An Automated Brain Tumor Segmentation Framework Using Multimodal MRI

  • Haifeng Zhao
  • Shuhai ChenEmail author
  • Shaojie Zhang
  • Siqi Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)


An automated region of interest (ROI) segmentation framework is proposed for edema detection and brain tumor segmentation from brain magnetic resonance images (MRI). In order to further improve the accuracy of the framework, multimodal MRI data are applied in this framework. The framework mainly contains three stages. First the cluster algorithm and morphological operation are used for detecting the abnormal tissue i.e. edema so as to automatically initialize the level set method. Then edge-based level set method combining regional information is used for edema segmentation from Fluid Attenuated Inversion Recovery (FLAIR) MRI. The final segmentation result of brain tumor is obtained by using the cluster method, filling algorithm and opening (morphology) operation at T1 contrast-enhanced (T1c) MRI. The experiments are carried out on two modalities MRI slices of 8 true patients, which have the matching ground truth of the edema and tumor. Experimental results demonstrate the effectiveness of our algorithm.


Level set Brain tumor Image segmentation MRI 



The Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry (NO. 48, 2014-1685), the Key Natural Science Project of Anhui Provincial Education Department (KJ2017A016).


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Haifeng Zhao
    • 1
    • 2
  • Shuhai Chen
    • 1
    • 3
    Email author
  • Shaojie Zhang
    • 1
    • 2
  • Siqi Wang
    • 1
  1. 1.Key Lab of Intelligent Computing and Signal Processing of MOE and School of Computer and TechnologyAnhui UniversityHefeiPeople’s Republic of China
  2. 2.Key Lab of Industrial Image Processing and Analysis of Anhui ProvinceHefeiPeople’s Republic of China
  3. 3.Anhui UniversityHefei CityChina

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