Automatic Segmentation of Retinal Vasculature

Segmentation of retinal vessels from retinal fundus images is the key step in the automatic retinal image analysis. In this paper, we propose a new unsupervised automatic method to segment the retinal vessels from retinal fundus images. Contrast enhancement and illumination correction are carried out through a series of image processing steps followed by adaptive histogram equalization and anisotropic diffusion filtering. This image is then converted to a gray scale using weighted scaling. The vessel edges are enhanced by boosting the detail curvelet coefficients. Optic disk pixels are removed before applying fuzzy C-mean classification to avoid the misclassification. Morphological operations and connected component analysis are applied to obtain the segmented retinal vessels. The performance of the proposed method is evaluated using DRIVE database to be able to compare with other state-of-art supervised and unsupervised methods. The overall segmentation accuracy of the proposed method is 95.18% which outperforms the other algorithms.Comment: Published at IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 201

Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/non-COVID-19 Frameworks using Artificial Intelligence Paradigm: A Narrative Review

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for lowincome countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, lowcost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework

Bilateral fusion of mandibular primary teeth

The aim of the report was to highlight the rarity of occurrence of bilaterally fused mandibular primary lateral incisors and canines by virtue of the number of such cases reported in literature; to identify congenital absence of successor teeth;and to evaluate their pulpal morphologies to understand the type of fusion.<b> </b> Clinical observation along with an orthopantomograph and periapical radiographs were used to arrive at a diagnosis. The pulpal morphologies varied in each of the fused teeth although both were fusions of the Complete type. There was congenital absence of the permanent mandibular lateral incisors, bilaterally. It was a case of bilateral fusion of mandibular primary lateral incisors and canines of the Complete type with congenitally absent mandibular permanent lateral incisors. Only 13 such cases have been previously reported in literature

Application of Model Predictive Control in Supply Chain Processes

Questa tesi esamina la pianificazione del fabbisogno di materiali Material (Requirements Planning MRP) da una diversa prospettiva, quella delle matrici. L'intero processo viene infatti sviluppato utilizzando una serie di matrici che si evolvono nel tempo in un approccio basato sul sistema tempo-variante. Invece di iterare lungo i livelli della distinta base (materiali), calcoleremo pertanto, simultaneamente, tutti i requisiti dei materiali per tutti i prodotti in un dato momento. Il vantaggio principale di questo approccio è la velocità: possiamo calcolare MPS (Piano Principale di Produzione Master Production Schedule e MRP in pochi secondi. Nello sviluppo di questa idea ci muoveremo all'interno del perimetro di SIOP (Pianificazione vendite, inventario e operazioni (Sales, Inventory, Operations Planning), seguendo un approccio basato sul modello del controllo predittivo. Inizieremo da un'analisi dettagliata dei concetti e delle tecniche di pianificazione della domanda, sviluppando, poi, in dettaglio, i concetti centrali e l'approccio basato sulle matrici per il calcolo del MPS e MRP. Dopo la presentazione del metodo attraverso il suo utilizzo per il calcolo del Piano Principale di Produzione, estenderemo questo approccio al passaggio successivo, cioè alla pianificazione dei fabbisogni di materiali (MRP), dove vedremo come le richieste dei singoli articoli vengono ulteriormente esplose fino ai componenti seguendo la distinta base dell'articolo. In una industria multi-prodotto con prodotti complessi e con componenti che potrebbero far parte di più di un prodotto, questo calcolo, sebbene concettualmente semplice, diventa un lavoro pesantemente complesso. Il cambiamento nella struttura del prodotto, il cambiamento nella distinta dei materiali, l'obsolescenza e l'introduzione di nuovi prodotti complica ulteriormente questo calcolo. Al posto dell'approccio iterativo, ampiamente utilizzato in letteratura corrente e in tutte le attuali applicazioni software, noi utilizzeremo allora un approccio basato sulle matrici. Invece di calcolare il fabbisogno articolo per articolo seguendo i vari livelli della distinta base, la struttura a matrici proposta eseguirà i calcoli per tutti gli articoli, di un determinato periodo di tempo, tutto in una sola volta. Con MPS e MRP calcolati, estenderemo l'approccio a matrice al calcolo dei livelli di inventario e del fabbisogno di capacità produttiva richiesta per soddisfare l'MPS. Durante il calcolo dei livelli di inventario vedremo anche un'applicazione importante e diretta di questo metodo nel calcolo delle scorte. Nel calcolo dei fabbisogni di capacità ci concentreremo, in particolare, su come vengono calcolati i fabbisogni di lavoro diretto con l'utilizzo delle matrici. L'ultima e importante applicazione della modellistica di sistema che vedremo, è nella pianificazione finanziaria, in particolare per la previsione del flusso di cassa.This thesis analyses the Material Requirements Planning (MRP) from an uncommon perspective of matrices. The whole process is developed using a set of matrices evolving over time in a time variant system approach. Instead of iterating along Bill Of Material (BOM) levels we will simultaneously calculate the materials requirement for all products at any given instance of time. The main advantage of this approach is the speed: we can calculate MPS and MRP in seconds. In the development of this idea we will be following a model predictive control approach, moving along the framework of SIOP (Sales, Inventory and Operations Planning), starting with a detailed analysis of demand planning concepts and techniques. We will then develop in detail the core concepts of the matrix approach to material requirements calculation, starting with Master Production Schedule (MPS). We will extend this approach to the next step, the Material Requirements Planning (MRP) where we will see how the demands for the single items are further exploded down to the components of that item. In a multi-product industry with complex products and with components that could be part of more than one product, this calculation though conceptually simple become a heavily complex job. Change in product structure, change in bill of materials to say it in a more technical term, obsolescence and new product introductions further complicates this calculation. Instead of the iterative approach widely used in literature and all current software applications, we will use a matrix approach here also. Instead of calculating the requirements item per item and then summing it up, the proposed matrix structure will do the calculations for all the items for a specific time period all at once. With the Master Production Schedule and Material Requirements Planning calculated, we will also extend this matrix approach to calculate the inventory levels and capacity requirements. While calculating inventory levels we will also see an important and direct application of this method in calculating the stockouts. In calculation of capacity requirement we will focus specifically on how direct labour requirements are calculated using the matrices. A last and important application of system modelling is in financial planning, especially on a systems approach to stockout forecasting

