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
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
834028Informations 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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