A novel machine vision application of characteristic identification using band-limited filtration as applied to cancer metastasis in the quail cam assay
| dc.contributor.advisor | Nowak, Brent M. | |
| dc.contributor.author | Whitney, Thomas | |
| dc.contributor.committeeMember | Rigney, Michael | |
| dc.contributor.committeeMember | Saygin, Can | |
| dc.contributor.committeeMember | Han, Hai-Chao | |
| dc.date.accessioned | 2024-03-08T17:36:26Z | |
| dc.date.available | 2024-03-08T17:36:26Z | |
| dc.date.issued | 2011 | |
| dc.description | This item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID. | |
| dc.description.abstract | In vivo, real time imaging of the cancer metastasis process in living organisms may provide insights relevant to viability, characteristic identification, and ultimately a better understanding of treatment efficacy. Current in vivo methods for studying metastasis are conducted through visual inspection of test embryos. These visual inspections are performed to determine embryo viability and site selection within these organisms for the introduction of cancer. Once this cancer has been inserted, the process related to its propagation and the introduction of therapies can be quantitatively studied through the use of light-emitting reporters. Limitations within this method can include, but are not limited to, the large number of samples required for consistency, coupled with the visual inspection related to viability and the cancer introduction site. The work presented relates to the development of an automated method of characteristic identification within an imaged embryo environment. Band-limited optical filtration was utilized as a preprocessing method for contrast enhancement and attenuation, relative to four unique features under inspection within the imaged scene. A total, automated image processing algorithm was developed to analyze embryo viability, omit spurious data, and to identify and characterize the embryo body and vascular network. Through the incorporation of optical filtration, a structured imaging environment and a developed image processing algorithm, deterministic outputs were able to be obtained. The results from these processed images have led to an accurate method of quail embryo feature identification that may be used as a means of furthering aspects related to metastasis research. | |
| dc.description.department | Mechanical Engineering | |
| dc.format.extent | 174 pages | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.isbn | 9781124629155 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12588/6176 | |
| dc.language | en | |
| dc.subject | Band Pass Filtration | |
| dc.subject | Feature Extraction | |
| dc.subject | Image Analysis | |
| dc.subject | Machine Vision | |
| dc.subject.classification | Mechanical engineering | |
| dc.subject.classification | Oncology | |
| dc.title | A novel machine vision application of characteristic identification using band-limited filtration as applied to cancer metastasis in the quail cam assay | |
| dc.type | Thesis | |
| dc.type.dcmi | Text | |
| dcterms.accessRights | pq_closed | |
| thesis.degree.department | Mechanical Engineering | |
| thesis.degree.grantor | University of Texas at San Antonio | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Science |
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