Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

Telemedicine Distance Mentoring of Healthcare Students

The healthcare system is facing a challenge similar to other industries in maintaining an adequately trained home care workforce in a time when government funding for educational geriatrics programs is limited, and academic centers are emphasizing faculty productivity that may limit their time dedicated to teaching and training healthcare students. [See PDF for complete abstract]

Spatial analysis of water body distance and West Nile Virus human cases in Houston, TX

West Nile Virus (WNV) is an arboviral disease that has affected hundreds of residents in Harris County, Texas since its introduction in 2002. Persistent infection, lingering sequelae and other long-term symptoms of patients reaffirm the need for prevention of this important vector-borne disease. This study aimed to determine if living within 400m of a water body increases one’s odds of infection with WNV. Additionally, we wanted to determine if one’s proximity to a particular water type or water body source increased one’s odds of infection with WNV.^ 145 cases’ addresses were abstracted from the initial interview and consent records from a cohort of patients (Epidemiology of Arboviral Encephalitis in Houston study, HSC-SPH-03-039). After applying inclusion criteria, 140 cases were identified for analysis. 140 controls were selected for analysis using a population proportionate to size model and US Census Bureau data. MapMarker USA v14 was used to geocode the cases’ addresses. Both cases’ and controls’ coordinates were uploaded onto a Harris County water shapefile in MapInfo Professional v9.5.1. Distance in meters to the closest water source, closest water source type, and closest water source name were recorded.^ Analysis of Variance (p=0.329, R2 = 0.0034) indicated no association between water body distance and risk of WNV disease. Living near a creek (x2 = 11.79, p < 0.001), or the combined group of creek and gully (x 2 = 14.02, p < 0.001) were found to be strongly associated with infection of WNV. Living near Cypress Creek and its feeders (x2 = 15.2, p < 0.001) was found to be strongly associated with WNV infection. We found that creek and gully habitats, particularly Cypress Creek, were preferential for the local disease transmitting Culex quinquefasciatus and reservoir avian population.^