Rule based segmentation of colon glands
buir.advisor | Demir, ĆiÄdem GĆ¼ndĆ¼z | |
dc.contributor.author | YĆ¼cel, Simge | |
dc.date.accessioned | 2018-10-04T06:28:07Z | |
dc.date.available | 2018-10-04T06:28:07Z | |
dc.date.copyright | 2018-09 | |
dc.date.issued | 2018-09 | |
dc.date.submitted | 2018-09-02 | |
dc.description | Cataloged from PDF version of article. | en_US |
dc.description | Thesis (M.S.): Bilkent University, Department of Computer Engineering, Ä°hsan DoÄramacı Bilkent University, 2018. | en_US |
dc.description | Includes bibliographical references (leaves 49-51). | en_US |
dc.description.abstract | Colon adenocarcinoma, which accounts for more than 90 percent of all colorectal cancers, originates from epithelial cells that form colon glands. Thus, for its diagnosis and grading, it is important to examine the distortions in the organizations of these epithelial cells, and hence, the deformations in the colon glands. Therefore, localization of the glands within a tissue and quanti cation of their deformations is essential to develop an automated or a semi-automated decision support system. With this motivation, this thesis proposes a new structural segmentation algorithm to detect glands in a histopathological tissue image. This structural algorithm proposes to transform the histopathological image into a new representation by locating a set of primitives using the Voronoi diagram, to generate gland candidates by de ning a set of rules on this new representation, and to devise an iterative algorithm that selects a subset of these candidates based on their tness scores. The main contribution of this thesis is the following: The representation introduced by this proposed algorithm enables us to better encode the colon glands by de ning the rules and the tness scores with respect to the appearance of the glands in a colon tissue. This representation and encoding have not been used by the previous studies. The experimental results of our algorithm show that this proposed algorithm improves the segmentation results of its pixel-based and structural counterparts without applying any further processing. | en_US |
dc.description.provenance | Submitted by BetĆ¼l Ćzen (ozen@bilkent.edu.tr) on 2018-10-04T06:28:07Z No. of bitstreams: 1 simge_yucel_master_thesis.pdf: 26102369 bytes, checksum: b82473593903ec7b2f11140dd9bb5a70 (MD5) | en |
dc.description.provenance | Made available in DSpace on 2018-10-04T06:28:07Z (GMT). No. of bitstreams: 1 simge_yucel_master_thesis.pdf: 26102369 bytes, checksum: b82473593903ec7b2f11140dd9bb5a70 (MD5) Previous issue date: 2018-09 | en |
dc.description.statementofresponsibility | by Simge YĆ¼cel. | en_US |
dc.format.extent | xi, 51 leaves : illustrations (some color) ; 30 cm. | en_US |
dc.identifier.itemid | B158597 | |
dc.identifier.uri | http://hdl.handle.net/11693/48075 | |
dc.language.iso | English | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Histopathological Image Analysis | en_US |
dc.subject | Gland Segmentation | en_US |
dc.subject | Voronoi Diagram | en_US |
dc.subject | Structural Method | en_US |
dc.title | Rule based segmentation of colon glands | en_US |
dc.title.alternative | Kalın baÄırsak bezlerinin kurala dayanarak bƶlĆ¼tlenmesi | en_US |
dc.type | Thesis | en_US |
thesis.degree.discipline | Computer Engineering | |
thesis.degree.grantor | Bilkent University | |
thesis.degree.level | Master's | |
thesis.degree.name | MS (Master of Science) |
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