The prevalence of early childhood caries and treatment needs among children attending Anganwadi centers in Goa state: A cross-sectional survey

Context: The prevalence of early childhood caries (ECC) is widespread, as reported in studies conducted in various states across India. Many children residing in the rural areas attend Anganwadi centers for preprimary education, nourishment, and health care. Aim: The aim of the study was to determine the prevalence of ECC among children attending Anganwadi centers in the state of Goa and their treatment needs. Settings and Design: The study was approved by the Institutional Ethical Committee of Goa Dental College and Hospital. The study was carried out in Anganwadi centers spanning the various districts and talukas of Goa state. Materials and Methods: The decayed, missing, and filled teeth (dmft) index was recorded in 3–5-year-old children along with treatment needs as per the modified WHO pro forma. Statistical Analysis: Statistical software (STATA) for data science by StataCorp LLC (version 17), descriptive statistics, and Chi-square test. Results: A total of 386 children were examined, out of which 47% had ECC. The prevalence of ECC was highest in Canacona and the least in Tiswadi talukas. The severity and occurrence of ECC were found to the proportional to age. With regard to treatment needs, 8.55% needed restoration of at least one surface, 10.88% needed restoration of 2 or more surfaces, 5.44% required a crown, 11.4% needed pulpal treatment, and 6.74% needed extractions. Within the dmft component, the percentage of decayed teeth was 46.89%, followed by filled (0.52%) and missing (0.52%) teeth. Conclusion: The prevalence and severity of ECC in children attending Anganwadi centers in Goa were found to be large and proportional with increasing age

Reliability of the magnification method for localisation of ectopic upper canines

To evaluate the reliability of the magnification method for localisation of palatally placed canines

University of Auckland Diabetic Retinopathy (UoA-DR) Database- END USER LICENCE AGREEMENT

<b>INTRODUCTION</b><br>The University of Auckland Retinopathy Database has been created as part of the research carried out at the University of Auckland aimed at developing an automatic screening system to screen patients affected by diabetic retinopathy. The Database has been developed in collaboration with the Al-Salama Eye Hospital and collaborators from India.<br>The Database includes the following:<br>Retinal images: approx. 200 taken by Fundus camera, mostly of individuals affected with diabetic retinopathy Resolution: 2124 x 2056 pixels Size: approx. 500MB Extracted features: 3 x per image (retinal vessels, optic disc boundary and centre, fovea centre location)<br><br><b>REQUESTS FOR ACCESS</b><br>Requests for access to the Database are considered on a case-by-case basis. If you wish to access the Database, please contact the University at <u><i>[email protected]</i></u>, with a copy to <u><i>[email protected]</i></u>, including your email contact details and a signed copy of this End User Licence Agreement.<br>If your request for access is approved, the University will email you a private link to download the Database.<br><br><br