Carotid automated ultrasound double line extraction system (CADLES) via Edge-Flow

This paper presents a completely user-independent algorithm, that automatically extracts the far (distal) double line (lumen-intima and media-adventitia) in the carotid artery using an Edge Flow technique (a class of AtheroEdge™ systems) based on directional probability maps using the attributes of intensity and texture. The extracted double line translates into a measure of the intima-media thickness (IMT), a validated marker for the progression of atherosclerosis. The Carotid Automated Double Line Extraction System based on Edge-Flow (CADLES-EF) is characterized and validated by comparing the output of the algorithm with two other completely automatic techniques (CALEXia and CULEXsa) published by the same authors. Validation was performed on a multi-institutional database of 300 longitudinal B-mode carotid images with normal and pathologic arteries. CADLES-EF showed an intima-media thickness (IMT) bias of 0.043±0.097 mm in comparison to CALEXia and CULEXsa that showed 0.134±0.0.88 mm and 0.74±0.092 mm, respectively. The system's Figure of Merit (FoM) showed an improvement when compared to previous automated methods: CALEXia and CULEXsa, leading to values of 84.7%, 91.5%, while our new approach, CADLES-EF performed the best with 94.8%.

[1]  Alessandro C. Rossi,et al.  Automatic recognition of the common carotid artery in longitudinal ultrasound B-mode scans , 2008, Medical Image Anal..

[2]  Jasjit S. Suri,et al.  Characterization of a Completely User-Independent Algorithm for Carotid Artery Segmentation in 2-D Ultrasound Images , 2007, IEEE Transactions on Instrumentation and Measurement.

[3]  Filippo Molinari,et al.  Intima-media thickness: setting a standard for a completely automated method of ultrasound measurement , 2010, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[4]  C.P. Loizou,et al.  Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery , 2005, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[5]  B. S. Manjunath,et al.  Edge flow: A framework of boundary detection and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Aurélio J. C. Campilho,et al.  Segmentation of the carotid intima-media region in B-mode ultrasound images , 2010, Image Vis. Comput..

[7]  Emmanouil G. Sifakis,et al.  Using the Hough transform to segment ultrasound images of longitudinal and transverse sections of the carotid artery. , 2007, Ultrasound in medicine & biology.

[8]  Jasjit S. Suri,et al.  A state of the art review on intima-media thickness (IMT) measurement and wall segmentation techniques for carotid ultrasound , 2010, Comput. Methods Programs Biomed..

[9]  J. Suri,et al.  An Integrated Approach to Computer‐Based Automated Tracing and Its Validation for 200 Common Carotid Arterial Wall Ultrasound Images , 2010, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.