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From Scans to Insights: Using Deep Learning to Estimate Fat and Muscle Volume of Human Eyes

Technology Core Machine Learning | CV
Industry Medical
Potential industries Healthcare
Client Ophthalmology Centre

Summary

AI Superior, in collaboration with an Ophthalmology Centre, has developed an advanced deep learning model to estimate the volume of fat and muscle in human eyes using CT and MRI orbit scans. By analyzing MRI scans, our model successfully segments fat and muscle tissue in each slice, allowing for accurate volume estimation and facilitating before and after volume comparisons following interventions. This groundbreaking project brings new possibilities for understanding and managing ocular health.

Challenge

The client, an Ophthalmology Centre, faced the challenge of accurately estimating the volume of fat and muscle in the human eye. This information is crucial for monitoring eye health, evaluating the effectiveness of interventions, and conducting comparative analyses. Traditional methods for estimating volume required manual measurement, resulting in time-consuming processes and potential errors. The client sought an automated and reliable solution to streamline this critical aspect of eye care.

Solution by AI Superior

AI Superior took on the challenge and focused on analyzing MRI scans to estimate the volume of fat and muscle in the human eye. We employed cutting-edge deep learning techniques to develop an advanced model capable of accurately segmenting fat and muscle tissue in each slice of an MRI orbit scan. By leveraging the model’s capabilities, we achieved highly precise volume estimation for the eye’s anatomical structures. Our deep learning model was designed to handle different views of the eye, including Coronal, Sagittal, and Axial, ensuring comprehensive analysis of the orbital region.

 

Outcome and Implications

AI Superior’s solution has the potential to transform the way ophthalmologists analyze and monitor eye health. By automating the process of segmenting fat and muscle tissue, our model provides precise volume estimations, enabling more comprehensive assessments and facilitating effective interventions. Moreover, our model facilitates before and after volume comparisons, which is particularly valuable for monitoring the effectiveness of interventions or treatments. By quantifying the changes in fat and muscle volume, ophthalmologists can assess the impact of surgical procedures, therapeutic interventions, or disease progression on the ocular structures.

AI Superior continues to lead the way in leveraging artificial intelligence for ophthalmic applications. By combining advanced technologies with medical expertise, we are dedicated to transforming the landscape of eye care. With projects like this and Eye Metrics, AI Superior is redefining possibilities in ophthalmology and delivering innovative solutions that make a meaningful difference in patients’ lives.

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