A Biomedical Image Segmentation Approach Using Fractional Order Darwinian Particle Swarm Optimization and Thresholding

Chakraborty, Shouvik; Mali, Kalyani; Banerjee, Arghasree; Bhattacharjee, Mayukh

doi:10.1007/978-981-15-9433-5_29

Cited by 7 publications

(3 citation statements)

References 26 publications

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“…For example, the frequency response of FIR and IIR filters can be approximated to the frequency response of the fractional operator. These methods can be used to implement the fractional order operator needed for different systems, such as image processing [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

High Performance Fractional Anisotropic Diffusion Filter forPortable Applications

AbdAlRahman¹,

Al-Atabany²,

Soltan³

et al. 2023

Preprint

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Anisotropic diffusion is one of the most effective methods used in image processing. It can be used to eliminate the small textures of an imagewhile preserving its significant edges. In this paper,a new anisotropic diffusion filter is proposed based on a fractional calculus kernel rather than an integer kernel to improve the overall performance of the filter. Integer and fractional anisotropic filters are implementedusing the Genesys-2 FPGA kit to utilize the efficiency of parallelism in FPGAs. Integer and fractional anisotropic filters are tested against the achievable PSNR value vs the number of iterations. The proposed fractional anisotropic filter has a better PSNR value using a smaller number of iterations, reducing the power and area compared to integer anisotropic filter.The proposed filter can be used in image smoothing,edge detection, image segmentation, image denoisingand cartooning. In addition, the proposed filter will save the power of applications with power constraints, such as portable devices, as it requires fewer iterations than integer anisotropic filters. The proposed filter reduces the required power consumption by 58.2%.

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Section: Introductionmentioning

confidence: 99%

High Performance Fractional Anisotropic Diffusion Filter forPortable Applications

AbdAlRahman¹,

Al-Atabany²,

Soltan³

et al. 2023

Preprint

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“…Still, literature on supervised learning-based COVID-19 detection using CT or X-Ray images is growing significantly. It can also be observed from the present state-of-the-art literature, that the unsupervised approaches are not investigated rigorously even though they can be quite helpful on various occasions [29] – [31] . Motivated from this, an image analysis process is proposed in this article that is not dependent on any pre-labeled data.…”

Section: Introductionmentioning

confidence: 99%

“…The incorporation of the concept superpixel renders reduction of computational overhead and helps in providing an efficient way of representing spatial information. The flower pollination algorithm developed by Yang [39] is successfully applied to solve various problems [40] like various other metaheuristics [31] , [41] . For the sake of conciseness of the article, the authors have refrained themselves from illustrating this approach in detail with appropriate citations added for further references.…”

Section: Introductionmentioning

confidence: 99%

An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 From Radiological Images

Ding

Chakraborty

Mali

et al. 2022

IEEE Trans. Fuzzy Syst.

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A global pandemic scenario is witnessed worldwide owing to the menace of the rapid outbreak of the deadly COVID-19 virus. To save mankind from this apocalyptic onslaught, it is essential to curb the fast spreading of this dreadful virus. Moreover, the absence of specialized drugs has made the scenario even more badly and thus an early-stage adoption of necessary precautionary measures would provide requisite supportive treatment for its prevention. The prime objective of this article is to use radiological images as a tool to help in early diagnosis. The interval type 2 fuzzy clustering is blended with the concept of superpixels, and metaheuristics to efficiently segment the radiological images. Despite noise sensitivity of watershed-based approach, it is adopted for superpixel computation owing to its simplicity where the noise problem is handled by the important edge information of the gradient image is preserved with the help of morphological opening and closing based reconstruction operations. The traditional objective function of the fuzzy cmeans clustering algorithm is modified to incorporate the spatial information from the neighboring superpixel-based local window. The computational overhead associated with the processing of a huge amount of spatial information is reduced by incorporating the concept of superpixels and the optimal clusters are determined by a modified version of the flower pollination algorithm. Although the proposed approach performs well but should not be considered as an alternative to gold standard detection tests of COVID-19. Experimental results are found to be promising enough to deploy this approach for real-life applications.

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A multilevel biomedical image thresholding approach using the chaotic modified cuckoo search

Chakraborty,

Mali

2023

Soft Comput

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A Biomedical Image Segmentation Approach Using Fractional Order Darwinian Particle Swarm Optimization and Thresholding

Cited by 7 publications

References 26 publications

High Performance Fractional Anisotropic Diffusion Filter forPortable Applications

High Performance Fractional Anisotropic Diffusion Filter forPortable Applications

An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 From Radiological Images

A multilevel biomedical image thresholding approach using the chaotic modified cuckoo search

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