Software Summaries
Hunstad, David ; Kenney, Kenneth ; Komeshak, Rachel ; Lackey, Ian ; Rich, Eliot
T-017287
— Background: Faculty members from institutions all over the world are publishing scientific articles, presenting data to conferences, and writing proposals for government-funded grants all simultaneously at one time. Of course, the outcomes happen to be known at different times for each specific task…
Software to predict low back pain from brain imagingHawasli, Ammar ; Jayasekera, Dinal ; Lamichhane, Bidhan ; Leuthardt, Eric ; Ray, Wilson
T-019322
— Technology Description: Researchers at Washington University, led by Eric Leuthardt, have developed software that can identify specific brain regions involved in chronic low back pain from neuroimaging data. This software, powered by machine learning, relies on differences in cortical thickness an…
Efficient multi-dimensional 4D MRI and PET/MR motion correctionAn, Hongyu ; Eldeniz, Cihat
T-016414
— Technology Description Researchers in Prof. Hongyu An’s laboratory have developed a new image processing system for faster acquisition of motion-corrected MR or PET/MR images. This technology could be expanded to multiple sampling schema to correct both respiratory and cardiac motion. Liv…
Computer vision training system for robust artificial intelligence image classificationTong, Liang ; Vorobeychik, Yevgeniy ; Wu, Tong
T-019303
— Technology Description Researchers in Prof. Yevgeniy Vorobeychik’s laboratory have developed a new adversarial model and training methods to defend deep neural networks against physical attacks that corrupt image classifications. This system outperforms previous state-of-the-art techniques a…
Pressure recovery ratio (PRR) index for real-time assessment of heart failureChung, Charles ; Kovacs, Sandor ; Shmuylovich, Leonid ; Zhang, Weixiong
T-007562
— Technology Description Researchers in the Cardiovascular Biophysics Laboratory at Washington University developed a patented, real-time, automated index to reliably detect delayed relaxation during cardiac catheterization diagnostics. This technique, called pressure recovery ratio (PRR), serves as…
Machine learning methods for real-time MRI image processing: MRI-only radiation treatment planning and improving MR image resolutionGreen, Olga ; Mutic, Sasa ; Park, Chunjoo (Justin) ; Zhang, Hao
T-018522
— Technology Description A team of researchers at Washington University School of Medicine developed deep learning image processing techniques to improve MRI diagnostics and potentially enable faster, more precise MRI-guided radiation therapy without exposing patients to radiation from CT imaging. S…
Real-time air and water quality monitoring with AI-based data analysis and low cost sensorsBiswas, Pratim ; Li, Jiayu
T-018523
— Technology Description Prof. Pratim Biswas and colleagues have developed an artificial intelligence platform to provide accurate, low-cost analysis of air and water quality by integrating data gathered from particulate matter (PM) sensors and other sources. This technology could be used to make th…
Machine learning method for fast, reliable quality assurance of patient imaging in radiation therapy or computer-aided detectionAltman, Michael ; Green, Olga ; Kavanaugh, James ; Li, Hua ; Mutic, Sasa ; Wooten, Hasani
T-013577
— Technology Description A team of researchers at Washington University has created a machine learning method to quickly and reliably validate patient contours in digital medical images for radiation therapy and computer aided image analysis. Currently, automated contouring tools for delineating tu…
Blockchain-based algorithms for secure, collaborative risk assessment and decision makingJain, Raj ; Salman, Tara
T-018710
— Technology Description Researchers in Prof. Raj Jain’s laboratory have developed a new type of algorithm that extends the security of decentralized blockchains from consensus validation to efficient group decision making. This technology, called “probabilistic blockchains”, provi…
Self-powered, solid-state devices for remote sensing, timing and security of internet-of-things and other passive assetsChakrabartty, Shantanu ; Zhou, Liang
T-015908
— Technology Description Engineers in Prof. Shantanu Chakrabartty’s laboratory have developed a self-powered, CMOS-based, nano-scale “smart sensor” and timer system that uses quantum-tunneling for reliable, long-lasting memory or authentication. This technology is a floating gate …
Multiparametric Cardiac Strain Analysis of Myocardial ViabilityCupps, Brian ; Kar, Julia ; Pasque, Michael
T-014564
— Background: Assessing left ventricle (LV) cardiac contractile function is a good indicator of overall heart health and is used to determine which patients are good candidates for revascularization surgery. With over 3 million new coronary artery disease patients annually and over 1 million annual re…
Method To Remove Brain Stimulation Artifacts in Neural SignalsBrunner, Peter ; Leuthardt, Eric ; Willie, Jon ; Xie, Tao
T-020083
— Value proposition: Method and system for removing multiple types of brain stimulation artifacts in neural signals to improve neurological diagnoses and therapies. Technology Description Researchers at Washington University in St. Louis have developed a method to remove brain stimulation artifact…
