MRI Segmentation for Computer-Aided Diagnosis of Brain Tumor: A Review

  • Princi SoniEmail author
  • Vijayshri Chaurasia
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)


Brain tumor is an uncontrolled growth of cells in the brain. Diagnosis of brain tumor is complicated and challenging task as the brain itself a complex structure and tumor have excessive variety, diversity in shape, large range in intensity and ambiguous boundaries. The validity of brain tumor segmentation is a significant issue in biomedical signal processing because it has a direct impact on surgical groundwork. Detection of brain tumor by magnetic resonance imaging (MRI) using (CAD) involves; preprocessing, segmentation, and morphological operation for analysis purpose. The magnetic resonance imaging segmentation is characterized by a high nonuniformity of both the pathology and the surrounding non-pathologic brain tissue. Computer Aided Diagnosis system can assist in the detection of suspicious brain disease as the manual segmentation is time-consuming and it reported the time-varying result. To tag tumor pixel or trace tumor area, texture and pattern remembrance, classification is performed with different algorithms. This article presents an overview of the most relevant brain tumor segmentation methods.


Brain tumor MRI Image segmentation Computer-aided diagnosis 


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Electronics and CommunicationMaulana Azad National Institute of TechnologyBhopalIndia

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