Comparative analysis of two techniques for detection and segmentation of moving bodies

This paper makes a comparative analysis of results produced by the application of two techniques for the detection and segmentation of bodies in motion captured in images sequence, namely: 1) technique based on the temporal average of the values of each pixel recorded in N consecutive image frames and, 2) technique based on historical values associated with pixels recorded in different frames of an image sequence.

Does normalized signal intensity of cervical discs on T2 weighted MRI images change in whiplash patients?

PURPOSE We tested the hypothesis that whiplash trauma leads to changes of the signal intensity of cervical discs in T2-weighted images. METHODS AND MATERIALS 50 whiplash patients (18-65 years) were examined within 48h after motor vehicle accident, and again after 3 and 6 months and compared to 50 age- and sex-matched controls. Signal intensity in ROI's of the discs at the levels C2/3 to C7/T1 and the adjacent vertebral bodies were measured on sagittal T2 weighted MR images and normalized using the average of ROI's in fat tissue. The contrast between discs and both adjacent vertebrae was calculated and disc degeneration was graded by the Pfirrmann-grading system. RESULTS Whiplash trauma did not have a significant effect on the normalized signals from discs and vertebrae, on the contrast between discs and adjacent vertebrae, or on the Pfirrmann grading. However, the contrast between discs and adjacent vertebrae and the Pfirrmann grading showed a strong correlation. In healthy volunteers, the contrast between discs and adjacent vertebrae and Pfirrmann grading increased with age and was dependent on the disc level. CONCLUSION We could not find any trauma related changes of cervical disc signal intensities. Normalized signals of discs and Pfirrmann grading changed with age and varied between disc levels with the used MR sequence.

Zone design of specific sizes using adaptive additively weighted voronoi diagrams

Territory or zone design processes entail partitioning a geographic space, organized as a set of areal units, into different regions or zones according to a specific set of criteria that are dependent on the application context. In most cases, the aim is to create zones of approximately equal sizes (zones with equal numbers of inhabitants, same average sales, etc.). However, some of the new applications that have emerged, particularly in the context of sustainable development policies, are aimed at defining zones of a predetermined, though not necessarily similar, size. In addition, the zones should be built around a given set of seeds. This type of partitioning has not been sufficiently researched; therefore, there are no known approaches for automated zone delimitation. This study proposes a new method based on a discrete version of the adaptive additively weighted Voronoi diagram that makes it possible to partition a two-dimensional space into zones of specific sizes, taking both the position and the weight of each seed into account. The method consists of repeatedly solving a traditional additively weighted Voronoi diagram, so that each seed?s weight is updated at every iteration. The zones are geographically connected using a metric based on the shortest path. Tests conducted on the extensive farming system of three municipalities in Castile-La Mancha (Spain) have established that the proposed heuristic procedure is valid for solving this type of partitioning problem. Nevertheless, these tests confirmed that the given seed position determines the spatial configuration the method must solve and this may have a great impact on the resulting partition.

Background foreground segmentation with RGB-D Kinect data: An efficient combination of classifiers

Low cost RGB-D cameras such as the Microsoft’s Kinect or the Asus’s Xtion Pro are completely changing the computer vision world, as they are being successfully used in several applications and research areas. Depth data are particularly attractive and suitable for applications based on moving objects detection through foreground/background segmentation approaches; the RGB-D applications proposed in literature employ, in general, state of the art foreground/background segmentation techniques based on the depth information without taking into account the color information. The novel approach that we propose is based on a combination of classifiers that allows improving background subtraction accuracy with respect to state of the art algorithms by jointly considering color and depth data. In particular, the combination of classifiers is based on a weighted average that allows to adaptively modifying the support of each classifier in the ensemble by considering foreground detections in the previous frames and the depth and color edges. In this way, it is possible to reduce false detections due to critical issues that can not be tackled by the individual classifiers such as: shadows and illumination changes, color and depth camouflage, moved background objects and noisy depth measurements. Moreover, we propose, for the best of the author’s knowledge, the first publicly available RGB-D benchmark dataset with hand-labeled ground truth of several challenging scenarios to test background/foreground segmentation algorithms.

What is the Impact of the Underserved Pathway program on Entering an Underserved Family Medicine Residency? A Comparison of Three Approaches for Estimating the Average Treatment Effect

Thesis (Master's)--University of Washington, 2016-06

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.

Moving toward change: Institutionalizing reform through implementation of the Learning Assistant model and Open Source Tutorials

Florida International University has undergone a reform in the introductory physics classes by focusing on the laboratory component of these classes. We present results from the secondary implementation of two research-based instructional strategies: the implementation of the Learning Assistant model as developed by the University of Colorado at Boulder and the Open Source Tutorial curriculum developed at the University of Maryland, College Park. We examine the results of the Force Concept Inventory (FCI) for introductory students over five years (n=872) and find that the mean raw gain of students in transformed lab sections was 0.243, while the mean raw gain of the traditional labs was 0.159, with a Cohen’s d effect size of 0.59. Average raw gains on the FCI were 0.243 for Hispanic students and 0.213 for women in the transformed labs, indicating that these reforms are not widening the gaps between underrepresented student groups and majority groups. Our results illustrate how research-based instructional strategies can be successfully implemented in a physics department with minimal department engagement and in a sustainable manner.

Diagnostic value of diffusion weighted MRI and ADC in differential diagnosis of cavernous hemangioma of the liver.

Aims: To investigate the use of diffusion weighted magnetic resonance imaging (DWI) and the apparent diffusion coefficient (ADC) values in the diagnosis of hemangioma. Materials and methods: The study population consisted of 72 patients with liver masses larger than 1 cm (72 focal lesions). DWI examination with a b value of 600 s/mm2 was carried out for all patients. After DWI examination, an ADC map was created and ADC values were measured for 72 liver masses and normal liver tissue (control group). The average ADC values of normal liver tissue and focal liver lesions, the “cut-off” ADC values, and the diagnostic sensitivity and specificity of the ADC map in diagnosing hemangioma, benign and malignant lesions were researched. Results: Of the 72 liver masses, 51 were benign and 21 were malignant. Benign lesions comprised 38 hemangiomas and 13 simple cysts. Malignant lesions comprised 9 hepatocellular carcinomas, and 12 metastases. The highest ADC values were measured for cysts (3.782±0.53×10-3 mm2/s) and hemangiomas (2.705±0.63×10-3 mm2/s). The average ADC value of hemangiomas was significantly higher than malignant lesions and the normal control group (p<0.001). The average ADC value of cysts were significantly higher when compared to hemangiomas and normal control group (p<0.001). To distinguish hemangiomas from malignant liver lesions, the “cut-off” ADC value of 1.800×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 90.9%. To distinguish hemangioma from normal liver parenchyma the “cut-off” value of 1.858×10-3 mm2/s had a sensitivity of 97.4% and a specificity of 95.7%. To distinguish benign liver lesions from malignant liver lesions the “cut-off” value of 1.800×10-3 mm2/s had a sensitivity of 96.1% and a specificity of 90.0%. Conclusion: DWI and quantitative measurement of ADC values can be used in differential diagnosis of benign and malignant liver lesions and also in the diagnosis and differentiation of hemangiomas. When dynamic examination cannot distinguish cases with vascular metastasis and lesions from hemangioma, DWI and ADC values can be useful in the primary diagnosis and differential diagnosis. The technique does not require contrast material, so it can safely be used in patients with renal failure. Keywords: