Towards a Connected Mobile Cataract Screening System: A Future Approach.
Wan Mimi Diyana Wan ZakiHaliza Abdul MutalibLaily Azyan RamlanAini HussainMustapha AouachePublished in: Journal of imaging (2022)
Advances in computing and AI technology have promoted the development of connected health systems, indirectly influencing approaches to cataract treatment. In addition, thanks to the development of methods for cataract detection and grading using different imaging modalities, ophthalmologists can make diagnoses with significant objectivity. This paper aims to review the development and limitations of published methods for cataract detection and grading using different imaging modalities. Over the years, the proposed methods have shown significant improvement and reasonable effort towards automated cataract detection and grading systems that utilise various imaging modalities, such as optical coherence tomography (OCT), fundus, and slit-lamp images. However, more robust and fully automated cataract detection and grading systems are still needed. In addition, imaging modalities such as fundus, slit-lamps, and OCT images require medical equipment that is expensive and not portable. Therefore, the use of digital images from a smartphone as the future of cataract screening tools could be a practical and helpful solution for ophthalmologists, especially in rural areas with limited healthcare facilities.
Keyphrases
- optical coherence tomography
- loop mediated isothermal amplification
- deep learning
- high resolution
- healthcare
- diabetic retinopathy
- cataract surgery
- real time pcr
- machine learning
- label free
- convolutional neural network
- high throughput
- randomized controlled trial
- current status
- optic nerve
- systematic review
- mass spectrometry
- quantum dots
- health insurance