Skeletal scintigraphy image enhancement based neutrosophic sets and salp swarm algorithm.
Recently, several schemes are proposed for enhancing the dark regions of the skeletal scintigraphy image. Nevertheless, most of them are flawed by some performance problems. This paper presents an adaptive scheme based on Salp Swarm algorithm (SSA) and a neutrosophic set (NS) under multi-criteria to...
| Publicado en: | Artificial Intelligence in Medicine Vol. 109 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Sep2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146612905&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 146612905 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09333657 3HY jtl: Artificial Intelligence in Medicine issn: 09333657 maglogo: N pubinfo: dt: Sep2020 vid: 109 pid: 1004 pub: Elsevier B.V. artinfo: ui: 146612905 146612905 NLM34756218 10.1016/j.artmed.2020.101953 NLM34756218 146612905 ppct: 1 formats: tig: atl: Skeletal scintigraphy image enhancement based neutrosophic sets and salp swarm algorithm. aug: au: Nasef, Mohammed M. Eid, Fatma T. Sauber, Amr M. affil: Mathematics and Computer Science Department, Faculty of Science, Menoufia University, 32511, Egypt sug: subj: Image Enhancement Algorithms Radionuclide Imaging Ferrans and Powers Quality of Life Index ab: Recently, several schemes are proposed for enhancing the dark regions of the skeletal scintigraphy image. Nevertheless, most of them are flawed by some performance problems. This paper presents an adaptive scheme based on Salp Swarm algorithm (SSA) and a neutrosophic set (NS) under multi-criteria to enhance the dark regions of the skeletal scintigraphy image efficiently. Enhancing the dark regions is first converted into an optimization problem. The SSA algorithm is used to find the best improvement for each image separately, and then the neutrosophic algorithm is used to find similarity score to each image with adaptive weight coefficients obtained by the SSA algorithm. The proposed algorithm is applied to an Egyptian medical dataset collected from Menoufia University Hospital and it is a no-reference image. The experiments are done using 3 different resolutions 512*512, 256*256, and 128*128 and compared with Gamma Correction, the NS algorithm and the local enhance algorithm. The results demonstrate that the proposed algorithm achieves superior performance in almost criteria fitness function, entropy, eumber of edges, nNaturalness image quality Evaluator, sharpness, sharpness index, and contrast-distorted images using contrast enhancement. The results showed the idea of integration between the falsity membership of the neutrosophic set and the Salp swarm algorithm can be used to Skeletal Scintigraphy enhancement. This paper proved that it can depend on falsity membership of the neutrosophic set in the Image Enhancement field. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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