Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/45168
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dc.contributor.authorSoo, Beng Beng.
dc.date.accessioned2011-06-09T07:30:15Z
dc.date.available2011-06-09T07:30:15Z
dc.date.copyright2011en_US
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10356/45168
dc.description.abstractThe assessment of lymph node is commonly used as a yardstick in diagnosis, staging, treatment and therapy control of tumours and their metastases. Current practice of the radiologists is to manually measure the major and minor axis of nodes based on experiences. This method is highly subjected to inter-operator variation. In this report, we present an automated lymph node segmentation model in longitudinal studies. With this model, lymph node would be segmented once using the semi-automated active contour (snake) at baseline and subsequent follow-up studies could be segmented automatically through registration. We applied two types of registration i.e. Free Form Deformation (FFD) and Demons Registration in this study and compared the efficiency and accuracy of both. It was found that Demons-based registration generates results with higher accuracy. We applied the automated segmentation technique to 18 pairs of lymph nodes from 8 patients at baseline and follow-up. A set of manual segmentation results, recognized by two experienced radiologists, serves as the gold standard for evaluation of performance of the method. In Demons-based model, we could observe that 11 out of 18 nodes are well segmented, 6 out of 18 nodes showed slight leakage due to blurred boundaries and 1 out of 18 failed terribly. Including the failed node in statistics, the overall automated segmentation showed an average Dice’s Coefficient of 0.799, sensitivity of 0.799 and specificity of 0.970.en_US
dc.format.extent65 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Science::Medicine::Optical instrumentsen_US
dc.titleSegmentation of lymph node in longitudinal studies of thoracic CT imagesen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorPoh Chueh Looen_US
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen_US
dc.description.degreeBachelor of Engineering (Chemical and Biomolecular Engineering)en_US
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Appears in Collections:SCBE Student Reports (FYP/IA/PA/PI)
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