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Progressive and Multipath Neural Network for Medical Image Segmentation

Researchers at the National Institutes of Health Clinical Center (NIHCC) developed a technology that improves segmentation detail levels for anatomical structures in medical images through a new, deep learning approach. Difficult anatomical features, often segmented incorrectly with other image segmentation methods, are correctly segmented and identified using this novel technology, which is available for licensing or co-development.

Denoising of Dynamic Magnetic Resonance Spectroscopic Imaging Using Low Rank Approximations in the Kinetic Domain

Scientists at The National Cancer Institute (NCI) and The National Institute of Neurological Disorders and Stroke (NINDS) have invented a method of imaging glucose metabolism in vivo using MRI chemical shift imaging (CSI) experiments that relies on a simple, but robust and efficient, post-processing procedure by the higher dimensional analog of singular value decomposition, tensor decomposition. This new technology is denoising software for MRIs that significantly improves the measurement of low-intensity signals without the need for dynamic nuclear polarization (DNP). The scientists seek research co-development partners and/or licensees for their invention.

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