MEDICAL IP participated in <RSNA 2022>, which was held in Chicago from November 27 to December 1.
At this RSNA, MEDICAL IP introduced innovative technologies that will lead the evolution of radiology, such as ▲medical image-based digital twin implementation solution and 3D quantitative analysis solution for medical images.
Based on the medical AI technology that quickly and accurately divides and analyzes organs and lesions in medical images through artificial intelligence, the company digitizes anatomical structures and utilizes them in a three-dimensional virtual space. A variety of product lineups were presented at the exhibition.
A company official said, "The company's technology, which implements human body components as digital twins and extends them to virtual/augmented reality and metaverse, is a source that enables medical images to be used in medical education, surgery, prevention and prediction." We are introducing our unique technology that provides not only visual information but also quantified quantitative information of AI-based medical images to those in the field of radiology at both home and abroad.”
'Lung Volumetry' technology, which measures lung volume information from X-ray data, drew attention from radiology department medical staff who participated in RSNA. A paper using TisepX was published in the journal 'Radiology', and an abstract presentation was conducted regarding the result of the publication, and Professor Hyungjin Kim of the Department of Radiology at Seoul National University Hospital gave an presentation on <Prediction of Total Lung Capacity Using Chest Radiographs: Validation of Technical Performance and Clinical Utility>
Developed through MEDICAL IP's proprietary technology and algorithm, TiSepX is an innovative technology that derives 3D visualization and quantitative analysis results through dimensional conversion learning of 2D X-ray images. It received positive reviews.
In addition to this, academic presentations by medical staff on MEDICAL IP's medical AI analysis and digital twin implementation technology will continue during the conference. Researcher Jo Sang-wook of Yonsei University Severance Hospital in Professor Hong Nam-ki's team presented the results of research on predicting osteoporosis, sarcopenia, and metabolic syndrome using 'DeepCatch', an AI automatic analysis solution for body composition, and Professor Do Yoon-sik of Chungbuk National University Medical School will present real-time medical augmented reality (AR) technology for surgical navigation based on medical images, which was approved by the Ministry of Food and Drug Safety for the first time in Korea.
As such, leading medical staff in the field of radiology have demonstrated clinical usefulness by announcing clinical research results using Medical IP products, and based on this, collaboration discussions with global companies are expected to start in earnest.
MEDICAL IP CMO (Chief Medical Officer), Seoul National University Hospital, Department of Radiology Professor Soon ho Yoon introduced the latest MEDIP PRO developed in collaboration as NVIDIA's premier partner on theheme of 'MEDIP-enabled medical image digital twinning in NVIDIA Omniverse' at AI Theater.
In addition to this, a business meeting was held in Chicago with a global medical device company related to the installation of TiSepX on X-ray device in line with the conference period, and discussions with AWS on the establishment of a real-time digital twin implementation platform in a cloud environment. Business discussions were actively conducted.
Regarding this, CEO Park Sang-joon said, “With the global healthcare market continuing to grow, the introduction of cutting-edge technologies such as AI, digital twin, and metaverse will inevitably continue in areas based on medical data such as radiology.” Through this, we were able to confirm that Medical IP's technologies, such as digital twin and 3D quantitative analysis technology through AI in the medical field, have a competitive edge in the global market, and we will expand our performance overseas.