In recent years, deep convolutional neural networks (CNNs) have shown record-shattering performance in a variety of computer vision problems, such as visual object recognition, detection and segmentation. These methods have also been utilised in medical image analysis domain for lesion segmentation, anatomical segmentation and classification. We present an extensive literature review of CNN techniques applied in brain magnetic resonance imaging (MRI) analysis, focusing on the architectures, pre-processing, data-preparation and post-processing strategies available in these works. The aim of this study is three-fold. Our primary goal is to report how different CNN architectures have evolved, discuss state-of-the-art strategies, condense their results obtained using public datasets and examine their pros and cons. Second, this paper is intended to be a detailed reference of the research activity in deep CNN for brain MRI analysis. Finally, we present a perspective on the future of CNNs in which we hint some of the research directions in subsequent years.
Purpose To assess accuracy and adherence of visual field (VF) home-monitoring in a pilot sample of glaucoma patients. Design Prospective longitudinal feasibility and reliability study. Methods Twenty adults (median 71 years) with an established diagnosis of glaucoma were issued a tablet-perimeter (Eyecatcher), and were asked to perform one VF home-assessment per eye, per month, for 6 months (12 tests total). Before and after home-monitoring, two VF assessments were performed in-clinic using Standard Automated Perimetry (SAP; 4 tests total, per eye). Results All 20 participants could perform monthly home-monitoring, though one participant stopped after 4 months (Adherence: 98%). There was good concordance between VFs measured at home and in the clinic ( r = 0.94, P < 0.001). In 21 of 236 tests (9%) Mean Deviation deviated by more than ±3 dB from the median. Many of these anomalous tests could be identified by applying machine learning techniques to recordings from the tablets’ front-facing camera (Area Under the ROC Curve = 0.78). Adding home-monitoring data to 2 SAP tests made 6 months apart reduced measurement error (between-test measurement variability) in 97% of eyes, with mean absolute error more than halving in 90% of eyes. Median test duration was 4.5 mins ( Quartiles : 3.9 – 5.2 mins). Substantial variations in ambient illumination had no observable effect on VF measurements ( r = 0.07, P = 0.320). Conclusions Home-monitoring of VFs is viable for some patients, and may provide clinically useful data.
Eye movements are altered by visual field loss, and these changes are related to changes in clinical measures. Eye movements recorded while passively viewing images could potentially be used as biomarkers for visual field damage.
Objective:Satisfaction is becoming a popular health-care quality indicator as it reflects the reality of service or care provided. The aim of this study was to assess the level of patients' expectation toward and satisfaction from pharmacy service provided and to identify associated factor that might affect their expectation and satisfaction.Methods:A cross-sectional study was conducted on 287 patients, who were served in five pharmacies of Gondar University Hospital in May 2015. Data regarding socio-demographic characteristics and parameters that measure patients' expectation and satisfaction were collected through interview using the Amharic version of the questionnaire. Data were entered into SPSS version 21, and descriptive statistics, cross-tabs, and binary logistic regressions were utilized. P < 0.05 was used to declare association.Findings:Among 287 respondents involved in the study, 149 (51.9%) claimed to be satisfied with the pharmacy service and setting. Two hundred and twenty-nine (79.4%) respondents have high expectation toward gaining good services. Even though significant association was observed between the pharmacy type and patients level of satisfaction, sociodemographic characteristics of a patient were not found to predict the level of satisfaction. There is a higher level of expectation among study participants who earn higher income per month (>(2000 Ethiopian birr [ETB]) than those who get less income (<1000 ETB).Conclusion:Although patients have a higher level of expectation toward pharmacy services, their satisfaction from the service was found to be low.
ObjectivesTo explore the acceptability of home visual field (VF) testing using Eyecatcher among people with glaucoma participating in a 6-month home monitoring pilot study.DesignQualitative study using face-to-face semistructured interviews. Transcripts were analysed using thematic analysis.SettingParticipants were recruited in the UK through an advertisement in the International Glaucoma Association (now Glaucoma UK) newsletter.ParticipantsTwenty adults (10 women; median age: 71 years) with a diagnosis of glaucoma were recruited (including open angle and normal tension glaucoma; mean deviation=2.5 to −29.9 dB).ResultsAll participants could successfully perform VF testing at home. Interview data were coded into four overarching themes regarding experiences of undertaking VF home monitoring and attitudes towards its wider implementation in healthcare: (1) comparisons between Eyecatcher and Humphrey Field Analyser (HFA); (2) capability using Eyecatcher; (3) practicalities for effective wider scale implementation; (4) motivations for home monitoring.ConclusionsParticipants identified a broad range of benefits to VF home monitoring and discussed areas for service improvement. Eyecatcher was compared positively with conventional VF testing using HFA. Home monitoring may be acceptable to at least a subset of people with glaucoma.
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