News Archives - Lab of Medical Imaging and Computation

Detecting ischemic stroke mimic using deep learning-based analysis of medical images

Inventors: Synho Do, Byung Chul Yoon, Ramon Gilberto Gonzalez, Michael H Lev, Stuart Robert Pomerantz Publication date: 2023/10/26 Patent office: US Application number: 18305627 Description: An ischemic stroke mimic is detected or otherwise predicted based on medical images acquired from a subject. Medical image data, which include medical images acquired from the head of the…

System and method for analyzing medical images to detect and classify a medical condition using machine learning and a case-pertinent radiology atlas

Inventors: Hyunkwang Lee, Sehyo Yune, Synho Do Publication date: 2024/4/30 Patent office: US Patent number: 11972567 Application number: 17055068 DescriptionA system for analyzing medical images to detect and classify a medical condition, the system includes an input for receiving a medical image, a convolutional neural network coupled to the input and configured to analyze the…

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease

Authors: Adham M Alkhadrawi, Lisa Y Lin, Saul A Langarica, Kyungsu Kim, Sierra K Ha, Nahyoung G Lee, Synho Do Publication date: 2024/5/1 Journal: Investigative Ophthalmology & Visual Science Volume: 65 Issue: 5 Pages: 6-6 Publisher: The Association for Research in Vision and Ophthalmology Description: Purpose: Thyroid eye disease (TED) is characterized by proliferation…

Artificial Intelligence for Breast Cancer Screening: Trade-offs between Sensitivity and Specificity

Authors: Manisha Bahl, Synho Do Publication date: 2024/5/8 Journal: Radiology: Artificial Intelligence Volume: 6 Issue: 3 Pages: e240184 Publisher: Radiological Society of North America Description: Manisha Bahl, MD, MPH, FSBI, is a radiologist at the Massachusetts General Hospital, an associate professor at Harvard Medical School, and a fellow of the Society of Breast Imaging. Her…

Deep-Learning Based Automated Segmentation and Quantitative Volumetric Analysis of Orbital Muscle and Fat for Diagnosis of Thyroid Eye Disease and Associated Optic Neuropathy

Authors: Lisa Lin, Adham Alkhadrawi, Saul Langarica, Kyungsub Kim, Sierra Ha, Nahyoung Grace Lee, Synho Do Publication date: 2024/6/17 Journal: Investigative Ophthalmology & Visual Science Volume: 65 Issue: 7 Pages:1595-1595 Publisher: The Association for Research in Vision and Ophthalmology Abstract Purpose : Thyroid eye disease (TED) is characterized by proliferation of orbital tissues and…

[US patent, #18559016] Collaborative artificial intelligence annotation platform leveraging blockchain for medical imaging

Inventors: Synho Do Publication date: 2024/7/11 Patent office: US Application number: 18559016 Description: A system and method are provided for providing a collaborative annotation platform. The method includes enabling access to a collaborative annotation project associated with at least one medical image. The method also includes receiving crowd-sourced annotations associated with at least one medical…

Kyungsu Kim’s Farewell Lunch

Kyungsu Kim PhD appointed as Assistant Professor at Seoul National University We are proud to announce that Kyungsu Kim PhD has been appointed as Assistant Professor at Seoul National University.

2023 Summer Intern Research

For the LMIC 2023 summer research internship, “Justin Hwang” has provided a summary of his research, final report, and corresponding GitHub repository. https://github.com/justinhwang24/lung-abnormality-detection Summary: Machine learning aids in diagnosing lung abnormalities from medical images. This study used convolutional neural networks (CNNs) to detect these abnormalities in 1,740 chest radiographs, achieving 93.10% accuracy. Such…

Accurate auto-labeling of chest X-ray images based on quantitative similarity to an explainable AI model

Doyun Kim, Joowon Chung, Jongmun Choi, Marc D. Succi, John Conklin, Maria Gabriela Figueiro Longo, Jeanne B. Ackman, Brent P. Little, Milena Petranovic, Mannudeep K. Kalra, Michael H. Lev & Synho Do

Prediction of oxygen requirement in patients with COVID-19 using a pre-trained chest radiograph xAI model: efficient development of auditable risk prediction models via a fine-tuning approach

Joowon Chung, Doyun Kim, Jongmun Choi, Sehyo Yune, Kyoung Doo Song, Seonkyoung Kim, Michelle Chua, Marc D. Succi, John Conklin, Maria G. Figueiro Longo, Jeanne B. Ackman, Milena Petranovic, Michael H. Lev & Synho Do