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Graphical User Interface (GUI) of digital index evaluation system for finger clubbing identification

Masra, S.M.W., Goh, K.L., Muhammad, M.S., Sapawi, R., Kipli, K., Shahrom, N.S., et al.

Scientific Research Journal, 2017;14(2):99-112.
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This paper presents the development of a Graphical User Interface (GUI)
for calculating the sum of nail-fold (NF) and distal interphalangeal joint
(DIP) ratios for all ten fingers. The sum of NF:DIP ratios for all ten fingers
leads to the Digital Index (DI) that was used as the measure for identifying
and determining the presence of finger clubbing symptom. This GUI system
was developed to serve as a simple and user-friendly interface for clinicians
to calculate DI value of patients in a busy clinic practice. It is also equipped
with the capability to keep the patient’s past diagnosis medical check-up
data for future monitoring purposes. The result shows that the developed
system helps the clinicians to perform calculation of DI value and identify
the presence of finger clubbing in a very short time. The average time taken
to measure both NF and DIP circumferences using Finger Clubbing Meter,
and to compute DI values using Digital Index Evaluation System (DIES)
interface is 6:36 ± 1:24 minutes (Mean ± SD) .This system is expected to
contribute in detecting the finger clubbing problem at early stage of so the
treatment can be performed immediately.
Fulltext A Review on the Extraction of Quantitative Retinal Microvascular Image Feature

Kipli K, Hoque ME, Lim LT, Mahmood MH, Sahari SK, Sapawi R, et al.

Comput Math Methods Med, 2018;2018:4019538.
PMID: 30065780 DOI: 10.1155/2018/4019538

Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric features measurements such as vessel tortuosity, branching angles, branching coefficient, vessel diameter, and fractal dimension. These extracted markers or characterized fundus digital image features provide insights and relates quantitative retinal vascular topography abnormalities to various pathologies such as diabetic retinopathy, macular degeneration, hypertensive retinopathy, transient ischemic attack, neovascular glaucoma, and cardiovascular diseases. Apart from that, this noninvasive research tool is automated, allowing it to be used in large-scale screening programs, and all are described in this present review paper. This paper will also review recent research on the image processing-based extraction techniques of the quantitative retinal microvascular feature. It mainly focuses on features associated with the early symptom of transient ischemic attack or sharp stroke.
Development of 3D-printed universal adapter in enhancing retinal imaging accessibility

Latip AAA, Kipli K, Kamaruddin AMNA, Sapawi R, Lias K, Jalil MA, et al.

3D Print Med, 2024 Jul 19;10(1):23.
PMID: 39028380 DOI: 10.1186/s41205-024-00231-0

BACKGROUND: The revolutionary technology of smartphone-based retinal imaging has been consistently improving over the years. Smartphone-based retinal image acquisition devices are designed to be portable, easy to use, and cost-efficient, which enables eye care to be more widely accessible especially in geographically remote areas. This enables early disease detection for those who are in low- and middle- income population or just in general has very limited access to eye care. This study investigates the limitation of smartphone compatibility of existing smartphone-based retinal image acquisition devices. Additionally, this study aims to propose a universal adapter design that is usable with an existing smartphone-based retinal image acquisition device known as the PanOptic ophthalmoscope. This study also aims to simulate the reliability, validity, and performance overall of the developed prototype.
METHODS: A literature review has been conducted that identifies the limitation of smartphone compatibility among existing smartphone-based retinal image acquisition devices. Designing and modeling of proposed adapter were performed using the software AutoCAD 3D. For the proposed performance evaluation, finite element analysis (FEA) in the software Autodesk Inventor and 5-point scale method were demonstrated.
RESULTS: Published studies demonstrate that most of the existing smartphone-based retinal imaging devices have compatibility limited to specific older smartphone models. This highlights the benefit of a universal adapter in broadening the usability of existing smartphone-based retinal image acquisition devices. A functional universal adapter design has been developed that demonstrates its compatibility with a variety of smartphones regardless of the smartphone dimension or the position of the smartphone's camera lens. The proposed performance evaluation method generates an efficient stress analysis of the proposed adapter design. The end-user survey results show a positive overall performance of the developed universal adapter. However, a significant difference between the expert's views on the developed adapter and the quality of images is observed.
CONCLUSION: The compatibility of existing smartphone-based retinal imaging devices is still mostly limited to specific smartphone models. Besides this, the concept of a universal and suitable adapter for retinal imaging using the PanOptic ophthalmoscope was presented and validated in this paper. This work provides a platform for future development of smartphone-based ophthalmoscope that is universal.

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