Volume( 10) - Issue( 4) 2023 pp 1-8 DOI: 10.62346/ijbsip_v10_no4_23_01

Automatic Segmentation and Edge Detection in MRI Scan for Brain Tumor Classification and Evaluation

Title

Automatic Segmentation and Edge Detection in MRI Scan for Brain Tumor Classification and Evaluation

Abstract

Medical image processing is the challenging field with newly developing importance. Medical imaging methods view images present in internal human body components for medical research. Transportation Brain tumor segmentation is a perceptive step in medical domains. The correct size and treatment measurement in the MR images enable one to easily view the tumor portion. One could differentiate a necrosis from the surrounding tissue. based on eliminating tumor information from brain MRI, the automatic image segmentation technique method of segmentation dividing brain MR images independently into tumor, white matter, gray matter, and cerebrospinal fluid This work detects brain tumors by using improved automatic image segmentation techniques applied on MRI scan images. We show the segmentation and extraction of the brain tumor with help from pixel intensity. Iterative thresholding lets one find tumor origins and age. Apart from the tumor component, the age of the tumor and the dissemination in those clearly identifiable regions are also present. The proposed approach might be applied successfully such that the doctor can stop the tumor from spreading and the source could help to identify the exact area. In this sense, knowing the length of the tumor seen in an MRI image from a patient's record will help the doctor.

Keywords

Automatic image segmentation, cerebrospinal fluid, gray matter, Magnetic Resonance Imaging, region of interest and white matter.

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