Applying a radiomics-based CAD scheme to classify between malignant and benign pancreatic tumors using CT images.

Gai, Tiancheng; Thai, Theresa; Jones, Meredith; Jo, Javier; Zheng, Bin

Gai, Tiancheng; Thai, Theresa; Jones, Meredith; Jo, Javier; Zheng, Bin.

Afiliación

Gai T; School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA.
Thai T; Department of Radiological Sciences, University of Oklahoma Health Science Center, Oklahoma City, OK, USA.
Jones M; Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA.
Jo J; School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA.
Zheng B; School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA.

J Xray Sci Technol ; 30(2): 377-388, 2022.

Article en En | MEDLINE | ID: mdl-35095015

Asunto(s)

Diagnóstico por Computador; Neoplasias Pancreáticas; Diagnóstico por Computador/métodos; Humanos; Neoplasias Pancreáticas/diagnóstico por imagen; Curva ROC; Estudios Retrospectivos; Máquina de Vectores de Soporte; Tomografía Computarizada por Rayos X

Palabras clave

Pancreatic cancer detection; classification of pancreatic tumor; computer-aided diagnosis (CAD); image segmentation using deep learning model; support vector machine

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias Pancreáticas / Diagnóstico por Computador Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: J Xray Sci Technol Asunto de la revista: RADIOLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

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