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Hybrid Image Processing-Based Examination of 2D Brain MRI Slices to Detect Brain Tumor/Stroke Section: A Study

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Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Abstract

In human physiology, the brain is the most important internal organ, and a disease in the brain affects the individual severely and the untreated disease will lead to death. In the brain, tumor as well as ischemic stroke is the leading cause of death/permanent disability in elderly. The clinical-level diagnosis of this disease is normally carried with the well-known imaging technique called magnetic resonance imaging (MRI) due to its multimodality and proven nature. Radiology helps to generate a 3D structure of the MRI and from which the 2D slices are extracted and examined to detect the abnormality. Further, the examination of 2D slices is quite simple compared to the 3D image. This work implements a hybrid imaging technique by considering the thresholding and segmentation techniques. Thresholding helped to improve the visibility of the abnormal part, and this thresholding is executed with the brain storm optimization-based Otsu’s/Kapur’s function. Later, the abnormal part from this image is extracted using the chosen segmentation technique. In this work, a detailed assessment of the existing segmentation procedures, such as watershed, active contour, level set and region growing, is presented. Finally, a study with the ground truth and extracted part is executed, and based on the Jaccard, Dice, and accuracy, the performance of the proposed technique is validated.

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Author information

Authors and Affiliations

  1. AP Research, Seven Lakes High School, Katy, TX, USA

    David Lin

  2. Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India

    V. Ra**ikanth

  3. Department of Computer Science and Engineering Technology, University of Houston-Downtown, Houston, TX, USA

    Hong Lin

Authors
  1. David Lin
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  2. V. Ra**ikanth
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  3. Hong Lin
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Corresponding author

Correspondence to V. Ra**ikanth .

Editor information

Editors and Affiliations

  1. Electronics and Communication Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India

    E. Priya

  2. Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India

    V. Ra**ikanth

Appendix

Appendix

Fig. 2.9
figure 9

Results attained with LS. (a) Initiation of bounding box, (b) bounding box, (c) converged LS on tumor, (d) 3D view of the extracted tumor, (e) binary image of the tumor (similar kind of results were attained with the active contour and region growing segmentation techniques)

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Fig. 2.10
figure 10

Sample images from high-grade BRATS2015 database

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Fig. 2.11
figure 11

Sample images from Radiopaedia clinical grade database

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Lin, D., Ra**ikanth, V., Lin, H. (2021). Hybrid Image Processing-Based Examination of 2D Brain MRI Slices to Detect Brain Tumor/Stroke Section: A Study. In: Priya, E., Ra**ikanth, V. (eds) Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-6141-2_2

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