Title :
Semantic segmentation of angiographic images
Author :
Menegaz, Gloria ; Lancini, Rosa
Author_Institution :
Signal Process. Lab., Fed. Inst. of Technol., Lausanne, Switzerland
fDate :
31 Oct-3 Nov 1996
Abstract :
The overall purpose of this work is to identify objects in an angiographic sequence by exploiting the temporal correlation between adjacent frames for analysis and compression purposes. The detection of the vascular tree in a reference image can support segmentation in adjacent frames by reducing the detection problem to a tracking procedure along the sequence. Object identification also allows an object-oriented approach to compression, as suggested by medical images nature. A vessel segmentation algorithm has been designed and implemented; it is an extrapolation and update procedure which exploits the a priori knowledge about the image content
Keywords :
data compression; diagnostic radiography; image segmentation; medical image processing; a priori knowledge; adjacent frames temporal correlation; angiographic images; extrapolation/update procedure; image content; medical diagnostic imaging; object identification; object-oriented approach; reference image; semantic segmentation; vascular tree detection; vessel segmentation algorithm; Biomedical imaging; Data mining; Feature extraction; Image coding; Image segmentation; Image sequence analysis; Laboratories; Signal processing; Signal processing algorithms; Skeleton;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.651920
