Visualization of the internal carotid artery using MRA images.

A virtual angioscopy system is implemented to visualize the inside of the internal carotid artery (ICA) for qualitative assessment of carotid artery stenosis using magnetic resonance angiography (MRA) images. The carotid artery is one of the body regions not accessible by real optical endoscopy but can be visualized with virtual endoscopy. In order to visualize the carotid artery, it is segmented using the region-growing algorithm after locating the initial seed on the presegmented binary image. The ICA is separated from the external carotid artery (ECA) using a priori knowledge of the anatomic structure after bifurcation. A fly-through path is computed based on the medial axis transform (MAT) to automatically move the virtual camera from the common carotid artery (CCA) to the ICA. Considering interactive rendering speed and usability of standard graphic hardware, the surface-rendering algorithm with the perspective projection method is used to generate an endoscopic view of the ICA. In addition, the endoscopic view with the raycasting algorithm is provided for off-line navigation of the carotid artery. Virtual angioscopy is highly recommended as a diagnostic tool for identifying the specific location of the stenosis and for analyzing the stenosis qualitatively. The virtual angioscopy system for carotid artery will benefit radiological diagnostics, medical education, surgical planning and postoperative assessment.

[1]  Tim Morris,et al.  Computer Vision and Image Processing: 4th International Conference, CVIP 2019, Jaipur, India, September 27–29, 2019, Revised Selected Papers, Part I , 2020, CVIP.

[2]  Do-Yeon Kim,et al.  Computerized quantification of carotid artery stenosis using MRA axial images. , 2004, Magnetic resonance imaging.

[3]  Arnold W. M. Smeulders,et al.  Spectral Volume Rendering , 2000, IEEE Trans. Vis. Comput. Graph..

[4]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[5]  William E. Lorensen,et al.  Marching cubes: a high resolution 3D surface construction algorithm , 1996 .

[6]  H Rusinek,et al.  Volumetric rendering of MR images. , 1989, Radiology.

[7]  Jim R. Parker,et al.  Algorithms for image processing and computer vision , 1996 .

[8]  Andrew Mehnert,et al.  An improved seeded region growing algorithm , 1997, Pattern Recognit. Lett..

[9]  J. Wickham,et al.  Minimally Invasive Surgery: Future developments , 1994, BMJ.

[10]  W E Higgins,et al.  Automatic axis generation for virtual bronchoscopic assessment of major airway obstructions. , 2002, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[11]  R. Edelman,et al.  Magnetic resonance imaging (2) , 1993, The New England journal of medicine.

[12]  V Argiro,et al.  Perspective volume rendering of CT and MR images: applications for endoscopic imaging. , 1996, Radiology.

[13]  Ron Kikinis,et al.  Simulation of Endoscopy , 1995, CVRMed.

[14]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Alan Watt,et al.  3D Computer Graphics , 1993 .

[16]  Mark J. Carlotto,et al.  Histogram Analysis Using a Scale-Space Approach , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  W. Thies,et al.  When to operate in carotid artery disease. , 2000, American family physician.

[18]  B. Mintz,et al.  Diagnosis and treatment of carotid artery stenosis , 2000, The Journal of the American Osteopathic Association.

[19]  Dirk Bartz,et al.  Virtual voyage: interactive navigation in the human colon , 1997, SIGGRAPH.

[20]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[21]  Zhengrong Liang,et al.  3D virtual colonoscopy , 1995, Proceedings 1995 Biomedical Visualization.

[22]  Geoffrey McLennan,et al.  Image-guided endoscopy for lung-cancer assessment , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[23]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.