University of Southern California

The General Hospital Corporation

The Brigham and Women's Hospital, Inc.

Ge Precision Healthcare LLC

Fujifilm Sonosite, Inc.

Mass General Brigham

Mass General Brigham Incorporated(b)

Quanzheng Li

Richard M Leahy

Wentao Zhu

Thomas M Duffy

Peter Conti

Davinder S Dhatt

Paul Tomotaro Danset

Adam Benjamin Pely

Diku Pranav Mandavia

Kyungsang Kim

Rohit Pardasani

Sangtae Ahn

Sanghee Cho

Bing Bai

Christopher Alexksandr White

Andrew Liteplo

Suzannah Mckinney

Dirk Johannes Varelmann

Pankaj Sarin

Marcio Aloisio Bezerra Cavalcanti Rockenbach

Fabiola Macruz

Hariharan Ravishankar

Systems and techniques for monitoring, predicting and/or alerting for short-term oxygen support needs of patients are presented. A system can include a data collection component that receives multimodal patient data for a patient having a respiratory condition in association with monitoring and treating the respiratory condition in real-time, the multimodal patient data comprising at least physiological data regarding physiological parameters tracked for the patient over a period of time, and current oxygen support data regarding a current oxygen support mechanism of the patient. The system can further include an oxygen support forecasting component that processes the multimodal patient data using an oxygen support forecasting model to generate an output forecast that indicates whether a change to the current oxygen support mechanism is recommended for the patient within a defined upcoming timeframe.

Monitoring, predicting and alerting short-term oxygen support needs for patients

Methods and apparatuses for performing automated detection of lung slide using a computing device (e.g., an ultrasound system, etc.) are disclosed. In some embodiments, the techniques determine lung sliding using one or more neural networks. In some embodiments, the neural networks are part of a process that determines probabilities of the lung sliding at one or more M-lines. In some embodiments, the techniques display one or more probabilities of lung sliding in a B-mode ultrasound image.

Automated detection of lung slide to aid in diagnosis of pneumothorax

A medical imaging system for reconstructing quantitative dynamic nuclear medicine images of a subject may include a three dimensional positron emission tomography (3D PET) scanner and a data processing system. The three dimensional positron emission tomography (3D PET) scanner may: perform scans of the subject at each of multiple bed positions, each scan being of only a sub-portion of the subject that is within an axial length covered by the scanner; and generate dynamic list-mode PET data that: represents a total number of photon pairs arriving at each of multiple detector pairs in the 3D PET scanner; and is organized in a list of elements, each element in the list including a detector pair index and an arrival time for each detected photon pair; and acquires PET data using a dynamic PET protocol with at least two scans at each of the multiple bed positions. The data processing system may: reconstruct Patlak slope and intercept images of the subject over an axial length of the subject that exceeds the axial length of each scan of the subject by optimizing a likelihood or penalized likelihood function using the list-mode PET data from at least two scans of the subject at each of the multiple bed positions; and store the reconstructed image in a storage device or displays the reconstructed image on a display system.

Direct patlak estimation from list-mode PET data

A technique for processing of data from time-of-flight (TOF) PET scanners. The size of TOF PET data may be reduced without significant loss of information through a process called rebinning. The rebinning may use the Fourier transform properties of the measured PET data, taken with respect to the time-of-flight variable, to perform data reduction. Through this rebinning process, TOF PET data may be converted to any of the following reduced representations: 2D TOF PET data, 3D non-TOF PET data, and 2D non-TOF PET data. Mappings may be exact or approximate. Approximate mappings may not require a Fourier transform in the axial direction which may have advantages when used with PET scanners of limited axial extent. Once TOF PET data is reduced in size using this rebinning, PET images may be reconstructed with hardware and/or software that is substantially less complex and that may run substantially faster in comparison to reconstruction from the original non-rebinned data.

Exact and approximate rebinning of time-of-flight PET positron emission tomography data

Growing community of inventors

Belmont, MA, United States of America

Quanzheng Li