TY - JOUR T1 - 3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images JF - COMPUTERIZED MEDICAL IMAGING AND GRAPHICS Y1 - 2003 A1 - Tianhu Lei A1 - Jayaram K Udupa A1 - Dewei Odhner A1 - László Gábor Nyúl A1 - Punam K Saha AB - Our earlier study developed a computerized method, based onfuzzy 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. VL - 27 SN - 0895-6111 IS - 5 N1 - UT: 000184800600003ScopusID: 0038122922doi: 10.1016/S0895-6111(03)00029-6 JO - COMPUT MED IMAG GRAP ER - TY - JOUR T1 - Incorporating a measure of local scale in voxel-based 3-D image registration JF - IEEE TRANSACTIONS ON MEDICAL IMAGING Y1 - 2003 A1 - László Gábor Nyúl A1 - Jayaram K Udupa A1 - Punam K Saha AB - We present a new class of approaches for rigid-body registrationand their evaluation in studying multiple sclerosis (MS) via multiprotocol magnetic resonance imaging (MRI). Three pairs of rigid-body registration algorithms were implemented, using cross-correlation and mutual information (MI), operating on original gray-level images, and utilizing the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local "scale" value assigned to it, defined as the radius of the largest ball centered at the voxel with homogeneous intensities. Three-dimensional image data of the head were acquired from ten MS patients for each of six MRI protocols. Images in some of the protocols were acquired in registration. The registered pairs were used as ground truth. Accuracy and consistency of the six registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no "best" method. For medium misregistration, the method using MI, for small add large misregistration the method using normalized cross-correlation performs best. For high-resolution data the correlation method and for low-resolution data the MI method, both using the original gray-level images, are the most consistent. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have potential for image registration as suggested by this work. VL - 22 SN - 0278-0062 IS - 2 N1 - UT: 000182391600009ScopusID: 0038398636doi: 10.1109/TMI.2002.808358 JO - IEEE T MED IMAGING ER - TY - CHAP T1 - Task-specific comparison of 3D image registration methods T2 - Medical Imaging 2001: Image Processing Y1 - 2001 A1 - László Gábor Nyúl A1 - Jayaram K Udupa A1 - Punam K Saha ED - Milan Sonka ED - Kenneth M Hanson AB - We present a new class of approaches for rigid-body registrationand their evaluation in studying Multiple Sclerosis via multi protocol MRI. Two pairs of rigid-body registration algorithms were implemented, using cross- correlation and mutual information, operating on original gray-level images and on the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local scale value assigned to it, defined as the radius of the largest sphere centered at the voxel with homogeneous intensities. 3D data of the head were acquired from 10 MS patients using 6 MRI protocols. Images in some of the protocols have been acquired in registration. The co-registered pairs were used as ground truth. Accuracy and consistency of the 4 registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no best method. For medium and large misregistration, methods using mutual information, for small misregistration, and for the consistency tests, correlation methods using the original gray- level images give the best results. We have previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have considerable potential for image registration as suggested by this work. JF - Medical Imaging 2001: Image Processing PB - SPIE CY - Bellingham; Washington N1 - ScopusID: 0034843423doi: 10.1117/12.431044 ER -