3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images

Abstract Our earlier study developed a computerized method, based on fuzzy connected object delineation principles and algorithms, for artery and vein separation in contrast enhanced Magnetic Resonance Angiography (CE-MRA) images. This paper reports its current development—a software package—for routine clinical use. The software package, termed 3DVIEWNIX-AVS, consists of the following major operational parts: (1) converting data from DICOM3 to 3DVIEWNIX format, (2) previewing slices and creating VOI and MIP Shell, (3) segmenting vessel, (4) separating artery and vein, (5) shell rendering vascular structures and creating animations. This package has been applied to EPIX Medical Inc's CE-MRA data (AngioMark MS-325). One hundred and thirty-five original CE-MRA data sets (of 52 patients) from 6 hospitals have been processed. In all case studies, unified parameter settings produce correct artery–vein separation. The current package is running on a Pentium PC under Linux and the total computation time per study is about 3 min. The strengths of this software package are (1) minimal user interaction, (2) minimal anatomic knowledge requirements on human vascular system, (3) clinically required speed, (4) free entry to any operational stages, (5) reproducible, reliable, high quality of results, and (6) cost effective computer implementation. To date, it seems to be the only software package (using an image processing approach) available for artery and vein separation of the human vascular system for routine use in a clinical setting.

[1]  Jayaram K. Udupa,et al.  3D MR angiographic visualization and artery-vein separation , 1999, Medical Imaging.

[2]  Dewey Odhner,et al.  3DVIEWNIX: an open, transportable, multidimensional, multimodality, multiparametric imaging software system , 1994, Medical Imaging.

[3]  A E Stillman,et al.  Ultrasmall superparamagnetic iron oxide to enhance MRA of the renal and coronary arteries: studies in human patients. , 1996, Journal of computer assisted tomography.

[4]  J F Debatin,et al.  Human aorta: preliminary results with virtual endoscopy based on three-dimensional MR imaging data sets. , 1996, Radiology.

[5]  Jayaram K. Udupa,et al.  Shell rendering , 1993, IEEE Computer Graphics and Applications.

[6]  J. Udupa,et al.  Iterative relative fuzzy connectedness and object definition: theory, algorithms, and applications in image segmentation , 2000, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737).

[7]  K. Thuomas,et al.  MR Angiography of Abdominal and Peripheral Arteries , 1996, Acta radiologica.

[8]  R. Dolan,et al.  MS-325: albumin-targeted contrast agent for MR angiography. , 1998, Radiology.

[9]  Shuqun Zhang,et al.  Euclidean distance transform by stack filters , 1999, IEEE Signal Processing Letters.

[10]  Jayaram K. Udupa,et al.  An ultra-fast user-steered image segmentation paradigm: live wire on the fly , 2000, IEEE Transactions on Medical Imaging.

[11]  Emmanuelle Canet,et al.  Contrast‐enhanced 3D‐TOF MRA of peripheral vessels: Intravascular versus extracellular MR contrast media , 1998, Journal of magnetic resonance imaging : JMRI.

[12]  Sebastian Stier,et al.  Extraction of line properties based on direction fields , 1996, IEEE Trans. Medical Imaging.

[13]  Jayaram K. Udupa,et al.  Scale-based filtering of medical images , 2000, Medical Imaging: Image Processing.

[14]  Gunilla Borgefors,et al.  On Digital Distance Transforms in Three Dimensions , 1996, Comput. Vis. Image Underst..

[15]  Jayaram K. Udupa,et al.  Separation of artery and vein in contrast-enhanced MRA images , 2000, Medical Imaging.

[16]  R S Balaban,et al.  Magnetization transfer contrast in MR imaging of the heart. , 1991, Radiology.

[17]  K. Thuomas,et al.  MR Angiography of Abdominal and Peripheral Arteries , 1996 .

[18]  N M Rofsky,et al.  Gadolinium-enhanced body MR venography with subtraction technique. , 1997, AJR. American journal of roentgenology.

[19]  Max A. Viergever,et al.  Enhanced Artery Visualization in Blood Pool MRA: Results in the Peripheral Vasculature , 1999, IPMI.

[20]  Jayaram K. Udupa,et al.  A 3D generalization of user-steered live-wire segmentation , 2000, Medical Image Anal..

[21]  Jayaram K. Udupa,et al.  User-Steered Image Segmentation Paradigms: Live Wire and Live Lane , 1998, Graph. Model. Image Process..

[22]  Jayaram K. Udupa,et al.  3DVIEWNIX-AVS: a software package for separate visualization of arteries and veins in CE-MRA images , 2001, SPIE Medical Imaging.

[23]  C. Paschal,et al.  Variablemangle uniform signal excitation (vuse) for threel dimensional time‐of‐flight MR angiography , 1995, Journal of magnetic resonance imaging : JMRI.

[24]  Supun Samarasekera,et al.  Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation , 1996, CVGIP Graph. Model. Image Process..

[25]  Jayaram K. Udupa,et al.  Artery-vein separation via MRA-An image processing approach , 2001, IEEE Transactions on Medical Imaging.

[26]  D C Peters,et al.  Steady-state and dynamic MR angiography with MS-325: initial experience in humans. , 1998, Radiology.

[27]  Jayaram K. Udupa,et al.  Scale-Based Fuzzy Connected Image Segmentation: Theory, Algorithms, and Validation , 2000, Comput. Vis. Image Underst..

[28]  M. Prince.  Gadolinium-enhanced MR aortography. , 1990, Radiology.