Yogi Kanagasingam

A mobile-health system to manage Chronic Obstructive Pulmonary Disease patients at home

Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality in Australia and globally, and leads to a substantial burden on healthcare services. Effective and timely management of patients with COPD has been essential to alleviate COPD exacerbation, improve the quality of life, and consequently reduce the economic burden. To achieve this, a mobile and internet technologies assisted home care model (M-COPD) was developed to assist clinicians to remotely monitor and manage COPD conditions and events. This paper will focus on the technical aspect of M-COPD system by describing its setup and discussing how the M-COPD could address the clinical needs in monitoring and managing COPD conditions of patients at home.

A pilot study of a mobile-phone-based home monitoring system to assist in remote interventions in cases of acute exacerbation of COPD

We conducted a six-month feasibility study of a mobile-phone-based home monitoring system, called M-COPD. Patients with a history of moderate Acute Exacerbation of COPD (AECOPD) were given a mobile phone to record major symptoms (dyspnoea, sputum colour and volume), minor symptoms (cough and wheezing) and vital signs. A care team remotely monitored the recorded data and provided clinical interventions. Eight patients (mean age 65 years) completed the trial. Ten acute exacerbations occurred during the trial and were successfully treated at home. Prior to the AECOPD episode, the combined score of the major symptoms increased significantly (P < 0.05). Following the intervention, it decreased significantly (P < 0.05) within two weeks and returned to the baseline. The score of the minor symptoms also increased significantly (P < 0.05), but the decrease following the intervention was not significant. There were significantly fewer hospital admissions during the trial, fewer ED presentations and fewer GP visits than in a six-month matched period in the preceding year. The results demonstrate the potential of home monitoring for analysing respiratory symptoms for early intervention of AECOPD.

Drusen quantification for early identification of age related macular degeneration (AMD) using color fundus imaging

Age-related macular degeneration (AMD) is a major cause of visual impairment in the elderly and identifying people with the early stages of AMD is important when considering the design and implementation of preventative strategies for late AMD. Quantification of drusen size and total area covered by drusen is an important risk factor for progression. In this paper, we propose a method to detect drusen and quantify drusen size along with the area covered with drusen in macular region from standard color retinal images. We used combined local intensity distribution, adaptive intensity thresholding and edge information to detect potential drusen areas. The proposed method detected the presence of any drusen with 100% accuracy (50/50 images). For drusen detection accuracy (DDA), the segmentations produced by the automated method on individual images achieved mean sensitivity and specificity values of 74.94% and 81.17%, respectively.

Development and Practice of Store-and-Forward Telehealth Systems in Ophthalmology Dental and Emergency.

Store-and-forward (S&F) telehealth system has been becoming an increasing application in remote medical consultations. In this paper, we will introduce three novel S&F telehealth systems we developed for ophthalmological, dental and emergency applications. We will explain the general system architecture of the S&F systems. Then we will focus on the specific features and components in each system implemented for meeting their respective clinical requirements. In the final section we will present further implementation details and practices and provide discussions.

Retinal video recordings at different compression levels: a novel video-based imaging technology for diabetic retinopathy screening

BackgroundTo evaluate the optimal compression level of retinal color digital video recordings, a novel video-based imaging technology, in screening for diabetic retinopathy (DR).DesignEvaluation of a diagnostic technique.MethodsA total of 36 retinal videos, captured using EyeScan (Ophthalmic Imaging System), were compressed from original uncompressed file size of 1 GB (gigabyte) to four different compression levels—100 MB (megabyte) (Group 1); 30 MB (Group 2); 20 MB (Group 3); and 5 MB (Group 4). The videos were subsequently interpreted by an ophthalmologist and a resident using the International Clinical Diabetic Retinopathy Severity Scales.Main outcome measuresThe sensitivity, specificity and κ coefficient for DR grading detected by were calculated for each compression level (Groups 1–4), with reference to the original uncompressed retinal videos.ResultsGroups 1, 2, and 3 graded by both readers had sensitivity and specificity >90% in detecting DR, whereas for group 4, the sensitivity and specificity were 70.6% and 94.7% for ophthalmologist and 80.0% and 72.2% medical officer, respectively. The κ correlation in detecting DR for groups 1, 2, and 3 were >0.95, whereas for Group 4, the κ was 0.76 and 0.66 for ophthalmologist and medical officer, respectively.ConclusionRetinal video recording is a novel and effective DR screening technique with high sensitivity, specificity and κ correlation. With its compressibility, this is a potential effective technique that can be widely implemented in a routine, mobile, and tele-ophthalmology setting for DR screening services.

Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation

Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.

Detection and measurement of retinal blood vessel pulsatile motion

Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. Pulsatile properties caused by cardiac rhythm, such as spontaneous venous pulsation (SVP) and pulsatile motion of small arterioles, can be visualized by dynamic retinal imaging techniques and provide clinical significance. In this paper, we aim at vessel pulsatile motion detection and measurement. We proposed a novel approach for pulsatile motion measurement of retinal blood vessels by applying retinal image registration, blood vessel detection and blood vessel motion detection and measurement on infrared retinal image sequences. The performance of the proposed methods was evaluated on 8 image sequences with 240 images. A preliminary result has demonstrated the good performance of the method for blood vessel pulsatile motion observation and measurement.

Diabetic retinopathy screening: can the viewing monitor influence the reading and grading outcomes.

PurposeTo evaluate the accuracy of different viewing monitors for image reading and grading of diabetic retinopathy (DR).DesignSingle-centre, experimental case series—evaluation of reading devices for DR screening.MethodA total of 100 sets of three-field (optic disc, macula, and temporal views) colour retinal still images (50 normal and 50 with DR) captured by FF 450 plus (Carl Zeiss) were interpreted on 27-inch iMac, 15-inch MacBook Pro, and 9.7-inch iPad. All images were interpreted by a retinal specialist and a medical officer. We calculated the sensitivity and specificity of 15-inch MacBook Pro and 9.7-inch iPad in detection of DR signs and grades with reference to the reading outcomes obtained using a 27-inch iMac reading monitor.ResultsIn detection of any grade of DR, the 15-inch MacBook Pro had sensitivity and specificity of 96% (95% confidence interval (CI): 85.1–99.3) and 96% (95% CI: 85.1–99.3), respectively, for retinal specialist and 91.5% (95% CI: 78.7–97.2) and 94.3% (95% CI: 83.3–98.5), respectively, for medical officer, whereas for 9.7-inch iPad, they were 91.8% (95% CI: 79.5–97.4) and 94.1% (95% CI: 82.8–98.5), respectively, for retinal specialist and 91.3% (95% CI: 78.3–97.1) and 92.6% (95% CI: 81.3–97.6), respectively, for medical officer.ConclusionThe 15-inch MacBook Pro and 9.7-inch iPad had excellent sensitivity and specificity in detecting DR and hence, both screen sizes can be utilized to effectively interpret colour retinal still images for DR remotely in a routine, mobile or tele-ophthalmology setting. Future studies could explore the use of more economical devices with smaller viewing resolutions to reduce cost implementation of DR screening services.

Light and portable novel device for diabetic retinopathy screening

Background:  To validate the use of an economical portable multipurpose ophthalmic imaging device, EyeScan (Ophthalmic Imaging System, Sacramento, CA, USA), for diabetic retinopathy screening.