Playing for Data: Ground Truth from Computer Games

Recent progress in computer vision has been driven by high-capacity models trained on large datasets. Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games. Although the source code and the internal operation of commercial games are inaccessible, we show that associations between image patches can be reconstructed from the communication between the game and the graphics hardware. This enables rapid propagation of semantic labels within and across images synthesized by the game, with no access to the source code or the content. We validate the presented approach by producing dense pixel-level semantic annotations for 25 thousand images synthesized by a photorealistic open-world computer game. Experiments on semantic segmentation datasets show that using the acquired data to supplement real-world images significantly increases accuracy and that the acquired data enables reducing the amount of hand-labeled real-world data: models trained with game data and just 1/3 of the CamVid training set outperform models trained on the complete CamVid training set.Comment: Accepted to the 14th European Conference on Computer Vision (ECCV 2016

GABA(A) receptors containing (alpha)5 subunits in the CA1 and CA3 hippocampal fields regulate ethanol-motivated behaviors: an extended ethanol reward circuitry

GABA receptors within the mesolimbic circuitry have been proposed to play a role in regulating alcohol-seeking behaviors in the alcohol-preferring (P) rat. However, the precise GABA(A) receptor subunit(s) mediating the reinforcing properties of EtOH remains unknown. We examined the capacity of intrahippocampal infusions of an alpha5 subunit-selective ( approximately 75-fold) benzodiazepine (BDZ) inverse agonist [i.e., RY 023 (RY) (tert-butyl 8-(trimethylsilyl) acetylene-5,6-dihydro-5-methyl-6-oxo-4H-imidazo [1,5a] [1,4] benzodiazepine-3-carboxylate)] to alter lever pressing maintained by concurrent presentation of EtOH (10% v/v) and a saccharin solution (0.05% w/v). Bilateral (1.5-20 microgram) and unilateral (0.01-40 microgram) RY dose-dependently reduced EtOH-maintained responding, with saccharin-maintained responding being reduced only with the highest doses (e.g., 20 and 40 microgram). The competitive BDZ antagonist ZK 93426 (ZK) (7 microgram) reversed the RY-induced suppression on EtOH-maintained responding, confirming that the effect was mediated via the BDZ site on the GABA(A) receptor complex. Intrahippocampal modulation of the EtOH-maintained responding was site-specific; no antagonism by RY after intra-accumbens [nucleus accumbens (NACC)] and intraventral tegmental [ventral tegmental area (VTA)] infusions was observed. Because the VTA and NACC contain very high densities of alpha1 and alpha2 subunits, respectively, we determined whether RY exhibited a "negative" or "neutral" pharmacological profile at recombinant alpha1beta3gamma2, alpha2beta3gamma2, and alpha5beta3gamma2 receptors expressed in Xenopus oocytes. RY produced "classic" inverse agonism at all alpha receptor subtypes; thus, a neutral efficacy was not sufficient to explain the failure of RY to alter EtOH responding in the NACC or VTA. The results provide the first demonstration that the alpha5-containing GABA(A) receptors in the hippocampus play an important role in regulating EtOH-seeking behaviors

Association of A1C and Fasting Plasma Glucose Levels With Diabetic Retinopathy Prevalence in the U.S. Population: Implications for diabetes diagnostic thresholds

Abstract OBJECTIVE To examine the association of A1C levels and fasting plasma glucose (FPG) with diabetic retinopathy in the U.S. population and to compare the ability of the two glycemic measures to discriminate between people with and without retinopathy. RESEARCH DESIGN AND METHODS This study included 1,066 individuals aged ≥40 years from the 2005–2006 National Health and Nutrition Examination Survey. A1C, FPG, and 45° color digital retinal images were assessed. Retinopathy was defined as a level ≥14 on the Early Treatment Diabetic Retinopathy Study severity scale. We used joinpoint regression to identify linear inflections of prevalence of retinopathy in the association between A1C and FPG. RESULTS The overall prevalence of retinopathy was 11%, which is appreciably lower than the prevalence in people with diagnosed diabetes (36%). There was a sharp increase in retinopathy prevalence in those with A1C ≥5.5% or FPG ≥5.8 mmol/l. After excluding 144 people using hypoglycemic medication, the change points for the greatest increase in retinopathy prevalence were A1C 5.5% and FPG 7.0 mmol/l. The coefficients of variation were 15.6 for A1C and 28.8 for FPG. Based on the areas under the receiver operating characteristic curves, A1C was a stronger discriminator of retinopathy (0.71 [95% CI 0.66–0.76]) than FPG (0.65 [0.60 – 0.70], P for difference = 0.009). CONCLUSIONS The steepest increase in retinopathy prevalence occurs among individuals with A1C ≥5.5% and FPG ≥5.8 mmol/l. A1C discriminates prevalence of retinopathy better than FPG. Tests of glycemia and their thresholds for diabetes diagnosis is an area of long-standing debate. The presence of diabetic retinopathy is arguably the best criterion from which to compare glycemic measures because it is a specific and early clinical complication usually related to diabetes, and it represents a specific and relevant clinical end point for judging an alternative test (1). For these reasons, diabetic retinopathy has served as the basis for diagnostic criteria of type 2 diabetes (2–4) and provides the rationale for the American Diabetes Association's recommendation of a threshold of a fasting plasma glucose (FPG) of 7.0 mmol/l to define the presence of diabetes (4,5). However, an analysis of three recent population-based cross-sectional studies suggested that there may be considerable variation across populations and that the association of FPG with retinopathy prevalence may be more of a continuous relationship than previously thought (5). A1C levels are being considered as an alternative diagnostic tool for diabetes diagnosis (6). Unlike FPG, A1C does not require an overnight fast, is not affected by short-term lifestyle changes, and has less variability within individuals than FPG (7–9). Nevertheless, few studies have examined the prevalence of retinopathy across the spectrum of A1C levels, which could assist in the designation of ideal A1C diagnostic cut points (2,3). The newly released National Health and Nutrition Examination Survey (NHANES) 2005–2006 incorporated a multiple-field retinal photograph examination, presenting an opportunity to reassess the selection of glucose and A1C cut points for diabetes diagnosis. Our objectives were to examine the relation between levels of A1C and FPG and prevalence of retinopathy in the U.S. population and to compare the ability of both measures to differentiate people with and without retinopathy

