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.

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.^

Evaluation of PRESAGE® dosimeters for brachytherapy sources and the 3D dosimetry and characterization of the new AgX100 125I seed model

With continuous new improvements in brachytherapy source designs and techniques, method of 3D dosimetry for treatment dose verifications would better ensure accurate patient radiotherapy treatment. This study was aimed to first evaluate the 3D dose distributions of the low-dose rate (LDR) Amersham 6711 OncoseedTM using PRESAGE® dosimeters to establish PRESAGE® as a suitable brachytherapy dosimeter. The new AgX100 125I seed model (Theragenics Corporation) was then characterized using PRESAGE® following the TG-43 protocol. PRESAGE® dosimeters are solid, polyurethane-based, 3D dosimeters doped with radiochromic leuco dyes that produce a linear optical density response to radiation dose. For this project, the radiochromic response in PRESAGE® was captured using optical-CT scanning (632 nm) and the final 3D dose matrix was reconstructed using the MATLAB software. An Amersham 6711 seed with an air-kerma strength of approximately 9 U was used to irradiate two dosimeters to 2 Gy and 11 Gy at 1 cm to evaluate dose rates in the r=1 cm to r=5 cm region. The dosimetry parameters were compared to the values published in the updated AAPM Report No. 51 (TG-43U1). An AgX100 seed with an air-kerma strength of about 6 U was used to irradiate two dosimeters to 3.6 Gy and 12.5 Gy at 1 cm. The dosimetry parameters for the AgX100 were compared to the values measured from previous Monte-Carlo and experimental studies. In general, the measured dose rate constant, anisotropy function, and radial dose function for the Amersham 6711 showed agreements better than 5% compared to consensus values in the r=1 to r=3 cm region. The dose rates and radial dose functions measured for the AgX100 agreed with the MCNPX and TLD-measured values within 3% in the r=1 to r=3 cm region. The measured anisotropy function in PRESAGE® showed relative differences of up to 9% with the MCNPX calculated values. It was determined that post-irradiation optical density change over several days was non-linear in different dose regions, and therefore the dose values in the r=4 to r=5 cm regions had higher uncertainty due to this effect. This study demonstrated that within the radial distance of 3 cm, brachytherapy dosimetry in PRESAGE® can be accurate within 5% as long as irradiation times are within 48 hours.