Economic Underperformance: SSA from Planning through Life Crisis Coping and Structural Adjustment To What Strategic Agendas?

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Real-time standard scan plane detection and localisation in fetal ultrasound using fully convolutional neural networks

Fetal mid-pregnancy scans are typically carried out according to fixed protocols. Accurate detection of abnormalities and correct biometric measurements hinge on the correct acquisition of clearly defined standard scan planes. Locating these standard planes requires a high level of expertise. However, there is a worldwide shortage of expert sonographers. In this paper, we consider a fully automated system based on convolutional neural networks which can detect twelve standard scan planes as defined by the UK fetal abnormality screening programme. The network design allows real-time inference and can be naturally extended to provide an approximate localisation of the fetal anatomy in the image. Such a framework can be used to automate or assist with scan plane selection, or for the retrospective retrieval of scan planes from recorded videos. The method is evaluated on a large database of 1003 volunteer mid-pregnancy scans. We show that standard planes acquired in a clinical scenario are robustly detected with a precision and recall of 69 % and 80 %, which is superior to the current state-of-the-art. Furthermore, we show that it can retrospectively retrieve correct scan planes with an accuracy of 71 % for cardiac views and 81 % for non-cardiac views

Solving The Problem of Adaptive E-Learning By Using Social Networks

This paper propose an enhanced E-Learning Social Network Exploiting Approach focused around chart model and clustering algorithm, which can consequently gathering dispersed e-learners with comparative premiums and make fitting suggestions, which can at last upgrade the collective learning among comparable e-learners. Through closeness revelation, trust weights overhaul and potential companions change, the algorithm actualized a programmed adjusted trust association with progressively upgraded fulfillments. Keywords: Relations, Adaptive E-Learning, Clustering , Social Network , E-learning ,  and Collaborative Learnin

Quality-improvement program for ultrasound-based fetal anatomy screening using large-scale clinical audit.

OBJECTIVE: A large-scale audit and peer review of ultrasound images may improve sonographer performance, but is rarely performed consistently as it is time-consuming and expensive. The aim of this study was to perform a large-scale audit of routine fetal anatomy scans to assess if a full clinical audit cycle can improve clinical image-acquisition standards. METHODS: A large-scale, clinical, retrospective audit was conducted of ultrasound images obtained during all routine anomaly scans performed from 18 + 0 to 22 + 6 weeks' gestation at a UK hospital during 2013 (Cycle 1), to build a baseline understanding of the performance of sonographers. Targeted actions were undertaken in response to the findings with the aim of improving departmental performance. A second full-year audit was then performed of fetal anatomy ultrasound images obtained during the following year (Cycle 2). An independent pool of experienced sonographers used an online tool to assess all scans in terms of two parameters: scan completeness (i.e. were all images archived?) and image quality using objective scoring (i.e. were images of high quality?). Both were assessed in each audit at the departmental level and at the individual sonographer level. A random sample of 10% of scans was used to assess interobserver reproducibility. RESULTS: In Cycle 1 of the audit, 103 501 ultrasound images from 6257 anomaly examinations performed by 22 sonographers were assessed; in Cycle 2, 153 557 images from 6406 scans performed by 25 sonographers were evaluated. The analysis was performed including the images obtained by the 20 sonographers who participated in both cycles. Departmental median scan completeness improved from 72% in the first year to 78% at the second assessment (P < 0.001); median image-quality score for all fetal views improved from 0.83 to 0.86 (P < 0.001). The improvement was greatest for those sonographers who performed poorest in the first audit; with regards to scan completeness, the poorest performing 15% of sonographers in Cycle 1 improved by more than 30 percentage points, and with regards to image quality, the poorest performing 11% in Cycle 1 showed a more than 10% improvement. Interobserver repeatability of scan completeness and image-quality scores across different fetal views were similar to those in the published literature. CONCLUSIONS: A clinical audit and a set of targeted actions helped improve sonographer scan-acquisition completeness and scan quality. Such adherence to recommended clinical acquisition standards may increase the likelihood of correct measurement and thereby fetal growth assessment, and should allow better detection of abnormalities. As such a large-scale audit is time consuming, further advantages would be achieved if this process could be automated. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology

Automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound

Transperineal volumetric ultrasound (US) imaging has become routine practice for diagnosing pelvic floor disease (PFD). Hereto, clinical guidelines stipulate to make measurements in an anatomically defined 2D plane within a 3D volume, the so-called C-plane. This task is currently performed manually in clinical practice, which is labour-intensive and requires expert knowledge of pelvic floor anatomy, as no computer-aided C-plane method exists. To automate this process, we propose a novel, guideline-driven approach for automatic detection of the C-plane. The method uses a convolutional neural network (CNN) to identify extreme coordinates of the symphysis pubis and levator ani muscle (which define the C-plane) directly via landmark regression. The C-plane is identified in a postprocessing step. When evaluated on 100 US volumes, our best performing method (multi-task regression with UNet) achieved a mean error of 6.05 mm and 4.81 ∘ and took 20 s. Two experts blindly evaluated the quality of the automatically detected planes and manually defined the (gold standard) C-plane in terms of their clinical diagnostic quality. We show that the proposed method performs comparably to the manual definition. The automatic method reduces the average time to detect the C-plane by 100 s and reduces the need for high-level expertise in PFD US assessment

Single Stage Laparoscopic Orchiopexy for Impalpable Low Abdominal Undescended Testis in Children- Analysis of Outcome

Objective: To evaluate clinical efficacy of single stage laparoscopic orchiopexy by modified Prentiss procedure for the treatment of impalpable undescended testis within 2.5 cm from deep ring in children. Study Design: This was a retrospective case series study design. Place and Duration of Study: Department of surgery, section of pediatric surgery. Northern Area Armed Forces Hospital Hafer Al Batin, Saudi Arabia, from June 15, 2011, to Sep 15, 2021. Materials and Methods: All the children admitted with diagnosis of impalpable undescended testis were treated by single stage laparoscopic orchiopexy by modified Prentiss technique during the study period from June 15, 2011, till Sep 15, 2021. The total number of patients was 22. The age of the patients ranged from 1 year to 7 years. Seventeen (77.26 %) children had unilateral (10 with left sided and 7 with right sided) impalpable undescended testis. Five (22.72%) children had bilateral impalpable undescended testis. All the patients were evaluated by ultrasound and MRI abdomen to confirm the abdominal location. The patients were operated by single stage laparoscopic orchiopexy using modified Prentiss technique by single senior pediatric surgeon after confirming the location of testis within 2.5 cm from deep inguinal ring. All the patients were followed up in outpatient clinic after 1 week, after 6 months and after 1 year. The operative time, degree of post- operative pain, per operative and post- operative complications and follow up results were analyzed to evaluate the clinical outcome in terms of testicular location in the scrotum and size. Results: A total of 22 children were treated successfully by single stage laparoscopic orchiopexy by modified Prentiss technique. The age ranged from one year to 7 years at the time of surgery. Ten (45.45%) patients had left sided non-palpable testis, 7 (31.81%) had right sided and 5 (22.72%) children were having bilateral non palpable testis. There was no per-operative complication. One patient (4.54%) had scrotal hematoma which resolved spontaneously. All the children had successful outcome in terms of testicular size and location within scrotum after surgery on follow up of more than one year. There was no case (0%) of testicular atrophy in this series. Thirteen (59%) patients had testis in lowest position of scrotum, eight (36.36%) patients had testis in the middle scrotum and one (4.54%) patient had testis in the neck of the scrotum. Conclusion: Single stage Laparoscopic orchiopexy by modified Prentiss procedure is feasible, safe and effective technique to treat children with impalpable low abdominal undescended testis in childre

General practitioners\u27 knowledge and approach to chronic kidney disease in Karachi, Pakistan

