Bayesian Transductive Markov Random Fields for Interactive Segmentation in Retinal Disorders

In the realm of computer aided diagnosis (CAD) interactive segmentation schemes have been well received by physicians, where the combination of human and machine intelligence can provide improved segmentation efficacy with minimal expert intervention [1-3]. Transductive learning (TL) or semi-supervised learning (SSL) is a suitable framework for learning-based interactive segmentation given the scarce label problem. In this paper we present extended work on Bayesian transduction and regularized conditional mixtures for interactive segmentation [3]. We present a Markov random field model integrating a semi-parametric conditional mixture model within a Bayesian transductive learning and inference setting. The model allows efficient learning and inference in a semi-supervised setting given only minimal approximate label information. Preliminary experimental results on multimodal images of retinal disorders such as drusen, geographic atrophy (GA), and choroidal neovascularisation (CNV) with exudates and subretinal fibrosis show promising segmentation performance

Learning Non-Homogenous Textures and the Unlearning Problem with Application to Drusen Detection in Retinal Images

In this work we present a novel approach for learning non- homogenous textures without facing the unlearning problem. Our learning method mimics the human behavior of selective learning in the sense of fast memory renewal. We perform probabilistic boosting and structural similarity clustering for fast selective learning in a large knowledge domain acquired over different time steps. Applied to non- homogenous texture discrimination, our learning method is the first approach that deals with the unlearning problem applied to the task of drusen segmentation in retinal imagery, which itself is a challenging problem due to high variability of non-homogenous texture appearance. We present preliminary results

Retinal vessel segmentation using multi-scale wavelet frame analysis

Fundus imaging is a non-invasive technique for in vivo ophthalmoscopic inspection of retinal disorders. Quantitative information about the vascular network can facilitate clinical diagnosis of retinal diseases [1]. Goal: Segmentation of the vascular network in fundus images for further quantification and post processing as a binary classification into object and background. Approach: We perform an over-complete multi-scale wavelet frame expansion with selective channel rejection in the decomposition tree. Remaining channels undergo wavelet shrinkage and enhancement to separate retinal objects from background. Results: Comparison to expert gradings on a pixel by pixel basis show mean sensitivity and specificity of 0.8 and 0.9

Interactive Image Analysis in Age-related Macular Degeneration (AMD) and Stargardt Disease (STGD)

The literature of the last three decades is replete with automatic methods for retinal image analysis. Acceptance has been limited due to post-processing or tuning requirements that may be just as time consuming as the original manual methods. The point of view herein is that by taking advantage of the human visual system and expert knowledge from the outset, the promised efficiencies of digital methods can be achieved in practice as well as in theory. Thus, simple labeling of regions of interest that is accepted and easily performed in a few moments by the human can provide enormous advantage to an already well-developed algorithm. Three examples are provided: drusen segmentation, image registration, and geographic atrophy segmentation, with applications to disease understanding

The Design and Performance of a Distributed Flow Water-Cooled Solar Collector

Design of a flat plate collector which reduces the temperature differential between the absorber plate and the fluid is described. The reduced temperature differences are shown to yield increase collector performance. Flow characteristics of the collector are examined. Collector thermal performance is illustrated for typical operating and environmental conditions. A cost analysis is presented to demonstrate that material and assembly costs are substantially lower than for any collector presently on the market

Thermal Structures Technology Development for Reusable Launch Vehicle Cryogenic Propellant Tanks

Analytical and experimental studies conducted at the NASA, Langley Research Center (LaRC) for investigating integrated cryogenic propellant tank systems for a reusable launch vehicle (RLV) are described. The cryogenic tanks are investigated as an integrated tank system. An integrated tank system includes the tank wall, cryogenic insulation, thermal protection system (TPS) attachment sub-structure, and TPS. Analysis codes are used to size the thicknesses of cryogenic insulation and TPS insulation for thermal loads, and to predict tank buckling strengths at various ring frame spacings. The unique test facilities developed for the testing of cryogenic tank components are described. Testing at cryogenic and high-temperatures verifies the integrity of materials, design concepts, manufacturing processes, and thermal/structural analyses. Test specimens ranging from the element level to the subcomponent level are subjected to projected vehicle operational mechanical loads and temperatures. The analytical and experimental studies described in this paper provide a portion of the basic information required for the development of light-weight reusable cryogenic propellant tanks

Heritable Variation in Garter Snake Color Patterns in Postglacial Populations

Global climate change is expected to trigger northward shifts in the ranges of natural populations of plants and animals, with subsequent effects on intraspecific genetic diversity. Investigating how genetic diversity is patterned among populations that arose following the last Ice Age is a promising method for understanding the potential future effects of climate change. Theoretical and empirical work has suggested that overall genetic diversity can decrease in colonial populations following rapid expansion into postglacial landscapes, with potential negative effects on the ability of populations to adapt to new environmental regimes. The crucial measure of this genetic variation and a population's overall adaptability is the heritable variation in phenotypic traits, as it is this variation that mediates the rate and direction of a population's multigenerational response to selection. Using two large full-sib quantitative genetic studies (NManitoba = 144; NSouth Dakota = 653) and a smaller phenotypic analysis from Kansas (NKansas = 44), we compared mean levels of pigmentation, genetic variation and heritability in three pigmentation traits among populations of the common garter snake, Thamnophis sirtalis, along a north-south gradient, including a postglacial northern population and a putative southern refuge population. Counter to our expectations, we found that genetic variance and heritability for the three pigmentation traits were the same or higher in the postglacial population than in the southern population

Tales from the EMR: Does a 21st-Century Data Warehouse Facilitate Clinical Research for Pancreatic Cancer?

