Biomedical subjects

James C Gee

Publications and source records attributed to James C Gee.

13 recordsLinked to original sources

PubMed2006

Pulmonary nodule detection in CT images with quantized convergence index filter.

A novel filter termed quantized convergence index filter (QCI filter) that is capable of enhancing the conspicuity of rounded lesions is proposed as part of a CAD (computer-aided diagnosis) scheme for detecting pulmonary nodules in computed tomography (CT) images. In this filter and its predecessor, the convergence index filter (CI filter), the output at a pixel represents the degree of convergence toward the pixel shown by the directions of gray-level gradients at surrounding pixels. The QCI filter and the CAD scheme were evaluated using five clinical datasets containing 50 nodules. With the support region of 9 x 9 pixels, the QCI filter showed more selective response to the nodules than the CI filter. In the CAD scheme, intermediate nodule candidates are generated based on the QCI filter output and then classified using linear discriminant analysis of eight features that are attributed to each intermediate nodule candidate. The QCI filter output level itself was used as one of the features. The scheme achieved a sensitivity of 90% with 1.67 false positives per slice. The QCI filter output level was most effective among the features in correctly classifying intermediate nodule candidates. The QCI filter is promising as a tool of preprocessing for automated pulmonary nodule detection in CT images.

Algorithms↗

PubMed2006

User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability.

Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes the methods and software engineering philosophy behind this new tool and provides the results of validation experiments performed in the context of an ongoing child autism neuroimaging study. The validation establishes SNAP intrarater and interrater reliability and overlap error statistics for the caudate nucleus and finds that SNAP is a highly reliable and efficient alternative to manual tracing. Analogous results for lateral ventricle segmentation are provided.

Brain↗

PubMed2005

Lagrangian frame diffeomorphic image registration: Morphometric comparison of human and chimpanzee cortex.

We develop a novel Lagrangian reference frame diffeomorphic image and landmark registration method. The algorithm uses the fixed Langrangian reference frame to define the map between coordinate systems, but also generates and stores the inverse map from the Eulerian to the Lagrangian frame. Computing both maps allows facile computation of both Eulerian and Langrangian quantities. We apply this algorithm to estimating a putative evolutionary change of coordinates between a population of chimpanzee and human cortices. Inter-species functional homologues fix the map explicitly, where they are known, while image similarities guide the alignment elsewhere. This map allows detailed study of the volumetric change between chimp and human cortex. Instead of basing the inter-species study on a single species atlas, we diffeomorphically connect the mean shape and intensity templates for each group. The human statistics then map diffeomorphically into the space of the chimpanzee cortex providing a comparison between species. The population statistics show a significant doubling of the relative prefrontal lobe size in humans, as compared to chimpanzees.

Algorithms↗

PubMed2005

Deformable registration of diffusion tensor MR images with explicit orientation optimization.

In this paper we present a novel deformable registration algorithm for diffusion tensor (DT) MR images that enables explicit analytic optimization of tensor reorientation. The optimization seeks a piecewise affine transformation that divides the image domain into uniform regions and transforms each of them affinely. The objective function captures both the image similarity and the smoothness of the transformation across region boundaries. The image similarity enables explicit orientation optimization by incorporating tensor reorientation, which is necessary for warping DT images. The objective function is formulated in a way that allows explicit implementation of analytic derivatives to drive fast and accurate optimization using the conjugate gradient method. The optimal transformation is hierarchically refined in a subdivision framework. A comparison with affine registration for inter-subject normalization of 8 subjects shows that our algorithm improves the alignment of manually segmented white matter structures (corpus callosum and cortio-spinal tracts).

Algorithms↗

PubMed2005

Towards a dynamic model of pulmonary parenchymal deformation: evaluation of methods for temporal reparameterization of lung data.

We approach the problem of temporal reparameterization of dynamic sequences of lung MR images. In earlier work, we employed capacity-based reparameterization to co-register temporal sequences of 2-D coronal images of the human lungs. Here, we extend that work to the evaluation of a ventilator-acquired 3-D dataset from a normal mouse. Reparameterization according to both deformation and lung volume is evaluated. Both measures provide results that closely approximate normal physiological behavior, as judged from the original data. Our ultimate goal is to be able to characterize normal parenchymal biomechanics over a population of healthy individuals, and to use this statistical model to evaluate lung deformation under various pathological states.

Algorithms↗

PubMed2005

Statistical modeling of shape and appearance using the continuous medial representation.

We describe a novel approach to combining shape and appearance features in the statistical analysis of structures in medical images. The continuous medial representation is used to relate these two types of features meaningfully. The representation imposes a shape-based coordinate system on structure interiors, in a way that uses the boundary normal as one of the coordinate axes, while providing an onto and nearly one-to-one parametrization. This coordinate system is used to sample image intensities in the context of shape. The approach is illustrated by the principal components analysis of the shape and appearance of the hippocampus in T1-weighted MRI from a schizophrenia study.

Algorithms↗

PubMed2005

Towards a model of lung biomechanics: pulmonary kinematics via registration of serial lung images.

The lungs are highly elastic organs, composed of a variety of structures: vasculature, airways and parenchyma. The unique mechanical properties of each of these structures form the composite material of the lung. Numerous pulmonary diseases affect these material properties. Clinically, these structural changes cannot be directly quantified. However, medical imaging modalities such as computed tomography and magnetic resonance imaging can be used to observe lung morphology. It would be helpful to be able to correlate regional morphological changes with changes in pulmonary function. We present an approach toward the quantification of pulmonary deformation via non-rigid registration of serial MR images of the lung using the variational framework implemented in the Insight toolkit. Conventional registration methods, as exemplified by a finite element implementation of the classic elastic matching technique, are shown to perform well over a set of vascular landmarks in the measurement of lung motion. This performance is maintained in an augmented system, which combines inhomogeneous material properties with the use of domain discretizations tailored to reflect the apparent geometry within the image and to reduce background effects. These adaptations lay the groundwork for biomechanical modeling of the lung using the finite element method.

Algorithms↗

PubMed2005

A multilevel analysis of cognitive dysfunction and psychopathology associated with chromosome 22q11.2 deletion syndrome in children.

We present a multilevel approach to developing potential explanations of cognitive impairments and psychopathologies common to individuals with chromosome 22q11.2 deletion syndrome. Results presented support our hypothesis of posterior parietal dysfunction as a central determinant of characteristic visuospatial and numerical cognitive impairments. Converging data suggest that brain development anomalies, primarily tissue reductions in the posterior brain and changes to the corpus callosum, may affect parietal connectivity. Further findings indicate that dysfunction in "frontal" attention systems may explain some executive cognition impairments observed in affected children, and that there may be links between these domains of cognitive function and some of the serious psychiatric conditions, such as attention-deficit/hyperactivity disorder, autism, and schizophrenia, that have elevated incidence rates in the syndrome. Linking the neural structure and the cognitive processing levels in this way enabled us to develop an elaborate structure/function mapping hypothesis for the impairments that are observed. We show also, that in the case of the catechol-O-methyltransferase gene, a fairly direct relationship between gene expression, cognitive function, and psychopathology exists in the affected population. Beyond that, we introduce the idea that variation in other genes may further explain the phenotypic variation in cognitive function and possibly the anomalies in brain development.

Attention↗

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↗

PubMedDate not supplied

The correlation of cognitive decline with frontotemporal dementia induced annualized gray matter loss using diffeomorphic morphometry.

This study uses large deformation medical image registration to analyze, in a disease-specific normalized space, the annual rate of gray matter atrophy caused by frontotemporal dementia (FTD) and its correlation with cognitive decline. The analysis consists of three parts. First, a labeled structural MRI atlas is deformed into the shape of an average FTD brain. Second, annualized FTD-related atrophy of gray matter structures is estimated for each patient in the database. Third, the group-wise annualized atrophy rate caused by FTD is correlated, for each gray matter voxel, with declining performance on cognitive tests. This study gives insight into the relationship between FTD-related progressive cortical atrophy and loss in cognitive function.

Aged↗