Shape-driven segmentation of the arterial wall in intravascular ultrasound images

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a non-parametric probability density based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach

Computer Vision Techniques for Transcatheter Intervention

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area

Image and Signal Processing in Intravascular Ultrasound

Intravascular ultrasound (rvUS) is a new imaging mOdality providing real-time, crosssectional, high-resolution images of the arterial lumen and vessel wall. In contrast to conventional x-ray angiography that only displays silhouette views of the vessel lumen, IVUS imaging permits visualization of lesion morphology and accurate measurements of arterial cross-sectional dimensions in patients. These unique capabilities have led to many important clinical applications including quantitative assessment of the severity, restenosis, progression of atherosclerosis, selection and guidance of catheterbased therapeutic procedures and short- and long-term evaluation of the outcome of an intravascular intervention. Like the progress of other medial imaging modalities, the advent of IVUS techniques has brought in new challenges in the field of signal and image processing. Quantitative analysis of IVUS images requires the identification of arterial structures such as the lumen and plaque within an image. Manual contour tracing is well known to be time consuming and subjective. Development of an automated contour detection method may improve the reproducibility of quantitative IVUS and avoid a tedious manual procedure. Computerized three-dimensional (3D) reconstruction of an IVUS image series may extend the tomographic data to a more powerful volumetric assessment of the vessel segment. Obviously, this could not be achieved without the advance of 3D image processing techniques. Furthermore, it is demonstrated that processing of the original radio frequency (RF) echo signals provides an efficient means to improve the IVUS image quality as well as a new approach to extract volumetric flow information. The goals of the studies reported in this thesis are therefore directed toward development of video image and RF signal processing techniques for image enhancement, automated contour detection, 3D reconstruction and flow imaging. In this chapter several IVUS scanning mechanisms and some background information about ultrasonic imaging are briefly introduced. The principles of different video-based contour detection approaches and examples of contour detection in echocardiograms are discussed. Subsequently, applications of RF analysis in IVUS images are reviewed, followed by the scope of this thesis in the final part

Intravascular Ultrasound

Intravascular ultrasound (IVUS) is a cardiovascular imaging technology using a specially designed catheter with a miniaturized ultrasound probe for the assessment of vascular anatomy with detailed visualization of arterial layers. Over the past two decades, this technology has developed into an indispensable tool for research and clinical practice in cardiovascular medicine, offering the opportunity to gather diagnostic information about the process of atherosclerosis in vivo, and to directly observe the effects of various interventions on the plaque and arterial wall. This book aims to give a comprehensive overview of this rapidly evolving technique from basic principles and instrumentation to research and clinical applications with future perspectives