Semantic segmentation of angiographic images
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.