Authors:
Karla L Caballero
1
;
Joel Barajas
1
;
Oriol Pujol
2
;
Josefina Mauri
3
and
Petia Radeva
1
Affiliations:
1
Computer Vision Center, Autonomous University of Barcelona, Spain
;
2
University of Barcelona, Computer Vision Center, Spain
;
3
Hospital Universitari German Trias i Pujol, Spain
Keyword(s):
Intravascular Ultrasound, RF signals, Image Reconstruction, Tissue Classification, Adaboost, ECOC.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Informatics in Control, Automation and Robotics
;
Medical Image Analysis
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Plaque rupture in coronary vessels is one of the principal causes of sudden death in western societies. Reliable diagnostic tools are of great interest for physicians in order to detect and quantify vulnerable plaque in order to develop an effective treatment. To achieve this, a tissue classification must be performed. Intravascular Ultrasound (IVUS) represents a powerful technique to explore the vessel walls and to observe its morphology and histological properties. In this paper, we propose a method to reconstruct IVUS images from the raw Radio Frequency (RF) data coming from the ultrasound catheter. This framework offers a normalization scheme to compare accurately different patient studies. Then, an automatic tissue classification based on the texture analysis of these images and the use of Adapting Boosting (AdaBoost) learning technique combined with Error Correcting Output Codes (ECOC) is presented. In this study, 9 in-vivo cases are reconstructed with 7 different parameter set
. This method improves the classification rate based on images, yielding a 91% of well-detected tissue using the best parameter set. It is also reduced the inter-patient variability compared with the analysis of DICOM images, which are obtained from the commercial equipment.
(More)