Qt Ultrasound LLC

The Texas A&M University System

Qt Imaging, Inc.

Mark Wayne Lenox

Bilal Malik

Nasser Pirshafiey

James W Wiskin

John C Klock

Nasser Charles Pirshafiey

Martin Cwikla

Sandeep Tiwari

A catheter delivery device includes a hollow longitudinal body, a fluidic bypass, and a hemostasis valve. The hollow longitudinal body includes a clamping portion and a guide catheter. The guide catheter has a distal end for access into a vessel of a patient and a proximal end coupled to the clamping portion. The clamping portion has a distal end coupled to the guide catheter, a proximal end coupled to the hemostasis valve, and a guidewire securing section. When the guidewire securing section of the clamping portion is securing the guidewire, the fluidic bypass maintains fluid communication between the guide catheter and the hemostasis valve. In some cases, the guidewire securing section and the fluidic bypass are separated by material within the hollow longitudinal body. In some cases, the fluidic bypass is separate from the guidewire securing section outside of the hollow longitudinal body.

Catheter delivery guidewire clamp

A method for machine learning based ultrasound image reconstruction can include receiving, at a reconstruction engine, imaging data; generating an initial estimate for a transmission image via a neural network trained (machine or self-learning) on paired transmission ultrasound and reflection ultrasound data; and performing image reconstruction using the initial estimate to generate transmission ultrasound images. The image reconstruction can generate higher quality transmission ultrasound when carried out by using the initial estimate as the starting point for iterative image reconstruction and using transmission data obtained via conventional transmission ultrasound frequencies (e.g. from 0.8 MHz to 1.5 MHz).

Application of machine learning to iterative and multimodality image reconstruction

An automated system for selecting patient breast laterality is provided. A position sensor system using force or image sensors is coupled to a scanning bed or seated-type apparatus. Regardless of the size and weight of the patient, the position of patient at the time of scan will not be centered with respect to the center of the scanner. This relative difference in the position will be sensed as a difference in the transducer signal of an image sensor when comparing the right- and left-hand sides of the field of view or will be sensed as a difference in voltage when comparing the right and left-hand side outputs of a circuit using force or pressure sensor.

Automatic laterality identification for ultrasound tomography systems

The speed of sound, attenuation, and reflection data obtained through quantitative Transmission ultrasound (QTUS) differs by body tissue type. Skin, fat, gland, duct and connective tissues can be classified based on the sound, attenuation, and reflection data. The system can assign coloration to breast images to provide a color-coded breast tissue volume based on the output of the classifier.

Color coding an image for identifying anatomy using quantitative transmission ultrasound tomography

Treatment for a variety of diseases often requires guidance for the delivery of either a drug or radiation to the disease site. Positron Emission Tomography (PET) can provide three dimensional positioning of the location of positron emitting radioisotopes that can mark a disease site. However, the inversion of the raw emission projection data into a 3D volume is computationally intensive, and this results in a low update or frame rate. In order to be useful in either guiding a surgeon, or some other automated feedback approach, the update/frame rate must be of sufficient speed that the user can effectively control the process. This approach provides a substantial improvement to the frame rate by taking advantage of iterative reconstruction methodologies to shortcut the reconstruction process.

Growing community of inventors

College Station, TX, United States of America

Mark Wayne Lenox