Publications by Year: 2004

Hoyte L, Jakab M, Warfield SK, Shott S, Flesh G, Fielding JR. Levator Ani Thickness Variations in Symptomatic and Asymptomatic Women using Magnetic Resonance-based 3-dimensional Color Mapping. Am J Obstet Gynecol. 2004;191 (3) :856-61.Abstract
OBJECTIVE: This study was undertaken to develop and test a 3-dimensional (3D) color thickness mapping technique on levator ani imaged with magnetic resonance imaging (MRI). METHODS: Supine MRI datasets from 30 women were studied: 10 asymptomatic, 10 with urodynamic stress incontinence, and 10 with pelvic organ prolapse. Levators were manually outlined, and thickness mapping applied. Three-dimensional models were colored topographically, reflecting levator thickness. Thickness and occurrences of absent levator substance (gaps) were compared across the 3 groups, using nonparametric statistical tests. RESULTS: Color thickness mapping was successful in all subjects. There were statistically significant differences in thickness and gap percentages among the 3 groups of women, with thicker, bulkier levators in asymptomatic women, compared with women with prolapse or urodynamic stress incontinence. CONCLUSION: Color thickness mapping is feasible. It may be used to compare levators in symptomatic and asymptomatic women, to study relationships between levator thickness and pelvic floor dysfunction. This technique can be used in larger studies for hypothesis testing.
Park H-J, Kubicki M, Westin C-F, Talos I-F, Brun A, Peiper S, Kikinis R, Jolesz FA, McCarley RW, Shenton ME. Method for Combining Information from White Matter Fiber Tracking and Gray Matter Parcellation. AJNR Am J Neuroradiol. 2004;25 (8) :1318-24.Abstract
We introduce a method for combining fiber tracking from diffusion-tensor (DT) imaging with cortical gray matter parcellation from structural high-spatial-resolution 3D spoiled gradient-recalled acquisition in the steady state images. We applied this method to a tumor case to determine the impact of the tumor on white matter architecture. We conclude that this new method for combining structural and DT imaging data is useful for understanding cortical connectivity and the localization of fiber tracts and their relationship with cortical anatomy and brain abnormalities.
Tsai A, Wells III WM, Tempany CM, Grimson EWL, Willsky AS. Mutual Information in Coupled Multi-shape Model for Medical Image Segmentation. Med Image Anal. 2004;8 (4) :429-45.Abstract

This paper presents extensions which improve the performance of the shape-based deformable active contour model presented earlier in [IEEE Conf. Comput. Vision Pattern Recog. 1 (2001) 463] for medical image segmentation. In contrast to that previous work, the segmentation framework that we present in this paper allows multiple shapes to be segmented simultaneously in a seamless fashion. To achieve this, multiple signed distance functions are employed as the implicit representations of the multiple shape classes within the image. A parametric model for this new representation is derived by applying principal component analysis to the collection of these multiple signed distance functions. By deriving a parametric model in this manner, we obtain a coupling between the multiple shapes within the image and hence effectively capture the co-variations among the different shapes. The parameters of the multi-shape model are then calculated to minimize a single mutual information-based cost criterion for image segmentation. The use of a single cost criterion further enhances the coupling between the multiple shapes as the deformation of any given shape depends, at all times, upon every other shape, regardless of their proximity. We found that this resulting algorithm is able to effectively utilize the co-dependencies among the different shapes to aid in the segmentation process. It is able to capture a wide range of shape variability despite being a parametric shape-model. And finally, the algorithm is robust to large amounts of additive noise. We demonstrate the utility of this segmentation framework by applying it to a medical application: the segmentation of the prostate gland, the rectum, and the internal obturator muscles for MR-guided prostate brachytherapy.

Dickhaus CF, Burghart C, Tempany CM, D'Amico A, Haker S, Kikinis R, Woern H. Workflow Modeling and Analysis of Computer Guided Prostate Brachytherapy under MR Imaging Control. Stud Health Technol Inform. 2004;98 :72-4.Abstract

We demonstrate that classical Business Process Reengineering (BPR) methods can be successfully applied to Computer Aided Surgery while increasing safety and efficiency of the overall procedure through an integrated Workflow Management System. Computer guided Prostate Brachytherapy, as a sophisticated treatment by an interdisciplinary team, is perfectly suited to apply our method. Detailed suggestions for improvement of the whole procedure could be derived by our modified BPR method.