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Image Analysis of Glioblastoma Histopathology

Chaganti, Shikha
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611

Abstract Details

2014, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
Glioblastoma is a form of malignant brain tumor in humans involving glial or non-neuronal cells. The state-of-the-art diagnosis of Glioblastoma is predominantly based on subjective opinion of trained pathologists. However, with the availability of large-scale databases of Glioblastoma histopathology images, it is now possible, in principle, to objectively study and classify this class of tumors via image analysis and pattern recognition techniques. The objective of this work is to develop a quantitative framework for the analysis of Glioblastoma. The first, fundamental step in this process is the identification of histological structures in these images, that is, segmenting the constituent nuclei in the tissue. The work presents a two-step process of iterative thresholding and cleaving (ITC) to identify aforementioned structures. This improves significantly over standard color-based cell segmentation techniques in identifying cellular structures, giving 91.8% precision and 94.7% recall. Furthermore, using various architectural features obtained from each image, it ensures that the identification of regions important for the diagnosis process is distinctly clearer using the ITC approach than with standard approaches such as the Otsu method and adaptive thresholding.
Anca Ralescu, Ph.D. (Committee Chair)
Fred Annexstein, Ph.D. (Committee Member)
Bruce Aronow, Ph.D. (Committee Member)
75 p.
Computer Science
Image Analysis; Clustering; Computer aided diagnosis; Glioblastoma; Histopathology

Recommended Citations

Citations

  • Chaganti, S. (2014). Image Analysis of Glioblastoma Histopathology [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611

    APA Style (7th edition)

  • Chaganti, Shikha. Image Analysis of Glioblastoma Histopathology. 2014. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611.

    MLA Style (8th edition)

  • Chaganti, Shikha. "Image Analysis of Glioblastoma Histopathology." Master's thesis, University of Cincinnati, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406820611

    Chicago Manual of Style (17th edition)

ucin1406820611
317
© 2014, some rights reserved.Creative Commons License Image Analysis of Glioblastoma Histopathology by Shikha Chaganti is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.