TS-062628 — More than a billion people worldwide suffer from some neurological disorders, such as Alzheimer's, Parkinson's, multiple sclerosis, epilepsy, stroke, autism, addiction, and many others. These conditions result in more than 7 million deaths, with associated costs exceeding $1.5 trillion annua…

TS-062343 — The Need: In the face of mass casualty incidents, first responders play a critical role in saving lives and minimizing the impact of disasters. However, traditional training methods using mock patients or mannequin simulators for mass casualty triage are costly, challenging to replicate, and requir…

TS-062335 — The Need: In the field of ophthalmology and vision care, there is a critical need for accurate and comprehensive measurements of visual function over the entire visual field. Conditions such as glaucoma, age-related macular degeneration (AMD), diabetes, stroke, pituitary disease, brain tumors, and n…

TS-062310 — The Need Medical imaging plays a crucial role in diagnosing various diseases and conditions. Magnetic Resonance Imaging (MRI) has emerged as one of the most significant and preferred medical imaging modalities due to its non-invasive nature and low risk of side effects compared to other imaging met…

TS-062309 — The Need: Signal intensity inhomogeneity in Magnetic Resonance (MR) imaging presents a significant challenge, leading to degradation in image quality, obstructed diagnoses, reduced accuracy in quantitative analyses, and increased inter-scanner variability. The lack of effective inhomogeneity correct…

TS-062307 — The Need: Accurate characterization of receiver sensitivity is crucial for magnetic resonance imaging (MRI) techniques, particularly fast MRI using multi-channel coils. Different coils sample various parts of the k-space simultaneously during parallel MRI, and the final image's accuracy depends …

TS-042266 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.

TS-039164 — A new tool that can quantify the sensory maps of the human brain. The tool can be used to quantify plasticity and pathology in the sensory areas of the human brain that are associated with normal and abnormal development, aging, and diseases in sensory systems. The first application of the tool, on retinotopic maps of the visual cortex, has generated excellent results.

TS-038074 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.

TS-036544 — An algorithm that processes aerial images to provide farmers with data on crop emergence needed for improving crop management decisions.

TS-014871 — Encoding strategy for improvement of speech understanding in a noisy environment for audiotory prosthetic devices.