Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images.

breast cancer detection computer-aided diagnosis supervised learning texture features ultrasound imaging wavelet neural network

Journal

Frontiers in oncology
ISSN: 2234-943X
Titre abrégé: Front Oncol
Pays: Switzerland
ID NLM: 101568867

Informations de publication

Date de publication:
2022
Historique:
received: 12 12 2021
accepted: 14 03 2022
entrez: 30 6 2022
pubmed: 1 7 2022
medline: 1 7 2022
Statut: epublish

Résumé

Breast cancer is the most menacing cancer among all types of cancer in women around the globe. Early diagnosis is the only way to increase the treatment options which then decreases the death rate and increases the chance of survival in patients. However, it is a challenging task to differentiate abnormal breast tissues from normal tissues because of their structure and unclear boundaries. Therefore, early and accurate diagnosis and classification of breast lesions into malignant or benign lesions is an active domain of research. Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data

Identifiants

pubmed: 35769710
doi: 10.3389/fonc.2022.834028
pmc: PMC9234296
doi:

Types de publication

Journal Article

Langues

eng

Pagination

834028

Informations de copyright

Copyright © 2022 A, M, Bourouis, Band, Mosavi, Agrawal and Hamdi.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Ahila A (A)

Department of Electronics and Communication Engineering, Sethu Institute of Technology, Kariapatti, India.

Poongodi M (P)

College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Sami Bourouis (S)

Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia.

Shahab S Band (SS)

Future Technology Research Center, College of Future, National Yunlin University of Science and Technology, Douliou, Taiwan.

Amir Mosavi (A)

John von Neumann Faculty of Informatics, Obuda University, Budapest, Hungary.

Shweta Agrawal (S)

IAC, SAGE University, Indore, India.

Mounir Hamdi (M)

College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

Classifications MeSH