A review of segmentation methods in short axis cardiac MR images

For the last 15 years, Magnetic Resonance Imaging (MRI) has become a reference examination for cardiac morphology, function and perfusion in humans. Yet, due to the characteristics of cardiac MR images and to the great variability of the images among patients, the problem of heart cavities segmentation in MRI is still open. This paper is a review of fully and semi-automated methods performing segmentation in short axis images using a cardiac cine MRI sequence. Medical background and specific segmentation difficulties associated to these images are presented. For this particularly complex segmentation task, prior knowledge is required. We thus propose an original categorization for cardiac segmentation methods, with a special emphasis on what level of external information is required (weak or strong) and how it is used to constrain segmentation. After reviewing method principles and analyzing segmentation results, we conclude with a discussion and future trends in this field regarding methodological and medical issues.

This paper is a review of fully and semi-automated methods performing cardiac ventricle segmentation in short axis MR images. For this particularly complex segmentation task, prior knowledge is required. An original categorization for cardiac segmentation methods, with a special emphasis on what level of external information is required to constrain segmentation, is presented. Segmentation results are analyzed and methodological as well as medical issues are discussed.Figure optionsDownload high-quality image (70 K)Download as PowerPoint slideResearch highlights
► Comprehensive review on segmentation methods of cardiac short-axis MR images.
► 70 papers between 1993 and 2010 have been reviewed.
► Original categorization based on the level of prior required for segmentation.
► Critical analysis of segmentation results obtained on both cardiac ventricles.
► Highlighting the role of external knowledge and motion information for segmentation.