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Method and Apparatus for enhancing sensitivity and resolution in a grating interferometer by machine learning
RPI ID:
2019-001-401 / 2019-001-601
Innovation Summary:
A machine‑learning‑enhanced reconstruction pipeline improves both contrast sensitivity and spatial resolution in grating‑based X‑ray and neutron interferometry by fusing complementary image channels through a trained convolutional neural network (CNN). Paired interferometer images—capturing...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Ge Wang, Lee Seung Wook, Seho Lee
Keywords(s): convolutional neural network, Grating interferometer, High-sensitive phase contrast image, Image processing, machine-learning
Category(s): Biotechnology and the Life Sciences
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Patient Protection and Monitoring System
RPI ID:
2019-052-401
Innovation Summary:
This system introduces a sensor module for patient monitoring that uses time-of-flight (TOF) sensors to generate elevation maps of a patient room. These maps are analyzed to determine distance and velocity vectors of room occupants, enabling classification of activities as acceptable or unacceptable. The system...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Robert, Jr. Karlicek, Richard Radke, Arunas Tuzikas, Claire Karlicek
Keywords(s): Healthcare Systems, machine-learning, Occupancy, Patient Safety, Privacy, Sensing, Time of Flight
Category(s): Computational Science and Engineering
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Multicopter online rotor fault diagnosis system
RPI ID:
2022-019-301, 2022-019-401
Innovation Summary:
This system introduces an online fault diagnosis platform for multicopter rotor systems, enabling real-time detection of rotor anomalies during flight. It utilizes sensor data and diagnostic algorithms to monitor rotor performance and identify faults without interrupting operation. The system is...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Airin Dutta, Farhan Gandhi, Fotios Kopsaftopoulos
Keywords(s): aircraft, data-based modeling, fault detection, fault diagnosis, low-cost sensors, machine-learning, multicopters, UAV, VTOL
Category(s): Computational Science and Engineering
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Student Outcomes & Predictions in Higher Education using Artificial Intelligence (SOPHEA-I )
RPI ID: 2021-021-401
Innovation Summary:
A predictive analytics system uses student data to forecast retention rates across academic programs. The model incorporates behavioral, demographic, and performance metrics to identify at-risk students. Machine learning algorithms continuously refine predictions based on new inputs. The system supports institutional...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Jasmine Yang, Lu Enzhe, Jiarun Li, Yihui Yang, Hui Su, Yifan Liu, Keith Moo-Young
Keywords(s): AI, machine-learning, Student Persistent and success
Category(s): Media, Arts, Science and Technology
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Optical Reservoir Computing for Lung Tumor Movement Prediction in Radiation Therapy Applications
RPI ID: 2020-059-201
Innovation Summary:
A recurrent neural network (RNN) architecture is developed to predict tumor movement during radiation therapy. The model uses time-series data from respiratory and anatomical signals to forecast tumor position in real time. It supports adaptive radiation delivery and minimizes exposure to surrounding healthy...
Published: 3/10/2026
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Updated: 3/10/2026
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Inventor(s): Alex Hollingsworth, Clare Thiem, Nathan McDonald, Zhizhuo Liang, Zhaoran Huang
Keywords(s): CT, machine-learning, motion prediction, radiation therapy, real-time, reservoir computing, tumor
Category(s): Biotechnology and the Life Sciences
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Dual Network Architecture for Few-view CT – Trained on ImageNet Data and Transferred for Medical Imaging
RPI ID: 2020-001-401Innovation Summary:This invention introduces a deep learning-based system for reconstructing CT images from a limited number of views. The model is trained to infer missing projection data and generate high-quality images from sparse inputs. It significantly reduces radiation exposure while maintaining diagnostic accuracy. The system...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Hongming Shan, Wenxiang Cong, Huidong Xie
Keywords(s): deep learning, Dual network architecture (DNA), few-view CT, generative adversarial network (GAN), machine-learning, sparse-view CT
Category(s): Biotechnology and the Life Sciences
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Modularized Adaptive Processing Neural Network (MAP-NN) for Low-dose CT with Radiologists-in-the-loop
RPI ID: 2019-023-201Innovation Summary:This invention introduces a modularized adaptive processing neural network architecture designed for efficient and scalable AI applications. The system dynamically adjusts its structure and processing pathways based on input complexity and task requirements. It supports real-time learning and inference, making...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Hongming Shan
Keywords(s): deep learning, denoising, machine-learning, radiologists-in-the-loop, tomography reconstruction
Category(s): Biotechnology and the Life Sciences
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A Synergized Pulsing-Imaging Network (SPIN)
RPI ID: 2018-029-401Innovation Summary:This invention introduces a synergized pulsing-imaging network (SPIN) that jointly optimizes MRI pulse sequences and image reconstruction. The system uses a deep learning framework to co-train the pulse generation and image reconstruction modules, improving image quality and acquisition efficiency. It adapts to...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Qing Lyu, Tao Xu
Keywords(s): deep learning, machine-learning, medical imaging
Category(s): Biotechnology and the Life Sciences
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Training a CNN with pseudo ground truth for CT metal artifact reduction
RPI ID: 2018-021-201 / 2018-021-601Innovation Summary:This invention introduces a method for training convolutional neural networks (CNNs) to reduce artifacts in CT images using pseudo ground truth data. The system includes an estimated ground truth generator that produces reference images from artifact-laden scans, enabling the CNN to learn artifact...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Lars Gjesteby, Hongming Shan
Keywords(s): Biomedical Engineering, machine-learning, medical imaging
Category(s): Computational Science and Engineering
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A Deep Neural Network based Corrector for Pulse Pileup Effect of Photon Counting Detectors
RPI ID: 2018-020-401 / 2018-020-601Innovation Summary:This invention introduces a neural network-based corrector for photon-counting computed tomography (PCCT) systems. Designed to address spectral distortions and detector non-linearities, the system processes raw photon data to generate corrected images with enhanced spectral fidelity and quantitative...
Published: 7/21/2025
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Updated: 7/3/2025
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Inventor(s): Ge Wang, Ruibin Feng, David Rundle
Keywords(s): deep learning, machine-learning, photon-counting Data
Category(s): Computational Science and Engineering
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