The feasibility of using feature-flow and label transfer system to segment medical images with deformed anatomy in orthopedic surgery

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dc.contributor.advisorMa, Burton
dc.contributor.advisorElder, James
dc.contributor.advisorGodfrey, Parke
dc.contributor.advisorSchneider, Keith A.
dc.creatorZhao, Yao Jun
dc.date.accessioned2016-09-13T13:15:46Z
dc.date.available2016-09-13T13:15:46Z
dc.date.copyright2012-12
dc.degree.disciplineComputer Science
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractIn computer-aided surgical systems, to obtain high fidelity three-dimensional models, we require accurate segmentation of medical images. State-of-art medical image segmentation methods have been used successfully in particular applications, but they have not been demonstrated to work well over a wide range of deformities. For this purpose, I studied and evaluated medical image segmentation using the feature-flow based Label Transfer System described by Liu and colleagues. This system has produced promising results in parsing images of natural scenes. Its ability to deal with variations in shapes of objects is desirable. In this paper, we altered this system and assessed its feasibility of automatic segmentation. Experiments showed that this system achieved better recognition rates than those in natural-scene parsing applications, but the high recognition rates were not consistent across different images. Although this system is not considered clinically practical, we may improve it and incorporate it with other medical segmentation tools.
dc.identifier.urihttp://hdl.handle.net/10315/32036
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subject.keywordsFeature-flow systems
dc.subject.keywordsLabel transfer systems
dc.subject.keywordsMedical images
dc.subject.keywordsOrthopedic surgery
dc.subject.keywordsMedical image segmentation methods
dc.titleThe feasibility of using feature-flow and label transfer system to segment medical images with deformed anatomy in orthopedic surgery
dc.typeElectronic Thesis or Dissertation

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