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James S Duncan

Publications and source records attributed to James S Duncan.

5 recordsLinked to original sources
PubMed2003

A unified non-rigid feature registration method for brain mapping.

This paper describes the design, implementation and results of a unified non-rigid feature registration method for the purposes of anatomical MRI brain registration. An important characteristic of the method is its ability to fuse different types of anatomical features into a single point-set representation. We demonstrate the application of the method using two different types of features: the outer cortical surface and major sulcal ribbons. Non-rigid registration of the combined feature point-sets is then performed using a new robust non-rigid point matching algorithm. The point matching algorithm implements an iterative joint clustering and matching (JCM) strategy which effectively reduces the computational complexity without sacrificing accuracy. We have conducted carefully designed synthetic experiments to gauge the effect of using different types of features either separately or together. A validation study examining the accuracy of non-rigid alignment of many brain structures is also presented. Finally, we present anecdotal results on the alignment of two subject MRI brain data.

Algorithms↗
PubMed2003

Entropy-based dual-portal-to-3-DCT registration incorporating pixel correlation.

For patient setup verification in external beam radiotherapy (EBRT) of prostate cancer, we developed an information theoretic registration framework, called the minimax entropy registration framework, to simultaneously and iteratively segment portal images and register them to three-dimensional (3-D) computed tomography (CT) image data. The registration framework has two steps, the max step and the min step, and evaluates appropriate entropies to estimate segmentations of the portal images and to find the transformation parameters. In the initial version of the algorithm (Bansal et al. 1999), we assumed image pixels to be independently distributed, an assumption not true in general. Thus, to better segment the portal images and to improve the accuracy of the estimated registration parameters, in this initial formulation of the problem, the correlation among pixel intensities is modeled using a one-dimensional Markov random process. Line processes are incorporated into the model to improve the estimation of segmentation of the portal images. In the max step, the principle of maximum entropy is invoked to estimate the probability distribution on the segmentations. The estimated distribution is then incorporated into the min step to estimate the registration parameters. Performance of the proposed framework is evaluated and compared to that of a mutual information-based registration algorithm using both simulated and real patient data. In the proposed registration framework, registration of the 3-D CT image and the portal images is guided by an estimated segmentation of the pelvic bone. However, as the prostate can move with respect to the pelvic structure, further localization of the prostate using ultrasound image data is required, an issue to be further explored in future.

Algorithms↗
PubMed2003

MRI and PET study of deficits in hippocampal structure and function in women with childhood sexual abuse and posttraumatic stress disorder.

OBJECTIVE: Animal studies have suggested that early stress is associated with alterations in the hippocampus, a brain area that plays a critical role in learning and memory. The purpose of this study was to measure both hippocampal structure and function in women with and without early childhood sexual abuse and the diagnosis of posttraumatic stress disorder (PTSD). METHOD: Thirty-three women participated in this study, including women with early childhood sexual abuse and PTSD (N=10), women with abuse without PTSD (N=12), and women without abuse or PTSD (N=11). Hippocampal volume was measured with magnetic resonance imaging in all subjects, and hippocampal function during the performance of hippocampal-based verbal declarative memory tasks was measured by using positron emission tomography in abused women with and without PTSD. RESULTS: A failure of hippocampal activation and 16% smaller volume of the hippocampus were seen in women with abuse and PTSD compared to women with abuse without PTSD. Women with abuse and PTSD had a 19% smaller hippocampal volume relative to women without abuse or PTSD. CONCLUSIONS: These results are consistent with deficits in hippocampal function and structure in abuse-related PTSD.

Adult↗
PubMed2002

Estimation of 3-D left ventricular deformation from medical images using biomechanical models.

The quantitative estimation of regional cardiac deformation from three-dimensional (3-D) image sequences has important clinical implications for the assessment of viability in the heart wall. We present here a generic methodology for estimating soft tissue deformation which integrates image-derived information with biomechanical models, and apply it to the problem of cardiac deformation estimation. The method is image modality independent. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely isotropic, linear-elastic model, which accounts for the muscle fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion, exhibit a high correlation with strains produced in the same animals using implanted markers. Further, they show good agreement with previously published results in the literature. This proposed method provides quantitative regional 3-D estimates of heart deformation.

Algorithms↗