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In the medical field, demand for technological advances that can speed data analysis and be less prone to human error continues to increase. Robert Clements, associate professor in the Department of Biological Sciences at �鶹��Ƶ, recently received a federal grant to continue his work creating a more efficient and improved system to analyze medical data that will benefit not only the biomedical industry but also students at �鶹��Ƶ.

“Currently, MRI scans and microscopy images contain such large amounts of data that it takes countless hours to analyze,” said Clements. “Often times, we have to split up the data into sub-samples or smaller groups to represent a larger set of data”

Further, this type of analyzing takes a large amount of time and is not always 100% accurate. Errors in analyzing scans can lead to flaws or inconsistencies in the data, and incorrect medical decisions.

Clements explained that by creating algorithms to automate processing, it will allow less room for error and mistake. “Once completed, the proposed systems will provide support and improve the ability to accurately and quickly analyze biomedical data and will also provide insight into how cells dynamically respond to disease” Clements said.

Over a three year period, $446,115 has been granted to this project by the National Institutes of Health. This grant will be used to design and implement methods to automatically extract meaning from multi-dimensional volumes of microscopic and magnetic resonance imaging data and provide end user access to computational resources. The modular and expandable system will be able to assist in analyzing a wide range of data.

This grant has four main goals: create and implement algorithms that can extract and analyze data from thousands of cells in large microscopy images, design processing methods for better less error-prone understanding of dynamic MRI scans, evaluate these new methods on an animal model of disease, and integrate these activities in the classroom.

“Once completed, this system will be able to analyze more than just medical data,” Clements said. “It will have the capacity to read and evaluate data that span multiple different disciplines such as medicine, biology, psychology, materials science and beyond”

What once took several days and substantial staff power to go through will now be analyzed more accurately and efficiently.

The completion of this project will also provide opportunities for �鶹��Ƶ students to gain expertise in systems progression and utilization.

New courses will become available to �鶹��Ƶ students. These courses will train students to design, use and apply programming methods for analyzing a range of data types to be implemented within the framework.

The courses will allow students to work in teams using processing workflows to extract large amounts of data from biomedical research studies and will give students the opportunity to design and assist in the development of new data processing and other tasks.

“We will be able to share the education with the integration of the multidisciplinary research activities in diverse labs,” said Clements. “This work can lay the foundation for a diverse range of data analysis.”

Learn more about Department of Biological Sciences.