Abstract
This paper presents a fully automatic method to segment the right ventricle (RV) from short-axis cardiac MRI. A combination of a novel window-constrained accumulator thresholding technique, binary difference of Gaussian (DoG) filters, optimal thresholding, and morphology are utilized to drive the segmentation. A priori segmentation window constraints are incorporated to guide and refine the process, as well as to ensure appropriate area confinement of the segmentation. Training and testing were performed using a combined 48 patient datasets supplied by the organizers of the MICCAI 2012 right ventricle segmentation challenge, allowing for unbiased evaluations and benchmark comparisons. Marked improvements in speed and accuracy over the top existing methods are demonstrated.
Original language | English (US) |
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Pages (from-to) | 190-201 |
Number of pages | 12 |
Journal | Computerized Medical Imaging and Graphics |
Volume | 38 |
Issue number | 3 |
DOIs | |
State | Published - Apr 2014 |
Externally published | Yes |
Keywords
- A priori constraints
- Binary difference of Gaussians filter
- Cardiac MRI
- Optimal thresholding
- Ventricular segmentation
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Graphics and Computer-Aided Design