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Title: Automatic edema segmentation and quantification from cardiac MRI with 3D visualization
Author: Kadir, Kushsairy Abdul
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2012
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The extent of myocardial edema delineates the ischemic area-at-risk (AAR) after myocardial infarction (MI). Since AAR can be used to estimate the amount of salvageable myocardial post-MI, edema imaging has potential clinical utility in the management of acute MI patients. T2 weighted Cardiac Magnetic Resonance (CMR) imaging is widely used to investigate the extent of edema with recent acute MI patient. This thesis describes new approaches and methods of automatic edema segmentation and quantification with 3D visualization. An integrated approach has been developed, including the localization of Left Ventricle (LV) wall, segmentation of myocardial wall, segmentation and quantification of edema and 3D visualization and quantification. A novel automatic segmentation of LV wall is proposed. First a new LV wall localization algorithm is used to locate the centre of the blood pool region of the LV wall. Then a novel LV wall segmentation algorithm is used to segment the LV wall from the rest of anatomical structure. The advantage of the proposed method is in its ability to automatically localize the blood pool region of LV wall and the additional shape constraint which is adaptive to the data. A novel, Automatic Edema Segmentation and Quantification algorithm is presented which is developed based on a statistical mixture model. The technique takes advantage of the characteristic of the MRI signal where the signal is governed by a Rician distribution and using this information regions of edema are segmented over the rest of LV wall. A post-processing step in used to include microvascular obstruction as part of the edema region. The computational simplicity and good edema discrimination are described. Finally, a novel integrated approach to 3D visualization and quantification algorithm is presented. It extracts the information of the LV wall boundary and edema boundary. Then the information is used to generate an interactive 3D image which helps the clinician to visualize the extent of edema and its location. This edema quantification and 3D visualization method is evaluated by expert clinicians with favourable results.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral