Biomedical subjects

James C Gee

Publications and source records attributed to James C Gee.

4 recordsLinked to original sources

PubMed2004

Geodesic estimation for large deformation anatomical shape averaging and interpolation.

The goal of this research is to promote variational methods for anatomical averaging that operate within the space of the underlying image registration problem. This approach is effective when using the large deformation viscous framework, where linear averaging is not valid, or in the elastic case. The theory behind this novel atlas building algorithm is similar to the traditional pairwise registration problem, but with single image forces replaced by average forces. These group forces drive an average transport ordinary differential equation allowing one to estimate the geodesic that moves an image toward the mean shape configuration. This model gives large deformation atlases that are optimal with respect to the shape manifold as defined by the data and the image registration assumptions. We use the techniques in the large deformation context here, but they also pertain to small deformation atlas construction. Furthermore, a natural, inherently inverse consistent image registration is gained for free, as is a tool for constant arc length geodesic shape interpolation. The geodesic atlas creation algorithm is quantitatively compared to the Euclidean anatomical average to elucidate the need for optimized atlases. The procedures generate improved average representations of highly variable anatomy from distinct populations.

Algorithms↗

PubMed2004

Structural shape characterization via exploratory factor analysis.

UNLABELLED: This article presents an exploratory factor analytic approach to morphometry in which a high-dimensional set of shape-related variables is examined with the purpose of finding clusters with strong correlation. This clustering can potentially identify regions that have anatomic significance and thus lend insight to knowledge discovery and morphometric investigations. METHODS: The information about regional shape is extracted by registering a reference image to a set of test images. Based on the displacement fields obtained form image registration, the amount of pointwise volume enlargement or reduction is computed and statistically analyzed with the purpose of extracting a reduced set of common factors. EXPERIMENTS: The effectiveness and robustness of the method is demonstrated in a study of gender-related differences of the human corpus callosum anatomy, based on a sample of 84 right-handed normal controls. RESULTS: The method is able to automatically partition the structure into regions of interest, in which the most relevant shape differences can be observed. The confidence of results is evaluated by analyzing the statistical fit of the model and compared to previous experimental works.

Anthropometry↗

PubMed2003

Voxelwise mapping of magnetic resonance ventilation-perfusion ratio in a porcine model by multimodality registration: technical note.

RATIONALE AND OBJECTIVES: The purpose of this study was to demonstrate the construction of voxelwise ventilation-perfusion (V/Q) ratio maps in a porcine model by nonrigidly aligning the respective ventilation and perfusion images using a multimodality registration algorithm. MATERIALS AND METHODS: The first-pass contrast agent technique for a blood flow map and 3He used for ventilation imaging were performed using a normal porcine model. The registered 3He-ventilation image was then aligned to the blood flow map using a multimodality registration algorithm. The voxelwise V/Q ratios were calculated by dividing the registered 3He-ventilation image by the blood flow map. The V/Q ratios were also semi-logarithmically scatter-plotted against the number of voxels. RESULTS: From perfusion magnetic resonance images, a voxel-by-voxel blood flow map was produced. Registered 3He ventilation image was successfully obtained as well as V/Q ratio map. Plots of the V/Q ratios obtained by this registration approach were similar to the logarithmic normal distribution. CONCLUSION: Registration of MR perfusion and ventilation images can potentially enable quantitative evaluation of regional pulmonary function and thus yield deeper insight into the physiology and pathophysiology of the lung.

Animals↗

PubMed2002

Sexual dimorphism in the corpus callosum: a characterization of local size variations and a classification driven approach to morphometry.

We present two complementary quantitative approaches to the problem of characterizing morphometric variations between two distinct populations. The case presented focuses solely on local size variations, but the general method can easily be applied to other scalar morphometric quantities. The first method uses a statistical parametric map (SPM) to ascertain a P value, which indicates whether any statistically significant differences exist between the populations. The second method focuses on finding the best single measurement which can be used for classifying the two populations. For our case study midsagittal cross sections of the corpora callosa from a population of normal males and females are nonrigidly registered (spatially normalized) to an atlas. The resulting deformations are then used to ascertain (i) whether there are any statistically significant differences between the populations and (ii) whether these differences allow one to perform classification. We make use of the Jacobian of the deformation field and normalize it to account for overall volume changes allowing us to focus on differences which are more related to morphometry than scale. From the (SPM) approach to the problem we find evidence of statistically significant differences in the morphology between the populations. Using a linear discriminant function we find that these differences do not appear to be useful for classification. Thus, this dataset provides an example of how statistically significant effects may not be of much diagnostic value. They may be of interest to the research community, but of little value to the clinician.

Adult↗