A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors.

Journal: Computer methods and programs in biomedicine
Published Date: Oct 31, 2020

Abstract

BACKGROUND: Brain tumors are life-threatening, and their early detection is crucial for improving survival rates. Conventionally, brain tumors are detected by radiologists based on their clinical experience. However, this process is inefficient. This paper proposes a machine learning-based method to 1) determine the presence of a tumor, 2) automatically segment the tumor, and 3) classify it as benign or malignant.

Authors

  • Baoshi Chen
    Department of Neuro-oncology, Neurosurgery Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. Electronic address: tiantanchenbaoshi@163.com.
  • Lingling Zhang
    Department of Information Technology, Hunan Women's University, Changsha, Hunan 410002, PR China. Electronic address: linglingmath@gmail.com.
  • Hongyan Chen
    Department of Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
  • Kewei Liang
    National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Xuzhu Chen
    Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, China. Electronic address: radiology888@aliyun.com.

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