期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：11
页码：2969-2987
出版社：Journal of Theoretical and Applied
摘要：This paper provides a detailed analysis of the existent methods and approaches utilized in medical image segmentation. Also integrate a comparative study of the automated brain tumor coupled through the utilization of tuomr detection techniques. Additionally, the paper will provide an analysis of the process integrated pertaining to the retrieval of brain images through the identification of the specific data sets selected in the process to identify the stipulated features., [1]maintains that the utilization of a computer-aided diagnosis in medical imaging influences the decision-making capacity of specialists in the provision of accurate images pertaining to the existent volume and distance. Also maintains that the detection of brain ailments remains difficult among radiologists and neurologists due to the existence of similar brain abnormalities. The existence variances influence the level of difficulties experienced pertaining to the tasks due to the existence of differential diagnosis coupled with the complexity attached to manual segmentation. The processes delimit the accuracy levels leading to the identification of the need for the provision of additional time considered necessary in meeting the stipulated needs of the process. The process necessitates the integration of extensive processes necessary in the identification of reliable and accurate algorithms necessary in the provision of solutions pertaining to the existent questions. This part of the study seeks to integrate an illustrative analysis, which will provide illustration that will identify the existent needs relating to automatic detection. The approaches will influence the evaluation processes integrated pertaining to the existent human brain abnormalities including injuries, tumor and edema. The process will also remain instrumental in the identification of additional abnormalities that can be extracted from computerized images of human brain.
