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Fully Convolutional Networks (FCNs) for Medical Image Segmentation

Zhewei, Wang
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605199701509179

Abstract Details

2020, Doctor of Philosophy (PhD), Ohio University, Computer Science (Engineering and Technology).
In recent years, fully convolutional networks (FCNs) have become the state-of-the-art solutions for various image segmentation tasks. Duo to the network setups, however, the standard FCNs tend to have issues of 1) overlooking small components; and 2) lacking intermediate supervision. To tackle the first issue in FCNs, we develop a two-stage network solution and apply it for white-matter lesion segmentation task. In the first stage, we design three networks with different input sizes and train them with patches from brain MR scans. In the second stage, we process large and small lesion separately, and use ensemble-nets to combine the segmentation results. A number of network setups, including activation functions, training strategy and ensemble paradigms have been explored to improve the segmentation accuracy measured by Dice Similarity Coefficient. The address the second issue, we adopt the notions of network residual and Laplacian pyramids to design a Laplacian module as the building block for new FCNs. The networks are applied to segment follicles and follicular cells. In order to separate individual follicle instances, we take advantage of the topological relationship between follicles and colloid, and use colloid masks as the guidance to identify individual labels. We also utilize Sobel edge maps as a guiding loss to ensure the smoothness of the segmentation results.
David Juedes (Committee Member)
Razvan Bunescu (Committee Member)
Chang Liu (Committee Member)
Li Xu (Committee Member)
Qiliang Wu (Committee Member)
Jundong Liu (Advisor)
95 p.
Artificial Intelligence
Medical image analysis; deep learning

Recommended Citations

Citations

  • Zhewei, W. (2020). Fully Convolutional Networks (FCNs) for Medical Image Segmentation [Doctoral dissertation, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605199701509179

    APA Style (7th edition)

  • Zhewei, Wang. Fully Convolutional Networks (FCNs) for Medical Image Segmentation. 2020. Ohio University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605199701509179.

    MLA Style (8th edition)

  • Zhewei, Wang. "Fully Convolutional Networks (FCNs) for Medical Image Segmentation." Doctoral dissertation, Ohio University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1605199701509179

    Chicago Manual of Style (17th edition)

ohiou1605199701509179
167
© 2020, all rights reserved.
This open access ETD is published by Ohio University and OhioLINK.