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This technology includes a novel computational algorithm and software implementation to map and display biological pathways and their relationship on the surface of a globe in a three-dimensional space. Currently, biological pathways and genes are represented as two-dimensional networks, which is not effective for displaying complicated relationships between pathways and genes.

This technology relates to a software package called NIMH DAO Toolbox that uses multithreading and a unique buffer structure to shorten gaps in sample readouts. Data acquisition devices running in continuous sampling mode collect data samples at a given sampling rate. The samples are typically stored in a memory buffer and read out at a regular interval. If the sampling rate is short enough, there can be a gap between the time the first sample is acquired and the time that sample is available to the user. This gap is typically on the order of tens of milliseconds.

This technology relates to a closed-loop controller that is being developed as a phone app for emotional self-regulation in real-time. There is a significant association between emotion dysregulation and symptoms of depression, anxiety, eating pathology, and substance abuse, affecting millions worldwide. Consisting of a closed-loop controller that adjusts reward values in real-time according to individual mood response, the Mood Machine Interface technology compensates for adaptation to stimuli over time allowing it to generate substantial mood changes in the user.

This invention relates to methods and algorithms that incorporate information from multiple imaging modalities to identify, estimate the size, and track the time course of brain lesions. Subjects develop brain lesions over the natural course of a disease. Currently, lesions are measured and tracked by a trained neuroradiologist using slice-by-slice inspection, a slow process that is prone to human error and hard to generalize to large observational studies.

This technology includes an automated and non-invasive assessment system called Automated Identification of subjects at risks of Multiple Sclerosis (AIMS) to assist clinicians in their diagnostic evaluation. A focus of AIMS is the ‘central vein sign’ (and other radiological findings).

This technology includes a versatile intravascular 3D intracardiac echocardiography (ICE) catheter that can operate under conventional X-ray and MRI for use during interventional cardiac procedures. The 3D MRICE and custom, GPU-based, real-time imaging system are also included. Structural heart disease affects more than 2.9% of the US population, and common interventional procedures can be difficult because of limitations in catheter devices and inadequate image guidance.

This technology includes a new technique to improve the fidelity of time-varying signals acquired in the dynamic contrast enhanced (DCE) imaging. This technique enhances the time-varying signals in a given DCE image series through deep convolutional neural networks (CNN) to learn the relationship of signal versus contrast concentration from other series of different contrast doses.

This CDC developed auscultatory training apparatus includes a database of prerecorded physiological sounds (e.g., lung, bowel, or heart sounds) stored on a computer for playback. Current teaching tools, which utilize previously recorded sounds, suffer from the disadvantage that playback environments cause considerable distortion and errors in sound reproduction. For example, to those trainees using such systems, the reproduced respiratory sounds do not “sound” as if they are being generated by a live patient.

This invention pertains to a CDC developed sonic aerosol generator that provides a controllable, stable concentration of particulate aerosol over a long period of time for aerosol exposure studies. Specifically, in situ testing data indicate uniform aerosol stability can be maintainable for greater than 30 hours at concentrations of 15 mg/m³ or more. Additionally, the technology was specifically developed for, and validated in, animal studies assessing exposure to airborne multi-walled carbon nanotubes (MWCNT).