Background: The importance of an electronic medical record has been highlighted for both clinical care and research. In the current era, data warehouses and repositories have been established to serve the dual function of patient care and investigation. Purpose: The aim of this study was to compare a newly developed institutional clinical data warehouse, linked with the hospital information system (HIS), to a prospectively-maintained departmental database. Methods: A novel HIS-linked institutional clinical data warehouse was queried for 9 primary and secondary ICD-9-CM discharge diagnosis codes for pancreatic cancer. The database captured inpatient and outpatient clinical and billing information from a pool of over 2 million patients evaluated at an academic medical institution and its affiliates since 1995. A cohort was identified; following Institutional Review Board approval, demographic and clinical data was obtained. This data was compared to a manually-entered and prospectively-maintained surgical oncology database of the same institution, tracking 394 patients since 1999. Duplicated patients, and those unique to either dataset, were flagged. Patients with diagnosis dates prior to 1999 were excluded to allow comparison over the same time period. For validation purposes, a 10% random sample of remaining patients unique to each dataset underwent manual review of medical records including clinic notes, admission/discharge notes, diagnostic imaging, and pathology reports. Results: 1107 patients were identified from the HIS-linked dataset with pancreatic neoplasm-associated diagnosis codes dating from 1999 to 2009. Of these, 254 (22.9%) were captured in both datasets, while 853 (77.1%) were only in the HIS-linked dataset. Manual review of the 10% subset of the HIS-only group demonstrated that 55.6% of patients were without identifiable pancreatic pathology, suggesting miscoding, while 31.7% had diagnoses consistent with pancreatic neoplasm, and 12.7% had pseudocyst or pancreatitis. Of the 394 patients tracked by surgical oncology, 254 (64.5%) were captured in both datasets, while 140 (35.5%) had not been captured in the HIS-linked dataset. Manual review of the 10% subset of the non-captured patients demonstrated 93.3% with pancreatic neoplasm and 6.7% with pseudocyst or pancreatitis. Lastly, a review of the 10% subset of the 254 patient overlap demonstrated that 87.5% of patients were with pancreatic neoplasm, 8.3% with pseudocyst or pancreatitis, and 4.2% without pancreatic pathology. Conclusions: While technological advances provide a powerful means to automate institutional-level cohort identification and data collection, a high degree of misclassification may be present if queries are based solely on ICD-9-CM discharge codes. For that reason, careful validation and data cleaning are critical steps prior to research use. These results also suggest cautious interpretation of national-level administrative data utilizing ICD-9-CM diagnosis codes. Our findings suggest that the current state-of-the-art data warehouses continue to require clinical correlation and validation through traditional retrospective mechanisms

Brief of Feminists for Life of America, Professional Women\u27s Network, Birthright, Inc., Legal Action for Women, as Amici Curiae in Support of Respondents and Cross Petitioners - Planned Parenthood of Southeastern Pennsylvania v. Casey, 112 S. Ct. 2791 (1992)

Amici, representing women from all walks of life, are compelled by experience and conviction to advocate strongly that this Court reverse the vulnerable position of women caused by the lack of information given to women contemplating abortion. Amici respectfully urged this Court to affirm the ruling of the Court below, supporting the efforts of the women citizens of the Commonwealth of Pennsylvania to cause that government to exercise its police power to protect their health and safety by compelling the dissemination of the information necessary to make a fully informed decision

A hybrid segmentation approach for geographic atrophy in fundus auto-fluorescence images for diagnosis of age-related macular degeneration

Fundus auto-fluorescence (FAF) images with hypo-fluorescence indicate geographic atrophy (GA) of the retinal pigment epithelium (RPE) in age-related macular degeneration (AMD). Manual quantification of GA is time consuming and prone to inter- and intra-observer variability. Automatic quantification is important for determining disease progression and facilitating clinical diagnosis of AMD. In this paper we describe a hybrid segmentation method for GA quantification by identifying hypo-fluorescent GA regions from other interfering retinal vessel structures. First, we employ background illumination correction exploiting a non-linear adaptive smoothing operator. Then, we use the level set framework to perform segmentation of hypo-fluorescent areas. Finally, we present an energy function combining morphological scale-space analysis with a geometric model-based approach to perform segmentation refinement of false positive hypo- fluorescent areas due to interfering retinal structures. The clinically apparent areas of hypo-fluorescence were drawn by an expert grader and compared on a pixel by pixel basis to our segmentation results. The mean sensitivity and specificity of the ROC analysis were 0.89 and 0.98%