Automatic Detection of Brain Tumor on Computed Tomography Images for Patients in the Intensive Care Unit
Joint Authors
Fahmi, Fahmi
Apriyulida, Fitri
Nasution, Irina Kemala
Sawaluddin, Irina Kemala
Source
Journal of Healthcare Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
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%.
American Psychological Association (APA)
Fahmi, Fahmi& Apriyulida, Fitri& Nasution, Irina Kemala& Sawaluddin, Irina Kemala. 2020. Automatic Detection of Brain Tumor on Computed Tomography Images for Patients in the Intensive Care Unit. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186229
Modern Language Association (MLA)
Fahmi, Fahmi…[et al.]. Automatic Detection of Brain Tumor on Computed Tomography Images for Patients in the Intensive Care Unit. Journal of Healthcare Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1186229
American Medical Association (AMA)
Fahmi, Fahmi& Apriyulida, Fitri& Nasution, Irina Kemala& Sawaluddin, Irina Kemala. Automatic Detection of Brain Tumor on Computed Tomography Images for Patients in the Intensive Care Unit. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186229
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186229