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Literature DB >> 9306149

Automated detection of the left ventricular region in magnetic resonance images by Fuzzy c-Means model.

Abstract

A new method for automated detection of the Left Ventricular (LV) region in Magnetic Resonance Imaging is presented. This method is based on the Fuzzy c-Means (FCM) clustering algorithm. The FCM is applied to each static frame of the cardiac cycle to detect the LV region. Delineation of this region is essential in the quantitative analysis of the cardiac function. The effectiveness of the method is demonstrated by application to sequences of cardiac images.

Entities: Gene

Mesh：

Year: 1997 PMID： 9306149 DOI： 10.1023/a:1005755819752

Source DB: PubMed Journal: Int J Card Imaging ISSN： 0167-9899

12 in total

1. Magnetic resonance imaging vs. ultrafast computed tomography for cardiac diagnosis.

Authors: R M MacMillan
Journal: Int J Card Imaging Date: 1992

2. Automated identification of left ventricular borders from spin-echo magnetic resonance images. Experimental and clinical feasibility studies.

Authors: S R Fleagle; D R Thedens; J C Ehrhardt; T D Scholz; D J Skorton
Journal: Invest Radiol Date: 1991-04 Impact factor: 6.016

2. Left ventricle segmentation using graph searching on intensity and gradient and a priori knowledge (lvGIGA) for short-axis cardiac magnetic resonance imaging.

Authors: Hae-Yeoun Lee; Noel Codella; Matthew Cham; Martin Prince; Jonathan Weinsaft; Yi Wang
Journal: J Magn Reson Imaging Date: 2008-12 Impact factor: 4.813

2 in total

Automated detection of the left ventricular region in magnetic resonance images by Fuzzy c-Means model.

1. Magnetic resonance imaging vs. ultrafast computed tomography for cardiac diagnosis.

2. Automated identification of left ventricular borders from spin-echo magnetic resonance images. Experimental and clinical feasibility studies.

3. Tag and contour detection in tagged MR images of the left ventricle.

4. Knowledge-based system for boundary detection of four-dimensional cardiac magnetic resonance image sequences.

5. Segmentation of cardiac cine MR images for extraction of right and left ventricular chambers.

6. A model-based four-dimensional left ventricular surface detector.

7. On the foundations of relaxation labeling processes.

8. An automatic contour extraction algorithm for short-axis cardiac magnetic resonance images.

9. Measurement of left ventricular mass in vivo using gated nuclear magnetic resonance imaging.

10. In vivo measurement of myocardial mass using nuclear magnetic resonance imaging.

1. Automatic segmentation of left ventricle cavity from short-axis cardiac magnetic resonance images.

2. Left ventricle segmentation using graph searching on intensity and gradient and a priori knowledge (lvGIGA) for short-axis cardiac magnetic resonance imaging.