Due to lack of adequate number of formally trained nephrologists, many patients with chronic kidney disease (CKD) are seen by general practitioners (GPs). This study was designed to assess the knowledge of the GPs regarding identification of CKD and its risk factors, and evaluation and management of risk factors as well as complications of CKD. We conducted a cross-sectional survey of 232 randomly selected GPs from Karachi during 2011. Data were collected on a structured questionnaire based on the kidney disease outcomes and quality initiative recommendations on screening, diagnosis, and management of CKD. A total of 235 GPs were approached, and 232 consented to participate. Mean age was 38.5 ± 11.26 years; 56.5% were men. Most of the GPs knew the traditional risk factors for CKD, i.e., diabetes (88.4%) and hypertension (80%), but were less aware of other risk factors. Only 38% GPs were aware of estimated glomerular filtration rate in evaluation of patients with CKD. Only 61.6% GPs recognized CKD as a risk factor for cardiovascular disease. About 40% and 29% GPs knew the correct goal systolic and diastolic blood pressure, respectively. In all, 41% GPs did not know when to refer the patient to a nephrologist. Our survey identified specific gaps in knowledge and approach of GPs regarding diagnosis and management of CKD. Educational efforts are needed to increase awareness of clinical practice guidelines and recommendations for patients with CKD among GPs, which may improve management and clinical outcomes of this population

Use of population input functions for reduced scan duration whole-body Patlak F-18-FDG PET imaging

Abstract: Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated. Methods: Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants (K 1, k 3, and both K 1 and k 2) multiplied by 2, 1.5, and 0.75; and addition of noise (μ = 0 and σ = 5, 10 and 15%). Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (K i) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in K i was evaluated. Results: Percentage bias in K i observed using simulated modified IFs varied from − 16 to 16% depending on the simulated amplitude and direction of the IF modifications. Subsequent scaling of the PIF reduced these K i biases in most cases (287 out of 290) to < 5%. Conclusions: Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible

Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings

The aims of this work were to create a robust automatic software tool for measurement of the levator hiatal area on transperineal ultrasound (TPUS) volumes and to measure the potential reduction in variability and time taken for analysis in a clinical setting. The proposed tool automatically detects the C-plane (i.e., the plane of minimal hiatal dimensions) from a 3-D TPUS volume and subsequently uses the extracted plane to automatically segment the levator hiatus, using a convolutional neural network. The automatic pipeline was tested using 73 representative TPUS volumes. Reference hiatal outlines were obtained manually by two experts and compared with the pipeline's automated outlines. The Hausdorff distance, area, a clinical quality score, C-plane angle and C-plane Euclidean distance were used to evaluate C-plane detection and quantify levator hiatus segmentation accuracy. A visual Turing test was created to compare the performance of the software with that of the expert, based on the visual assessment of C-plane and hiatal segmentation quality. The overall time taken to extract the hiatal area with both measurement methods (i.e., manual and automatic) was measured. Each metric was calculated both for computer–observer differences and for inter-and intra-observer differences. The automatic method gave results similar to those of the expert when determining the hiatal outline from a TPUS volume. Indeed, the hiatal area measured by the algorithm and by an expert were within the intra-observer variability. Similarly, the method identified the C-plane with an accuracy of 5.76 ± 5.06° and 6.46 ± 5.18 mm in comparison to the inter-observer variability of 9.39 ± 6.21° and 8.48 ± 6.62 mm. The visual Turing test suggested that the automatic method identified the C-plane position within the TPUS volume visually as well as the expert. The average time taken to identify the C-plane and segment the hiatal area manually was 2 min and 35 ± 17 s, compared with 35 ± 4 s for the automatic result. This study presents a method for automatically measuring the levator hiatal area using artificial intelligence-based methodologies whereby the C-plane within a TPUS volume is detected and subsequently traced for the levator hiatal outline. The proposed solution was determined to be accurate, relatively quick, robust and reliable and, importantly, to reduce time and expertise required for pelvic floor disorder assessment