Automatic Detection of Brain Tumor on Computed Tomography Images for Patients in the Intensive Care Unit

Patients in the intensive care unit require fast and efficient handling, including in-diagnosis service. The objectives of this study are to produce a computer-aided system so that it can help radiologists to classify the types of brain tumors suffered by patients quickly and accurately; to build ap...

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Detalles Bibliográficos
Autores principales: Fahmi, Fahmi, Apriyulida, Fitri, Nasution, Irina Kemala, Sawaluddin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378674/
https://www.ncbi.nlm.nih.gov/pubmed/32733660
http://dx.doi.org/10.1155/2020/2483285
Descripción
Sumario:Patients in the intensive care unit require fast and efficient handling, including in-diagnosis service. The objectives of this study are to produce a computer-aided system so that it can help radiologists to classify the types of brain tumors suffered by patients quickly and accurately; to build applications that can determine the location of brain tumors from CT scan images; and to get the results of the analysis of the system design. The combination of the zoning algorithm with Learning Vector Quantization can increase the speed of computing and can classify normal and abnormal brains with an average accuracy of 85%.

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