimally (2013, background): “particle swarm optimization [34] and particle filtering [32], to help the registration jump out of local minima.”
A review of multimodal image matching: Methods and applications (2021, methodology): “Several heuristic and metaheuristic methods, such as greedy [81,82] and evolutionary algorithms [83,84], are also investigated to explore a larger solution space, thus being able to handle a more general problem, but they cannot guarantee their optimal solutions.”
Survey of Medical Image Registration (2013, methodology): “Dividing RECT angles (DIRECT) is a global technique for linearly bounded problems and multidirectional search (MDS) is a recent local method [111].”
Analysis of the publications on the applications of particle swarm optimisation (2008, background): “Image analysis applications include iris recognition, fruit quality grading, face detection and recognition, image segmentation, synthetic aperture radar imaging, locating treatment planning landmarks in orthodontic x-ray images, image classification, inversion of ocean colour reflectance measuremen”
A Partial Intensity Invariant Feature Descriptor for Multimodal Retinal Image Registration (2010, neutral): “The area-based approaches [12]–[24] compare and match the intensity differences of an image pair under a similarity metric such as mutual information [19]–[22] and cross correlation [12], [15], and then apply an optimization technique [23], [24] to maximize”
Swarm Intelligence in Optimization (2008, methodology): “al [176] Floor planning Sun, Hsieh, Wang and Lin [166]”