Blood Vessel Quantification and Analysis on CTA and MRA Images
Vascular disease is characterized by any condition that affects the circulatory system.
Currently there is a need for sophisticated software tools that can characterize the
integrity and functional state of vascular networks from different vascular imaging
modalities. These tools face significant challenges such as: large datasets, similarity in
intensity distributions of other organs and structures, and the presence of complex vessel
branches.
In my PhD course I present a new approach to automatically track, and quantify the properties
of vascular networks based on CTA and MRA images. Our methodology is based on the Hough
Transform to dynamically estimate the center of masse and vessel size along the
abdominal aorta. Furthermore, the vessel architecture and orientation is determined by
the analysis of the Hessian matrix of the CTA and MRA intensity distribution.
Fig.1 - Angiography example [Institut Mèdic per la Imatge- www.imi.es].
The challenge is to extract vascular networks and get information as branch pattern, lumen diameter, tortuosity, etc.
We intend to evaluate the methodology using synthetic datasets (fig2).
Fig.2 - The methodology performance on synthetic image.
Fig.3 - The methodology performance in a aortic arch and thoracic aorta on CTA image.
Programming language: C++
Libraries: VTK e ITK
Video (download): Video about vessel detection slice by slice (.avi)
|
maysa (a t) ime.usp.br
|
|
