Abstract
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%.
Highlights
Patients in the intensive care unit require fast and efficient handling, including in-diagnosis service. e development of technological systems in the medical world is proliferating
Detection of brain tumors has an essential role in the field of biomedical application in terms of diagnosis of medical image records. e importance of identifying brain tumors has increased in the recent years. e brain tumor classification was developed to help medical staff diagnose the disease
E objectives 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 Computed Tomography (CT) scan images, and to get the results of the analysis of the system design. e benefits obtained from this study are to help radiologists to diagnose the types of brain tumors suffered by patients quickly and accurately, especially patients in the intensive care unit, and it becomes one of the references for researchers who focus on computer vision technology in the medical field
Summary
Patients in the intensive care unit require fast and efficient handling, including in-diagnosis service. e development of technological systems in the medical world is proliferating. Preprocessing is part of processing an image before feature extraction is performed to determine an area or object. E objectives 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. E benefits obtained from this study are to help radiologists to diagnose the types of brain tumors suffered by patients quickly and accurately, especially patients in the intensive care unit, and it becomes one of the references for researchers who focus on computer vision technology in the medical field E objectives 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. e benefits obtained from this study are to help radiologists to diagnose the types of brain tumors suffered by patients quickly and accurately, especially patients in the intensive care unit, and it becomes one of the references for researchers who focus on computer vision technology in the medical field
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