A binocular machine vision system for three-dimensional surface measurement of small objects

Rendering three-dimensional information of a scene from optical measurements is very important for a wide variety of applications. However, computer vision advancements have not yet achieved the accurate three-dimensional reconstruction of objects smaller than 1 cm diameter. This paper describes the development of a novel volumetric method for small objects, using a binocular machine vision system. The achieved precision is high, providing a standard deviation of 0.04 mm. The robustness, of the system, issues from the lab prototype imaging system with the crucial z-axis movement without the need of further calibration and the fully automated volumetric algorithms.     

Sustained good glycaemic control in NIDDM patients by implementation of structured care in general practice: 2-year follow-up study

Summary In primary care it is difficult to treat the growing number of non-insulin-dependent diabetic (NIDDM) patients according to (inter)national guidelines. A prospective, controlled cohort study was designed to assess the intermediate term (2 years) effect of structured NIDDM care in general practice with and without ’diabetes service' support on glycaemic control, cardiovascular risk factors, general well-being and treatment satisfaction. The ’diabetes service', supervised by a diabetologist, included a patient registration system, consultation facilities of a dietitian and diabetes nurse educator, and protocolized blood glucose lowering therapy advice which included home blood glucose monitoring and insulin therapy. In the study group (SG; 22 general practices), 350 known NIDDM patients over 40 years of age (206 women; mean age 65.3 ± SD 11.9; diabetes duration 5.9 ± 5.4 years) were followed for 2 years. The control group (CG; 6 general practices) consisted of 68 patients (28 women; age 64.6 ± 10.3; diabetes duration 6.3 ± 6.4 years). Mean HbA_{1 c} (reference 4.3–6.1 %) fell from 7.4 to 7.0 % in SG and rose from 7.4 to 7.6 % in CG during follow-up (p = 0.004). The percentage of patients with poor control (HbA_{1 c} > 8.5 %) shifted from 21.4 to 11.7 % in SG, but from 23.5 to 27.9 % in CG (p = 0.008). Good control (HbA_{1 c} < 7.0 %) was achieved in 54.3 % (SG; at entry 43.4 %) and 44.1 % (CG; at entry 54.4 %) (p = 0.013). Insulin therapy was started in 29.7 % (SG) and 8.8 % (CG) of the patients (p = 0.000) with low risk of severe hypoglycaemia (0.019/patient year). Mean levels of total and HDL-cholesterol (SG), triglycerides (SG) and diastolic blood pressure (SG + CG) and the percentage of smokers (SG) declined significantly, but the prevalence of these risk factors remained high. General well-being (SG) did not change during intensified therapy. Treatment satisfaction (SG) tended to improve. Implementation of structured care, including education and therapeutic advice, results in sustained good glycaemic control in the majority of NIDDM patients in primary care, with low risk of hypoglycaemia. Lowering cardiovascular risk requires more than reporting results and referral to guidelines. [Diabetologia (1997) 40: 1334–1340] Received: 5 February 1997 and in revised form: 22 May 1997     

Percepciones estudiantiles sobre las propiedades del examen clínico objetivo estructurado en Uruguay. Disponiendo un cuestionario válido para analizar la factibilidad del nuevo formato durante la transición curricular

Introduction

Although an objective structured clinical examination (OSCE) format has been applied in Uruguay since 2004, and providing reliable performance measures, perceptions of it properties and level of student satisfaction have not been determined.

Epitope mapping and characterization of a novel CD4-induced human monoclonal antibody capable of neutralizing primary HIV-1 strains

Human immunodeficiency virus (HIV-1) enters target cells by binding its gp120 exterior envelope glycoprotein to CD4 and one of the chemokine receptors, CCR5 or CXCR4. CD4-induced (CD4i) antibodies bind gp120 more efficiently after CD4 binding and block the interaction with the chemokine receptor. Examples of CD4i antibodies are limited, and the prototypes of the CD4i antibodies exhibit only weak neutralizing activity against primary, clinical HIV-1 isolates. Here we report the identification of a novel antibody, E51, that exhibits CD4-induced binding to gp120 and neutralizes primary HIV-1 more efficiently than the prototypic CD4i antibodies. The E51 antibody blocks the interaction of gp120-CD4 complexes with CCR5 and binds to a highly conserved, basic gp120 element composed of the beta 19-strand and surrounding structures. Thus, on primary HIV-1 isolates, this gp120 region, which has been previously implicated in chemokine receptor binding, is accessible to a subset of CD4i antibodies.     

