Title :
Performing segmentation of ultrasound images using temporal information
Author :
Herlin, I.L. ; Giraudon, G.
Author_Institution :
INRIA Rocquencourt, France
Abstract :
Spatiotemporal segmentation in echocardiographic image sequences is discussed. Spatial properties and temporal properties are combined to compute segmentation and tracking in a single process. The Markov random field (MRF) framework is used for modeling the energy function. Starting from a reference image, where a manual segmentation is made, a method is developed to estimate the model parameters. An estimation is a crucial point in MRF models. Thus, given an initial segmentation of the sequence, this approach can segment and track a cardiac cavity during the cardiac cycle. Its performance is demonstrated on a real echocardiographic sequence
Keywords :
Markov processes; biomedical ultrasonics; cardiology; image segmentation; image sequences; parameter estimation; Markov random field; cardiac cavity; cardiac cycle; echocardiographic image sequences; energy function; manual segmentation; reference image; spatiotemporal segmentation; tracking; Acoustic noise; Data mining; Deformable models; Feature extraction; Filtering; Image segmentation; Image sequences; Layout; Markov random fields; Parameter estimation; Spatiotemporal phenomena; Ultrasonic imaging;
Conference_Titel :
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location :
New York, NY
Print_ISBN :
0-8186-3880-X
DOI :
10.1109/CVPR.1993.341103