A state of the art review on intima-media thickness (IMT) measurement and wall segmentation techniques for carotid ultrasound.
Last 10 years have witnessed the growth of many computer applications for the segmentation of the vessel wall in ultrasound imaging. Epidemiological studies showed that the thickness of the major arteries is an early and effective marker of onset of cardiovascular diseases. Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology. This review is an attempt to discuss the most performing methodologies that have been developed so far to perform computer-based segmentation and intima-media thickness (IMT) measurement of the carotid arteries in ultrasound images. First we will present the rationale and the clinical relevance of computer-based measurements in clinical practice, followed by the challenges that one has to face when approaching the segmentation of ultrasound vascular images. The core of the paper is the presentation, discussion, benchmarking and evaluation of different segmentation techniques, including: edge-detection, active contours, dynamic programming, local statistics, Hough transform, statistical modeling, and integration of these approaches. Also, we will discuss and compare the different performance metrics that have been proposed and used to perform the validation. Best performing user-dependent techniques show an average IMT measurement error of about 1μm when compared to human tracings [57], whereas completely automated techniques show errors of about 10μm. The review ends with a discussion about the current standards in carotid wall segmentation and in an overview of the future perspectives, which may include the adoption of advanced and intelligent strategies to let the computer technique measure the IMT in the image portion where measurement is more reliable.
Molinari
Filippo
F
Biolab, Department of Electronics, Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, Italy. filippo.molinari@polito.it
Zeng
Guang
G
Suri
Jasjit S
JS
D000465:Algorithms; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000473:pathology*; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D012016:Reference Values; D018570:Risk Assessment; D012984:Software; D017539:Tunica Intima / Q000000981:diagnostic imaging / Q000473:pathology*; D017540:Tunica Media / Q000000981:diagnostic imaging / Q000473:pathology*; D014463:Ultrasonography / Q000295:instrumentation* / Q000379:methods