Infrared spectroscopy: A new diagnostic tool in Alzheimer disease

Biological markers play an evolving role in the diagnosis of Alzheimer disease (AD). We compare conventional measurements of cerebrospinal fluid (CSF) tau and β-amyloid_1–42 proteins to a novel approach – Fourier transformed infrared (FT-IR) spectroscopy – a simple technique derived from chemical and physical sciences that characterizes intramolecular bonds. For automatic diagnostic analysis, we developed an artificial neural network (ANN). We examined 71 patients with a clinical diagnosis of AD and 66 controls. β-Amyloid_1–42 was decreased (sensitivity 80% and specificity 78%); tau was elevated (sensitivity 76% and specificity 88%) in CSF of AD patients. The combined tau/β-amyloid_1–42 quotient was able to distinguish healthy from diseased subjects with 99% sensitivity and 86% specificity. The ANN could separate FT-IR spectroscopy data with 88.5% sensitivity and 80% specificity. FT-IR spectroscopy proved to be cost-effective and simple to perform. Diagnostic sensitivity and specificity is in the range of CSF tau and β-amyloid_1–42 protein analysis. Larger sample numbers for ANN training and validation could increase diagnostic accuracy and thus prove to be a useful screening tool.     

Education Time Out and Debrief: Structured Implementation of Perioperative Resident Technical Education Discussion

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Optimizing Technology Development and Adoption in Medical Imaging Using the Principles of Innovation Diffusion, Part II: Practical Applications

Successful adoption of new technology development can be accentuated by learning and applying the scientific principles of innovation diffusion. This is of particular importance to areas within the medical imaging practice which have lagged in innovation; perhaps, the most notable of which is reporting which has remained relatively stagnant for over a century. While the theoretical advantages of structured reporting have been well documented throughout the medical imaging community, adoption to date has been tepid and largely relegated to the academic and breast imaging communities. Widespread adoption will likely require an alternative approach to innovation, which addresses the heterogeneity and diversity of the practicing radiologist community along with the ever-changing expectations in service delivery. The challenges and strategies for reporting innovation and adoption are discussed, with the goal of adapting and customizing new technology to the preferences and needs of individual end-users.     

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach

BackgroundGait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial accelerometry. However, these methods are tailored to very specific acceleration profiles, which may offer complications when dealing with larger data sets and inherent biological variability.Research questionCan a structured machine learning approach achieve a more accurate prediction of running gait event timings from tibial accelerometry, compared to the previously utilised heuristic approaches?MethodsForce-based event detection acted as the criterion measure in order to assess the accuracy, repeatability and sensitivity of the predicted gait events. 3D tibial acceleration and ground reaction force data from 93 rearfoot runners were captured. A heuristic method and two structured machine learning methods were employed to derive initial contact, toe off and stance time from tibial acceleration signals.ResultsBoth a structured perceptron model (median absolute error of stance time estimation: 10.00 ± 8.73 ms) and a structured recurrent neural network model (median absolute error of stance time estimation: 6.50 ± 5.74 ms) significantly outperformed the existing heuristic approach (median absolute error of stance time estimation: 11.25 ± 9.52 ms). Thus, results indicate that a structured recurrent neural network machine learning model offers the most accurate and consistent estimation of the gait events and its derived stance time during level overground running.SignificanceThe machine learning methods seem less affected by intra- and inter-subject variation within the data, allowing for accurate and efficient automated data output during rearfoot overground running. Furthermore offering possibilities for real-time monitoring and biofeedback during prolonged measurements, even outside the laboratory.