Matthew Y. Wang

Vanderbilt University, Nashville, Michigan, United States

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Publications (8)1.58 Total impact

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    ABSTRACT: Objective: The primary objective of this study is to perform a blinded ewluation of a group of retrospective image registration techniques using s a gold standard a prospective, marker-bsed registration method. In order to ensure blindedness, all retrospective registrations were performed by participants who hl no knowledge of the gold-standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those which have hl the distortion correction applied, with that of the same images before rectification.
    09/2001;
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    ABSTRACT: Purpose: The primary objective of this study is to perform a blinded evaluation of a group of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method. To ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those that have had the distortion correction applied, with that of the same images before rectification. Method: Image volumes of three modalities (CT, MR, and PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs), i.e., areas in the brain that would commonly be areas of neurological interest. A VOI is defined in the MR image and its centroid c is determined. Then, the prospective registration is used to obtain the corresponding point c′ in CT or PET. To this point, the retrospective registration is then applied, producing c″ in MR. Statistics are gathered on the target registration error (TRE), which is the distance between the original point c and its corresponding point c″. Results: This article presents statistics on the TRE calculated for each registration technique in this study and provides a brief description of each technique and an estimate of both preparation and execution time needed to perform the registration. Conclusion: Our results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.
    Journal of Computer Assisted Tomography 06/1997; 21(4):554-568. · 1.58 Impact Factor
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    ABSTRACT: In this paper, we describe an extrinsic point-based, interactive image-guided neurosurgical system designed at Vanderbilt University as part of a collaborative effort among the departments of neurological surgery, computer science, and biomedical engineering. Multimodal image-to- image and image-to-physical registration is accomplished using implantable markers. Physical space tracking is accomplished with optical triangulation. We investigate the theoretical accuracy of point-based registration using numerical simulations, the experimental accuracy of our system using data obtained with a phantom, and the clinical accuracy of our system using data acquired in a prospective clinical trial by six neurosurgeons at four medical centers from 158 patients undergoing craniotomies to resect cerebral lesions. We can determine the position of our markers with an error of approximately 0.4 mm in x-ray computed tomography (CT) and magnetic resonance (MR) images and 0.3 mm in physical space. The theoretical registration error using four such markers distributed around the head in a configuration that is clinically practical is approximately 0.5 - 0.6 mm. The mean CT-physical registration error for the phantom experiments is 0.5 mm and for the clinical data obtained with rigid head fixation during scanning is 0.7 mm. The mean CT-MR registration error for the clinical data obtained without rigid head fixation during scanning is 1.4 mm, which is the highest mean error that we observed. These theoretical and experimental findings indicate that this system is an accurate navigational aid that can provide real-time feedback to the surgeon about anatomical structures encountered in the surgical field.
    Proc SPIE 01/1997; 16:447-462.
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    ABSTRACT: It is becoming increasingly common for surgical navigation systems to be used intraoperatively to enable the surgeon to ascertain his or her position within the patient with respect to features in registered preoperative images. These systems assume that the skull and its contents behave as a rigid body between imaging and surgery, and during surgery. We have used the ACUSTAR I surgical navigation system to measure shifts in the brain surface relative to the skull between imaging and surgery on five patients. The preoperative images are registered to the coordinates of the surgical localizer using four fiducial markers screwed into the outer table of the skull. The brain surface is delineated from preoperative MR images, and the distance between this surface and brain surface points recorded intraoperatively is calculated. The median shift of points on the brain surface ranged from 0.3 mm to 7.4 mm. In all cases, the direction of this shift corresponds to a sinking of the brain intraoperatively compared to its preoperative position. We consider possible changes in CNS volume that might account for these shifts.
    CVRMed-MRCAS'97, First Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery, Grenoble, France, March 19-22, 1997, Proceedings; 01/1997
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    ABSTRACT: The primary objective of this study is to perform a blinded evaluation of two groups of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method, and to compare the performance of one group with the other. In order to ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold-standard results until after their results had been submitted. Image volumes of three modalities—X-ray Computed Tomography (CT), Magnetic Resonance (MR), and Positron Emission Tomography (PET)—were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs). Our results indicate that the volume-based techniques in this study tended to give substantially more accurate and reliable results than the surface-based ones for the CT-to-MR registration tasks and slightly more accurate results for the PET-to-MR tasks. It was also apparent that all of the registration techniques we examined have the potential to produce satisfactory results much of the time but that visual inspection is necessary to guard against large errors.
    CVRMed-MRCAS'97, First Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery, Grenoble, France, March 19-22, 1997, Proceedings; 01/1997
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    ABSTRACT: Registration of medical images to each other and to physical space for the purposes of surgical planning and surgical navigation can be accomplished using externally attached fiducial markers. The accuracy of fiducial localization, that is, the accuracy of estimating the position of the marker's centroid, is extremely important because marker- based registration accuracy is proportional to localization accuracy. The traditional method of calculating the marker centroid using intensity weighting contains a serious logic flaw. This paper introduces a novel and efficient method for correcting this flaw. Theoretical analysis, computer simulation, and analysis of clinical images demonstrate the importance of this correction.
    Proc SPIE 01/1997;
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    ABSTRACT: An extrinsic point-based, interactive image-guided neurosurgical system has been designed at Vanderbilt in a collaborative effort between the Departments of Neurosurgery, Biomedical Engineering, and Computer Science. In this paper we investigate the theoretical accuracy of point-based registration using numerical simulations, the experimental accuracy of the system using data obtained with a phantom, and the clinical accuracy of the system using data from a prospective clinical trial. We demonstrate that the accuracy of the registration of CT and MR images to each other and to physical space (i.e. patient anatomy) using four implantable fiducial markers is millimetric. Keywords---Registration accuracy, image registration, point-based registration, fiducial markers, image-guided neurosurgery. Introduction Registration techniques quantitatively relate the information in two images by determining a one-to-one mapping between them. Stereotactic surgery and stereotactic radiosurgery requ...
    07/1995;
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    ABSTRACT: There is an increasing demand for accurate registration of CT and MR images for diagnosis and for surgical planning. One useful technique registers images using externally attached fiducial markers. Previous studies have shown that point-based registration accuracy depends on fiducial localization accuracy, that is, the accuracy with which the position of a marker centroid can be estimated. This paper investigates the dependence of localization accuracy on marker size. The investigation is based on computer simulations. Three shapes are evaluated-- a sphere, a cylinder, and a cube, each with similar dimensions. The results indicate that (1) the accuracy depends strongly on the ratio of marker size to voxel size and (2) the dependence is almost identical among the three shapes tested. The simulation results are shown to agree with results from clinical images.
    Proc SPIE 01/1995;