Seoul National University Hospital, initiating AI image analysis KIMA logo Seoul National University Hospital initiates independently developed artificial intelligence image analysis starting from January 2019. AI will analyze chest x-ray images and detects abnormalities related to lung cancer or metastasis lung cancer. It will help a doctor diagnose early-stage lung cancer which could be unnoticed. This AI-based image analysis assistant system called ‘Lunit INSIGHT for Chest Radiography Nodule Detection’was co-developed by software company Lunit and Professor Changmin Park of Seoul National University Hospital Radiology Department. Seoul National University Hospital said ‘Lunit INSIGHT’will be linked to PACS for actual clinical image analysisto detect abnormalities in chest x-rays to assist doctors in the diagnosis of lung cancer and metastasis. It will also use independently developed deep learning technologies and high-quality image data to detect tiny or hidden lung cancer nodules that could be overlooked. +82-43-713-8999, 8998, 8997 kimakorea@khidi.or.kr

Seoul National University Hospital, initiating AI image analysis

KIMA NEWS

Seoul National University Hospital, initiating AI image analysis

March 4,2019

Seoul National University Hospital initiates independently developed artificial intelligence image analysis starting from January 2019. AI will analyze chest x-ray images and detects abnormalities related to lung cancer or metastasis lung cancer. It will help a doctor diagnose early-stage lung cancer which could be unnoticed. This AI-based image analysis assistant system called Lunit INSIGHT for Chest Radiography Nodule Detectionwas co-developed by software company Lunit and Professor Changmin Park of Seoul National University Hospital Radiology Department. Seoul National University Hospital said Lunit INSIGHTwill be linked to PACS for actual clinical image analysisto detect abnormalities in chest x-rays to assist doctors in the diagnosis of lung cancer and metastasis. It will also use independently developed deep learning technologies and high-quality image data to detect tiny or hidden lung cancer nodules that could be overlooked.

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