|Authors||K. S. Mcleod, S. Wall and J. Saberniak|
|Title||Quantitative Measures of Right Ventricular Shape Abnormalities in ARVC Patients|
|Project(s)||Center for Biomedical Computing (SFF)|
|Publication Type||Proceedings, refereed|
|Year of Publication||2016|
|Conference Name||24th Annual Meeting of the International Society for Magnetic Resonance in Medicine|
Better understanding of the impact that disease has on ventricular shape remodeling and improved tools for quantifying disease severity are needed in complex diseases such as ARVC. We propose a method to automatically characterise right ventricular shape features in ARVC patients using statistical methods applied to shapes extracted from CMR images in a population of 27 ARVC patients. In addition to characterizing the typical shape features in ARVC, the level of severity of any given shape feature (e.g. dilation) can be measured in a new patient to quantify the degree in which that specific feature is present in that patient.