Open AccessBrain Tumor Detection and Classification Using Image Processing Techniques
Author(s) -
Preetham Ganesh,
Tribhuwan Kumar,
Mukesh Kumar,
Sriram Kumar
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-v4-i3-005
Subject(s) - computer science , artificial intelligence , brain tumor , segmentation , image processing , computer vision , magnetic resonance imaging , feature (linguistics) , image segmentation , pattern recognition (psychology) , feature extraction , neuroimaging , image (mathematics) , radiology , medicine , pathology , linguistics , philosophy , psychiatry
At present, processing of medical images is a developing and important field. It includes many different types of imaging methods. Some of them are Computed Tomography scans (CT scans), X-rays and Magnetic Resonance Imaging (MRI) etc. These technologies allow us to detect even the smallest defects in the human body. Abnormal growth of tissues in the brain which affect proper brain functions is considered as a brain tumor. The main goal of medical image processing is to identify accurate and meaningful information using images with the minimum error possible. MRI is mainly used to get images of the human body and cancerous tissues because of its high resolution and better quality images compared with other imaging technologies. Brain tumor identifications through MRI images is a difficult task because of the complexity of the brain. MRI images can be processed and the brain tumor can be segmented. These tumors can be segmented using various image segmentation techniques. The process of identifying brain tumors through MRI images can be categorized into four different sections; pre-processing, image segmentation, feature extraction and image classification.