Myocardial perfusion SPECT optimizationJha, Abhinav Kumar ; Rahman, Md Ashequr ; Siegel, Barry ; Yu, Zitong
T-020357
— T-020357, T-020358, T-020744 Myocardial perfusion SPECT optimization Technology Description Researchers from the laboratory of Abhinav Jha at Washington University have devised methods to reliably improve and personalize myocardial perfusion SPECT imaging. The inventions include the following capa…
Real-time interference compensation in MRI guided radiotherapyCurcuru, Austen ; Gach, H. Michael ; Kim, Taeho ; Villa, Umberto
T-019745
— Technology Description Researchers at Washington University in St. Louis have developed a method to improve image quality during MR imaging guided radiation therapy (MR-IGRT) by correcting for B0 fluctuation in real-time. The corrections reduce electromagnetic interference (EMI) between the MRI sc…
Improved MRI resolution with Diffusion Dictionary Imaging (DDI)Wang, Qing ; Wang, Yong
T-019608
— Technology Description Researchers at Washington University in St. Louis have developed MRI post-processing software capable of imaging cellular components. The software matches specific patterns with a dictionary of signals corresponding to cellular components. While the researchers have previous…
Machine learning paired with photoacoustic microscopy and ultrasound for improved rectal cancer imagingChapman Jr., William "Will Jr" ; Leng, Xiandong ; Mutch, Matthew ; Uddin, Shihab ; Zhu, Quing
T-019449
— Technology Description: Researchers led by Quing Zhu at Washington University have developed a method for imaging rectal tumors using photoacoustic microscopy and ultrasound with a machine learning component. This method is better able to differentiate residual cancer from healthy tissue following…
MRI-based virtual histopathology for non-invasive diagnosis of prostate cancer, glioblastoma and other conditionsSong, Sheng-Kwei "Victor" ; Ye, Zezhong
T-016528
— Researchers in Prof. Sheng-Kwei (Victor) Song’s laboratory have developed diffusion histology imaging (“DHI”), a tool to provide a non-invasive diagnosis for accurately grading tumors and guiding treatment decisions. This “virtual histopathology” technology classifies mic…
Automated image processing tools for quantitative SPECT and PET scansJha, Abhinav Kumar ; Liu, Ziping ; Moon, Hae Sol ; Rahman, Md Ashequr ; Yu, Zitong
T-019331
— Engineers in Washington University’s Computational Medical Imaging Lab have developed automated, machine-learning techniques to improve nuclear medicine imaging (SPECT and PET). These tools include estimation-based segmentation methods to define boundaries and ASC (attenuation and scatter comp…
Methods to accurately measure diastolic function from echocardiogramChung, Charles ; Kovacs, Sandor ; Shmuylovich, Leonid
T-005426
— Technology Description Researchers in Prof. Sandor Kovacs’ laboratory developed a patented, non-invasive, load-independent method to measure the intrinsic diastolic performance of the heart. This load-independent index of filling (LIIF) can be incorporated into the software of echocardiogram…
Method to characterize gut microbiomeGordon, Jeffrey ; Raman, Arjun
T-018977
— Technology Description Researchers at Washington University in St. Louis have developed a method to stratify gut microbiota dysbiosis and monitor treatments to correct it. In order to efficiently treat microbiota imbalance, it would first be beneficial to understand the healthy organization and in…
Ultrasound-guided diffuse optical tomography for fast, low-cost functional imaging of breast lesionsMostafa, Atahar ; Zhu, Quing
T-018800
— Technology Description Prof. Quing Zhu and colleagues have pioneered a compact, low-cost ultrasound-guided optical tomography system designed to differentiate between benign and malignant breast lesions and reduce the need for costly and invasive biopsies. This technology enables fast, robust imag…
Automated, Improved Deformable Image Registration for Radiation Therapy and other Clinical ApplicationsYang, Deshan
T-017324
— Technology Description Prof. Deshan Yang and colleagues have developed automated systems and software toolkits to provide more accurate deformable image registration (DIR) for adaptive radiotherapy and other clinical applications. In particular, they have automated tedious and labor-intensive DIR …
User-friendly methods to detect artifacts in super-resolution microscopyLew, Matthew ; Mazidisharfabadi, Hesamaldin ; Nehorai, Arye
T-019008
— Engineers at Washington University have devised an automated system to enhance super-resolution microscopy images by detecting and quantifying image artifacts using no a priori information. This project stems from the advanced imaging research in Prof. Matthew Lew’s laboratory that includes op…
EMMI- non-invasive imaging method for safe, accurate, robust monitoring of uterine contractionsCahill, Alison ; Cuculich, Phillip ; Schwartz, Alan ; Wang, Yong
T-015805
— Technology Description Researchers at Washington University in St. Louis have developed an electromyometrial imaging (EMMI) method to non-invasively monitor uterine contractions. During pregnancy, many women experience preterm contractions. Sometimes these contractions progress to pre-term labor a…
Deep learning algorithm to expedite MRI-guided adaptive radiotherapy planningFu, Yabo ; Yang, Deshan
T-018708
— Technology Description Researchers in Prof. Deshan Yang’s laboratory have developed a deep-learning method for fast, robust, automated MRI segmentation to expedite treatment planning for patients undergoing MRI-guided adaptive radiotherapy (MR-IGART). Specifically, this technology utilizes a…
Accurate, efficient 2D strain mapping with robust detection of strain localizationBoyle, John ; Genin, Guy ; Pless, Robert ; Thomopoulos, Stavros
T-014090
— Summary DDE (Direct Deformation Estimation) and SIMPLE (Strain Interference with Measures of Probable Local Elevation) are two simple Digital Image Correlation algorithms that combine image analysis techniques with mechanical engineering principles to provide accurate, efficient, quantitative strai…
Deep Learning-Assisted Image Reconstruction for Tomographic ImagingAnastasio, Mark ; Kelly, Brendan ; Matthews, Thomas
T-017311
— Background Image reconstruction for any modern imaging technique is an optimization problem. Most image reconstructions methods are iterative in nature and produce sequential intermediate images that are compared to the raw acquisition data and subsequently updated to maximize the likelihood that t…
MRI neural network segmentation in atherosclerosisJha, Abhinav Kumar ; Li, Ran ; Woodard, Pamela ; Zheng, Jie
T-020254
— Technology Description Researchers at Washington University in St. Louis have developed a two-stage neural network model, with CNN and BNN architecture, to segment carotid atherosclerotic plaque components based on multi-weighted MR images and measure the uncertainty of the segmentation output. Th…
Software to predict low back pain from brain imagingHawasli, Ammar ; Jayasekera, Dinal ; Lamichhane, Bidhan ; Leuthardt, Eric ; Ray, Wilson
T-019322
— Technology Description: Researchers at Washington University, led by Eric Leuthardt, have developed software that can identify specific brain regions involved in chronic low back pain from neuroimaging data. This software, powered by machine learning, relies on differences in cortical thickness an…
Machine learning methods for real-time MRI image processing: MRI-only radiation treatment planning and improving MR image resolutionGreen, Olga ; Mutic, Sasa ; Park, Chunjoo (Justin) ; Zhang, Hao
T-018522
— Technology Description A team of researchers at Washington University School of Medicine developed deep learning image processing techniques to improve MRI diagnostics and potentially enable faster, more precise MRI-guided radiation therapy without exposing patients to radiation from CT imaging. S…
Toolkit to efficiently design exact pulse code sequences for MRI, NMR or quantum computingLi, Jr-Shin
T-017456
— Technology Description Engineers in Prof. Jr-Shin Li’s laboratory have developed a computationally efficient analytical technique to design exact RF pulse code sequences which optimize quantum applications such as MRI for medical diagnosis, NMR spectroscopy for uncovering protein structures …
Machine learning method for fast, reliable quality assurance of patient imaging in radiation therapy or computer-aided detectionAltman, Michael ; Green, Olga ; Kavanaugh, James ; Li, Hua ; Mutic, Sasa ; Wooten, Hasani
T-013577
— Technology Description A team of researchers at Washington University has created a machine learning method to quickly and reliably validate patient contours in digital medical images for radiation therapy and computer aided image analysis. Currently, automated contouring tools for delineating tu…
Myocardial perfusion SPECT optimizationJha, Abhinav Kumar ; Rahman, Md Ashequr ; Siegel, Barry ; Yu, Zitong
T-020357
— T-020357, T-020358, T-020744 Myocardial perfusion SPECT optimization Technology Description Researchers from the laboratory of Abhinav Jha at Washington University have devised methods to reliably improve and personalize myocardial perfusion SPECT imaging. The inventions include the following capa…
EMMI- non-invasive imaging method for safe, accurate, robust monitoring of uterine contractionsCahill, Alison ; Cuculich, Phillip ; Schwartz, Alan ; Wang, Yong
T-015805
— Technology Description Researchers at Washington University in St. Louis have developed an electromyometrial imaging (EMMI) method to non-invasively monitor uterine contractions. During pregnancy, many women experience preterm contractions. Sometimes these contractions progress to pre-term labor a…
ELISpot assay to immune phenotype patientsHotchkiss, Richard ; Mazer, Monty ; Remy, Kenneth ; Turnbull, Isaiah
T-019522
— Technology Description A team of researchers, led by Richard Hotchkiss at Washington University in St. Louis, have developed a version of the ELISpot assay to determine if COVID-19 patients are in a hyper-inflammatory or immunosuppressed state. The results of this assay, which can be performed wit…
IP-10 as a blood biomarker of respiratory failureMudd, Philip
T-019671
— Technology Description Researchers in Philip Mudd’s lab at Washington University have developed a blood biomarker test that detects impending respiratory failure before existing diagnostics. High levels of the biomarker IP-10 in the blood are correlated with the subsequent development of acu…
