A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images.

Ullah, Naeem; Khan, Mohammad Sohail; Khan, Javed Ali; Choi, Ahyoung; Anwar, Muhammad Shahid

Ullah, Naeem; Khan, Mohammad Sohail; Khan, Javed Ali; Choi, Ahyoung; Anwar, Muhammad Shahid.

Afiliación

Ullah N; Department of Software Engineering, University of Engineering and Technology, Taxila 47050, Pakistan.
Khan MS; Department of Computer Software Engineering, University of Engineering and Technology Mardan, Mardan 23200, Pakistan.
Khan JA; Department of Software Engineering, University of Science and Technology Bannu, Bannu 28100, Pakistan.
Choi A; Department of AI, Software Gachon University, Seongnem-si 13120, Korea.
Anwar MS; Department of AI, Software Gachon University, Seongnem-si 13120, Korea.

Sensors (Basel) ; 22(19)2022 Oct 06.

Article en En | MEDLINE | ID: mdl-36236674

Asunto(s)

Neoplasias Encefálicas; Aprendizaje Profundo; Algoritmos; Encéfalo/diagnóstico por imagen; Encéfalo/patología; Neoplasias Encefálicas/diagnóstico por imagen; Neoplasias Encefálicas/patología; Detección Precoz del Cáncer; Humanos; Imagen por Resonancia Magnética/métodos; Redes Neurales de la Computación

Palabras clave

MRI; TumorResNet; brain tumor detection; deep learning

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Encefálicas / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Guideline / Screening_studies Límite: Humans Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Pakistán

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