Latest AI Research at UC Berkeley developed a tracking algorithm for tracking the Dynamics of the Tear Film Lipid Layer

On Dec 16, 2022

The tear film must spread quickly and uniformly throughout the ocular surface for clear vision and good ocular health. One of the ocular morbidities that are most commonly observed is DED. The TFOS DEWS II defines dry eye (DE) as a multifactorial illness of the ocular surface with visual symptoms and a loss of tear film homeostasis, with tear film instability and hyperosmolarity, ocular surface inflammation and injury, and neurosensory abnormalities playing etiological roles. A variety of variables influences the genesis of DED.

The most extensively researched aspect, tear film instability, is influenced by the interaction of the complex multi-layered multi-layered tear film stretched over the ocular surface and the biomechanical activity of the eyelids. On the 1–10 m thickness of the human tear film, complex combinations of oily substances known as tear lipids make up the outermost layers. The tear lipid layer and its dynamics during inter-blink intervals may be seen and recorded using micro-interferometric tools. The lack of numerical methods to accurately distinguish between dry eye subtypes, such as evaporative, aqueous-deficient, mixed, and DE caused by excessive drainage, is a major barrier to current DED diagnoses.

Figure 1: The feature points in Figures 1a to 1d trace the time-dependent upward spread of the lipid layer. The frames in Figures 1e to 1h are identical, but they have been sharpened to make the lipid layer stand out more. The matching figures in Figures 1e to 1h are labelled with the time equivalent, whereas Figures 1a to 1d are labelled with the frame number. Frame 1 in Figure 1a, for instance, corresponds to frame 1 in Figure 1e indicated at 0.03 seconds.

The stability of the tear film is greatly influenced by the lipid layer, which may provide information about this condition with a large worldwide impact. This is the only earlier study examining the lipid layer distribution in the tear film. A better DED diagnosis may result from numerical analysis of the vertical and horizontal propagation rates of tear lipid films during inter-blinks, which can reveal important details about tear lipid film quality, viscoelasticity, mobility, and stability. They look at computer vision methods as potential tools for creating a brand-new DED diagnosis paradigm.

Meet Hailo-8™: An AI Processor That Uses Computer Vision For Multi-Camera Multi-Person Re-Identification (Sponsored)

They discover that an exponential decay curve may suit the height displacement of the film spread. In addition, they find out that the tear volume reduces according to the rate of the lipid layer spread. Using a video-interferometer, they gather interference pictures from the lipid layer of the tear film. The lipid layer spreading is then manually followed using photo-editing software. Their research intends to autonomously follow the spreading of the lipid layer using contemporary computer vision. A selection of eleven movies depicting the lipid layer spread in the tear film that was captured using a micro-interferometer is annotated. A tracking algorithm built on several foundational computer vision methods is created.

Check out the Paper and Project. All Credit For This Research Goes To Researchers on This Project. Also, don’t forget to join our Reddit page and discord channel, where we share the latest AI research news, cool AI projects, and more.

Aneesh Tickoo is a consulting intern at MarktechPost. He is currently pursuing his undergraduate degree in Data Science and Artificial Intelligence from the Indian Institute of Technology(IIT), Bhilai. He spends most of his time working on projects aimed at harnessing the power of machine learning. His research interest is image processing and is passionate about building solutions around it. He loves to connect with people and collaborate on interesting projects.

Credit: Source link