A review on medical image applications based on deep learning techniques

Basit Öğe Kaydı
dc.contributor.authorAbdulwahhab, Ali H.
dc.contributor.authorMahmood, Noof T.
dc.contributor.authorMohammed, Ali Abdulwahhab
dc.contributor.authorMyderrizi, Indrit
dc.contributor.authorAl-Jumaili, Mustafa Hamid
dc.date.accessioned2024-09-02T06:58:43Z
dc.date.available2024-09-02T06:58:43Z
dc.date.issued2024en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractThe integration of deep learning in medical image analysis is a transformative leap in healthcare, impacting diagnosis and treatment significantly. This scholarly review explores deep learning’s applications, revealing limitations in traditional methods while showcasing its potential. It delves into tasks like segmentation, classification, and enhancement, highlighting the pivotal roles of Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). Specific applications, like brain tumor segmentation and COVID-19 diagnosis, are deeply analyzed using datasets like NIH Clinical Center’s Chest X-ray dataset and BraTS dataset, proving invaluable for model training. Emphasizing high-quality datasets, especially in chest X-rays and cancer imaging, the article underscores their relevance in diverse medical imaging applications. Additionally, it stresses the managerial implications in healthcare organizations, emphasizing data quality and collaborative partnerships between medical practitioners and data scientists. This review article illuminates deep learning’s expansive potential in medical image analysis, a catalyst for advancing healthcare diagnostics and treatments.en_US
dc.identifier.citationAbdulwahhab, A. H., Mahmood, N. T., Mohammed, A. A., Myderrizi, I., Al-Jumaili, M. H. (2024). A review on medical image applications based on deep learning techniques. Journal of Image and Graphics(United Kingdom), 12(3), 215-227. 10.18178/JOIG.12.3.215-227en_US
dc.identifier.endpage227en_US
dc.identifier.issn2301-3699
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85201556291
dc.identifier.scopusqualityQ2
dc.identifier.startpage215en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/4814
dc.identifier.volume12en_US
dc.indekslendigikaynakScopus
dc.institutionauthorAbdulwahhab, Ali H.
dc.institutionauthorMohammed, Ali Abdulwahhab
dc.institutionauthorAl-Jumaili, Mustafa Hamid
dc.language.isoen
dc.publisherUniversity of Portsmouthen_US
dc.relation.ispartofJournal of Image and Graphics(United Kingdom)
dc.relation.isversionof10.18178/JOIG.12.3.215-227en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDeep learningen_US
dc.subjectHigh-quality medical image datasetsen_US
dc.subjectMachine learningen_US
dc.subjectMedical image analysisen_US
dc.titleA review on medical image applications based on deep learning techniques
dc.typeArticle

Dosyalar

Lisans paketi
Listeleniyor 1 - 1 / 1
[ X ]
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu