A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images

Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the nerve structures can assist the early diagnosis of this disease. This paper proposes a robust, fast and fully automatic nerve segmentation and morphometric parameter quantification system for corneal confocal microscope images. The segmentation part consists of three main steps. First, a preprocessing step is applied to enhance the visibility of the nerves and remove noise using anisotropic diffusion filtering, specifically a Coherence filter followed by Gaussian filtering. Second, morphological operations are applied to remove unwanted objects in the input image such as epithelial cells and small nerve segments. Finally, an edge detection step is applied to detect all the nerves in the input image. In this step, an efficient algorithm for connecting discontinuous nerves is proposed. In the morphometric parameters quantification part, a number of features are extracted, including thickness, tortuosity and length of nerve, which may be used for the early diagnosis of diabetic polyneuropathy and when planning Laser-Assisted in situ Keratomileusis (LASIK) or Photorefractive keratectomy (PRK). The performance of the proposed segmentation system is evaluated against manually traced ground-truth images based on a database consisting of 498 corneal sub-basal nerve images (238 are normal and 260 are abnormal). In addition, the robustness and efficiency of the proposed system in extracting morphometric features with clinical utility was evaluated in 919 images taken from healthy subjects and diabetic patients with and without neuropathy. We demonstrate rapid (13 seconds/image), robust and effective automated corneal nerve quantification. The proposed system will be deployed as a useful clinical tool to support the expertise of ophthalmologists and save the clinician time in a busy clinical setting

Automated Quantification of Neuropad Improves Its Diagnostic Ability in Patients with Diabetic Neuropathy.

PublishedResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tNeuropad is currently a categorical visual screening test that identifies diabetic patients at risk of foot ulceration. The diagnostic performance of Neuropad was compared between the categorical and continuous (image-analysis (Sudometrics)) outputs to diagnose diabetic peripheral neuropathy (DPN). 110 subjects with type 1 and 2 diabetes underwent assessment with Neuropad, Neuropathy Disability Score (NDS), peroneal motor nerve conduction velocity (PMNCV), sural nerve action potential (SNAP), Deep Breathing-Heart Rate Variability (DB-HRV), intraepidermal nerve fibre density (IENFD), and corneal confocal microscopy (CCM). 46/110 patients had DPN according to the Toronto consensus. The continuous output displayed high sensitivity and specificity for DB-HRV (91%, 83%), CNFD (88%, 78%), and SNAP (88%, 83%), whereas the categorical output showed high sensitivity but low specificity. The optimal cut-off points were 90% for the detection of autonomic dysfunction (DB-HRV) and 80% for small fibre neuropathy (CNFD). The diagnostic efficacy of the continuous Neuropad output for abnormal DB-HRV (AUC: 91%, P = 0.0003) and CNFD (AUC: 82%, P = 0.01) was better than for PMNCV (AUC: 60%). The categorical output showed no significant difference in diagnostic efficacy for these same measures. An image analysis algorithm generating a continuous output (Sudometrics) improved the diagnostic ability of Neuropad, particularly in detecting autonomic and small fibre neuropathy.National Institute of Health (NIH)Juvenile Diabetes Research Foundation (JDRF

Enhancing Biometric-Capsule-based Authentication and Facial Recognition via Deep Learning

In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based authentication systems. Though these systems demonstrate remarkable performance and have seen wide acceptance, they present unique and pressing security and privacy concerns. One proposed method which addresses these concerns is the elegant, fusion-based BioCapsule method. The BioCapsule method is provably secure, privacy-preserving, cancellable and flexible in its secure feature fusion design. In this work, we extend BioCapsule to face-based recognition. Moreover, we incorporate state-of-art deep learning techniques into a BioCapsule-based facial authentication system to further enhance secure recognition accuracy. We compare the performance of an underlying recognition system to the performance of the BioCapsule-embedded system in order to demonstrate the minimal effects of the BioCapsule scheme on underlying system performance. We also demonstrate that the BioCapsule scheme outperforms or performs as well as many other proposed secure biometric techniques

Preoperative Red Cell Distribution Width and 30-day mortality in older patients undergoing non-cardiac surgery: a retrospective cohort observational study

Increased red cell distribution width (RDW) is associated with poorer outcomes in various patient populations. We investigated the association between preoperative RDW and anaemia on 30-day postoperative mortality among elderly patients undergoing non-cardiac surgery. Medical records of 24,579 patients aged 65 and older who underwent surgery under anaesthesia between 1 January 2012 and 31 October 2016 were retrospectively analysed. Patients who died within 30 days had higher median RDW (15.0%) than those who were alive (13.4%). Based on multivariate logistic regression, in our cohort of elderly patients undergoing non-cardiac surgery, moderate/severe preoperative anaemia (aOR 1.61, p = 0.04) and high preoperative RDW levels in the 3rd quartile (>13.4% and ≤14.3%) and 4th quartile (>14.3%) were significantly associated with increased odds of 30-day mortality - (aOR 2.12, p = 0.02) and (aOR 2.85, p = 0.001) respectively, after adjusting for the effects of transfusion, surgical severity, priority of surgery, and comorbidities. Patients with high RDW, defined as >15.7% (90th centile), and preoperative anaemia have higher odds of 30-day mortality compared to patients with anaemia and normal RDW. Thus, preoperative RDW independently increases risk of 30-day postoperative mortality, and future risk stratification strategies should include RDW as a factor

The diagnostic and prognostic value of red cell distribution width in cardiovascular disease, current status and prospective

The red blood cell distribution width (RDW) is an index of the heterogeneity of circulating red blood cell size, which along with other standard complete blood count (CBC) parameters are used to identify hematological system diseases. Besides hematological disorders, several clinical studies have shown that an increased in the RDW may be associated with other diseases including acute pancreatitis, chronic kidney disease, gastrointestinal disorders, cancer, and of special interest in this review, cardiovascular disease (CVD). The diagnostic and prognostic value of RDW in different CVD (acute coronary syndrome, ischemic cerebrovascular disease, peripheral artery disease, atrial fibrillation, heart failure, and acute ischemic stroke) has been reviewed in this article, to provide an understanding how its measurement may be applied to improve the management of these conditions.Keywords: RDW, Biomarker, Cardiovascular disease

Clinical Usefulness of Measuring Red Blood Cell Distribution Width in Patients with Hepatitis B

BACKGROUND: Red blood cell distribution width (RDW), an automated measure of red blood cell size heterogeneity (e.g., anisocytosis) that is largely overlooked, is a newly recognized risk marker in patients with cardiovascular diseases, but its role in persistent viral infection has not been well-defined. The present study was designed to investigate the association between RDW values and different disease states in hepatitis B virus (HBV)-infected patients. In addition, we analyzed whether RDW is associated with mortality in the HBV-infected patients. METHODOLOGY/PRINCIPAL FINDINGS: One hundred and twenty-three patients, including 16 with acute hepatitis B (AHB), 61 with chronic hepatitis B (CHB), and 46 with chronic severe hepatitis B (CSHB), and 48 healthy controls were enrolled. In all subjects, a blood sample was collected at admission to examine liver function, renal function, international normalized ratio and routine hematological testing. All patients were followed up for at least 4 months. A total of 10 clinical chemistry, hematology, and biochemical variables were analyzed for possible association with outcomes by using Cox proportional hazards and multiple regression models. RDW values at admission in patients with CSHB (18.30±3.11%, P<0.001), CHB (16.37±2.43%, P<0.001) and AHB (14.38±1.72%, P<0.05) were significantly higher than those in healthy controls (13.03±1.33%). Increased RDW values were clinically associated with severe liver disease and increased 3-month mortality rate. Multivariate analysis demonstrated that RDW values and the model for end-stage liver disease score were independent predictors for mortality (both P<0.001). CONCLUSION: RDW values are significantly increased in patients with hepatitis B and associated with its severity. Moreover, RDW values are an independent predicting factor for the 3-month mortality rate in patients with hepatitis B

Current clinical applications of spectral tissue Doppler echocardiography (E/E' ratio) as a noninvasive surrogate for left ventricular diastolic pressures in the diagnosis of heart failure with preserved left ventricular systolic function

Congestive heart failure with preserved left ventricular systolic function has emerged as a growing epidemic medical syndrome in developed countries, which is characterized by high morbidity and mortality rates. Rapid and accurate diagnosis of this condition is essential for optimizing the therapeutic management. The diagnosis of congestive heart failure is challenging in patients presenting without obvious left ventricular systolic dysfunction and additional diagnostic information is most commonly required in this setting. Comprehensive Doppler echocardiography is the single most useful diagnostic test recommended by the ESC and ACC/AHA guidelines for assessing left ventricular ejection fraction and cardiac abnormalities in patients with suspected congestive heart failure, and non-invasively determined basal or exercise-induced pulmonary capillary hypertension is likely to become a hallmark of congestive heart failure in symptomatic patients with preserved left ventricular systolic function. The present review will focus on the current clinical applications of spectral tissue Doppler echocardiography used as a reliable noninvasive surrogate for left ventricular diastolic pressures at rest as well as during exercise in the diagnosis of heart failure with preserved left ventricular systolic function. Chronic congestive heart failure, a disease of exercise, and acute heart failure syndromes are characterized by specific pathophysiologic and diagnostic issues, and these two clinical presentations will be discussed separately

Appearance-based biometric recognition: Secure authentication and cancellability

Although, biometrics provide high-confidence and trusted security, they suffer from a fatal weakness that emerges from permanence and limitation in quantities. Such a drawback puts biometric data under a substantial risk of fraudulent, which makes the replacement of traditional authentication systems infeasible with the lack of proper biometric data protection. This paper presents a novel biometric protection method to generate secure facial biometric templates used in statistical-based recognition algorithms such as 2DPCA. Original biometrics are polynomially transformed to the secure domain, where cooccurrence matrices are used to generate the final templates. The paper presents a unique relationship established by the Hadamard product within the transformation. The generated secure templates are used in the same fashion as original biometrics for evaluations using 2DPCA without any change to the recognition algorithm. And yet, evaluations confirm high security with enhanced recognition accuracy by 3% and 4.5% over the original and other transformed data respectively. © 2007 IEEE