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

Background: Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. Approach: An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. Content: In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A$_{1c}$ (HbA$_{1c}$) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA$_{1c}$. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. Summary: The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended

Stroke severity mediates the effect of socioeconomic disadvantage on poor outcomes among patients with intracerebral hemorrhage

BackgroundSocioeconomic deprivation drives poor functional outcomes after intracerebral hemorrhage (ICH). Stroke severity and background cerebral small vessel disease (CSVD) burden have each been linked to socioeconomic status and independently contribute to worse outcomes after ICH, providing distinct, plausible pathways for the effects of deprivation. We investigate whether admission stroke severity or cerebral small vessel disease (CSVD) mediates the effect of socioeconomic deprivation on 90-day functional outcomes.MethodsElectronic medical record data, including demographics, treatments, comorbidities, and physiological data, were analyzed. CSVD burden was graded from 0 to 4, with severe CSVD categorized as ≥3. High deprivation was assessed for patients in the top 30% of state-level area deprivation index scores. Severe disability or death was defined as a 90-day modified Rankin Scale score of 4–6. Stroke severity (NIH stroke scale (NIHSS)) was classified as: none (0), minor (1–4), moderate (5–15), moderate–severe (16–20), and severe (21+). Univariate and multivariate associations with severe disability or death were determined, with mediation evaluated through structural equation modelling.ResultsA total of 677 patients were included (46.8% female; 43.9% White, 27.0% Black, 20.7% Hispanic, 6.1% Asian, 2.4% Other). In univariable modelling, high deprivation (odds ratio: 1.54; 95% confidence interval: [1.06–2.23]; p = 0.024), severe CSVD (2.14 [1.42–3.21]; p < 0.001), moderate (8.03 [2.76–17.15]; p < 0.001), moderate–severe (32.79 [11.52–93.29]; p < 0.001), and severe stroke (104.19 [37.66–288.12]; p < 0.001) were associated with severe disability or death. In multivariable modelling, severe CSVD (3.42 [1.75–6.69]; p < 0.001) and moderate (5.84 [2.27–15.01], p < 0.001), moderate–severe (27.59 [7.34–103.69], p < 0.001), and severe stroke (36.41 [9.90–133.85]; p < 0.001) independently increased odds of severe disability or death; high deprivation did not. Stroke severity mediated 94.1% of deprivation’s effect on severe disability or death (p = 0.005), while CSVD accounted for 4.9% (p = 0.524).ConclusionCSVD contributed to poor functional outcome independent of socioeconomic deprivation, while stroke severity mediated the effects of deprivation. Improving awareness and trust among disadvantaged communities may reduce admission stroke severity and improve outcomes

Recovering Motion Fields: An Evaluation of Eight Optical Flow Algorithms

Evaluating the performance of optical flow algorithms has been difficult because of the lack of ground-truth data sets for complex scenes. We describe a simple modification to a ray tracer that allows us to generate ground-truth motion fields for scenes of arbitrary complexity. The resulting flow maps are used to assist in the comparison of eight optical flow algorithms using three complex, synthetic scenes. Our study found that a modified version of Lucas and Kanade's algorithm has superior performance but produces sparse flow maps. Proesmans et al.'s algorithm performs slightly worse, on average, but produces a very dense depth map. 1 Introduction Seventeen years have passed since Horn and Schunck published their influential paper on the calculation of optical flow [4]. Since then, a substantial amount of research has been devoted to finding ways to calculate optical flow more efficiently and more accurately. Optical flow extraction has been proposed as a preprocessing step..

Three Dimensional (3D) Lumbar Vertebrae Data Set

3D modelling can be used for a variety of purposes, including biomedical modelling for orthopaedic or anatomical applications. Low back pain is prevalent in society yet few validated 3D models of the lumbar spine exist to facilitate assessment. We therefore created a 3D surface data set for lumbar vertebrae from human vertebrae. Models from 86 lumbar vertebrae were constructed using an inexpensive method involving image capture by digital camera and reconstruction of 3D models via an image-based technique. The reconstruction method was validated using a laser-based arm scanner and measurements derived from real vertebrae using electronic callipers. Results show a mean relative error of 5.2% between image-based models and real vertebrae, a mean relative error of 4.7% between image-based and arm scanning models and 95% of vertices’ errors are less than 3.5 millimetres with a median of 1.1 millimetres. The accuracy of the method indicates that the generated models could be useful for biomechanical modelling or 3D visualisation of the spine