Artificial Intelligence Algorithm to Detect Cataracts

The eye images obtained by low-cost near-infrared (NIR) cameras powered by artificial intelligence (AI) can assist in low design costs, ease of use, and practical solutions for cataract detection. The team proposed a multitask deep learning AI-based algorithm for automated cataract detection. It involves iris segmentation and multitask network classification.

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 Prof. Richa Singh of 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 Prof. Mayank Vatsa of IIT Jodhpur.

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Source-IANS