Known as MTCD, the proposed multi-task deep learning algorithm is inexpensive, uses eye images captured in the near-infrared domain and is computationally inexpensive, yielding high accuracy.
The proposed segmentation algorithm efficiently and effectively detects non-ideal eye boundaries.
AI-Based Solution For Cataract Detection
In traditional methods, cataracts are mainly detected through fundus images, where image acquisition is costlier and needs experts to handle the fundus cameras.
The team described their algorithm in a paper published in Science Direct.
“Currently, a large number of patients with cataracts have to visit secondary and tertiary care centres. The availability of such a solution can assist doctors at the primary health centres in helping such patients,” said Richa Singh, Professor, Department of Computer Science and Engineering, IIT Jodhpur, in a statement.
“We are extending this research to include both cataract and diabetic retinopathy in the solution and have collaborated with multiple hospitals in the country for domain expertise, data collection, and validation of the solution,” added Mayank Vatsa, Professor, Department of Computer Science and Engineering, IIT Jodhpur.
Source: IANS
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