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dc.contributor.advisorEvans, Kevin
dc.creatorStrapp, Ashley
dc.date.accessioned2010-05-14T13:26:59Z
dc.date.available2010-05-14T13:26:59Z
dc.date.issued2010-06
dc.identifier.urihttp://hdl.handle.net/1811/45364
dc.description2nd place winner at Denman Undergraduate Research Forumen_US
dc.description.abstractGoal: To determine the feasibility of utilizing image segmentation to evaluate axillary lymph nodes with both automatic and manual technology. Methods: Manual technology was accomplished with GE Logic 9 ultrasound machine, 3D volume set, and Vocal software. The automated technology was accomplished by uploading the volume sets to a computer with software that provides the ability to perform level set algorithms, active contours, deformable models, thresholding, and region growing and ultimately creates a segmented model of the node. Findings: Manual image segmentation provides smooth cortical borders on all nodes imaged. It is feasible to conduct automated segmentation of sonographic images from 3D rendered images of axillary lymph nodes. However automatic image segmentation provides textured borders that include afferent lymph vessels and aging changes. Cubic volume sets of each node for each type of segmentation have been calculated to be compared to each other as well. Significance: Automated image segmentation demonstrates early utility in determining precise cortical morphology of the node. This may be beneficial for assessing signs of detection of breast cancer. This research also furthers the idea that sonography can be used as a non-invasive, non-ionizing modality to manually and automatically segment lymph nodes. Continued research with image segmentation can promote a standard way to assess axillary lymph nodes and obtain precise tissue volumes and diagnosis.en_US
dc.description.sponsorshipGE Healthcareen_US
dc.description.sponsorshipPhillips Medical Corporationen_US
dc.description.sponsorshipThe Ohio State Universityen_US
dc.language.isoen_USen_US
dc.publisherThe Ohio State Universityen_US
dc.relation.ispartofseriesThe Ohio State University. School of Allied Medical Professions Honors Theses; 2010en_US
dc.subjectsonographic image segmentationen_US
dc.subjectmanual segmentationen_US
dc.subjectautomated segmentationen_US
dc.subjectultrasounden_US
dc.subjectaxillary lymph nodeen_US
dc.titleThe Feasibility of Utilizing Sonographic Image Segmentation to Evaulate Axillary Lymph Nodes: Automated Computer Software vs. Manual Segmentationen_US
dc.typeDataseten_US
dc.typeImageen_US
dc.typeThesisen_US
dc.description.embargoNo embargoen_US
dc.rights.ccAttribution 3.0 Unporteden_US
dc.rights.ccurihttp://creativecommons.org/licenses/by/3.0/en_US


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