Optimization of Modified Adaptive Neuro-Fuzzy Inference System (MANFIS) with Artificial Bee Colony (ABC) Algorithm for Classification of Bone Cancer

Bone cancer is the uneven progress of tissue in the bone. This illness can be primary or secondary. Primary bone sarcoma grows from the cells of the bone, while secondary bone cancer begins from different body organs and then extends to the bone cells. The cure of fillet cancer depends on tumor loca...

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Vydané v:2022 Second International Conference on Distributed Computing and High Performance Computing (DCHPC) s. 78 - 81
Hlavní autori: Lefteh, Ali, Houshmand, Monireh, Khorrampanah, Mahsa, Smaisim, Ghassan Fadhil
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 02.03.2022
Predmet:
Adaptive systems
ANFIS
Artificial bee colony algorithm
Bone Cancer
Bones
Clustering algorithms
Feature extraction
Fuzzy C-mean Clustering
Inference algorithms
Meta-Heuristic Algorithms
MRI
Productivity
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Abstract Bone cancer is the uneven progress of tissue in the bone. This illness can be primary or secondary. Primary bone sarcoma grows from the cells of the bone, while secondary bone cancer begins from different body organs and then extends to the bone cells. The cure of fillet cancer depends on tumor localization, size, and other factors. Therefore, initial recognition and category of bone cancer have become required to therapy the patient. In this procedure, a technique proposed for the glory of bone cancer employing fuzzy C-mean clustering also uses Modified Adaptive Neuro-Fuzzy Inference System (MANFIS) with Artificial Bee Colony algorithm to classify benign and malignant bone cancer. The experiments illustrate that the suggested method has a high accuracy of 96.67% and offers enhanced productivity than the systems in bone MR images.
AbstractList Bone cancer is the uneven progress of tissue in the bone. This illness can be primary or secondary. Primary bone sarcoma grows from the cells of the bone, while secondary bone cancer begins from different body organs and then extends to the bone cells. The cure of fillet cancer depends on tumor localization, size, and other factors. Therefore, initial recognition and category of bone cancer have become required to therapy the patient. In this procedure, a technique proposed for the glory of bone cancer employing fuzzy C-mean clustering also uses Modified Adaptive Neuro-Fuzzy Inference System (MANFIS) with Artificial Bee Colony algorithm to classify benign and malignant bone cancer. The experiments illustrate that the suggested method has a high accuracy of 96.67% and offers enhanced productivity than the systems in bone MR images.
Author Khorrampanah, Mahsa
Smaisim, Ghassan Fadhil
Houshmand, Monireh
Lefteh, Ali
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  givenname: Ali
  surname: Lefteh
  fullname: Lefteh, Ali
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  organization: Imam Reza International University,faculty of electrical engineering,Mashhad,Iran
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  givenname: Monireh
  surname: Houshmand
  fullname: Houshmand, Monireh
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  givenname: Mahsa
  surname: Khorrampanah
  fullname: Khorrampanah, Mahsa
  email: khorrampanah@tabrizu.ac.ir
  organization: University of Tabriz,Faculty of electrical and computer engineering,Tabriz,Iran
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  givenname: Ghassan Fadhil
  surname: Smaisim
  fullname: Smaisim, Ghassan Fadhil
  email: Ghassan.smaisim@uokufa.edu.iq
  organization: University of Kufa Nanotechnology and Advanced Materials Research Unit (NAMRU), University of Kufa,Faculty of Engineering,Department of Mechanical Engineering,Kufa,Iraq
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Snippet Bone cancer is the uneven progress of tissue in the bone. This illness can be primary or secondary. Primary bone sarcoma grows from the cells of the bone,...
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StartPage 78
SubjectTerms Adaptive systems
ANFIS
Artificial bee colony algorithm
Bone Cancer
Bones
Clustering algorithms
Feature extraction
Fuzzy C-mean Clustering
Inference algorithms
Meta-Heuristic Algorithms
MRI
Productivity
Title Optimization of Modified Adaptive Neuro-Fuzzy Inference System (MANFIS) with Artificial Bee Colony (ABC) Algorithm for Classification of Bone Cancer
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