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Coreline Soft Co., Ltd. Selected for Government-Funded Project on AI-Powered Diagnostic Assistance Software for Lung Diseases

[Edaily Reporter Park Sun-Yeop ] Coreline Soft Co., Ltd.(384470)announced on the 23rd that it has been selected as the lead research and development institution for a new project to be funded under the first round of the 2026 Inter-Ministerial Advanced Medical Device R&D Program, organized by the Inter-Ministerial Medical Device R&D Project Group, and has signed a cooperation agreement.
The project is titled “Clinical Trials to Verify the Safety and Efficacy of Two Types of CT-Based AI Diagnostic Assistance Software Medical Devices for Lung Diseases and Obtaining U.S. FDA Approval.”
The R&D period is 33 months, from April 1, 2026, to December 31, 2028. The total R&D budget is 2.94 billion won, of which 2.2 billion won is government funding. The company’s contribution is 740 million won, consisting of 666 million won in-kind and 74 million won in cash. The government grant amounts to 12.11% of Coreline Soft Co., Ltd.’s equity capital of 18,172,080,000 won.
The objective of this project is to conduct local clinical trials in the U.S. for the medical image analysis software “AVIEW Lung Nodule CAD (AVIEW IPN)” and “AVIEW Lung Metrics,” both developed by Coreline Soft Co., Ltd., and to obtain 510(k) clearance from the U.S. Food and Drug Administration (FDA). The publication of one paper in an international academic journal is also included in the final objectives.
AVIEW Lung Nodule CAD is an artificial intelligence (AI) software for the automatic detection of lung nodules based on CCTA and chest CT images. Coreline Soft Co., Ltd. plans to pursue FDA 510(k) clearance by conducting independent performance validation and confirmatory reader studies involving multiple readers and multiple cases at multiple U.S. institutions.
AVIEW Lung Metrics is a general-purpose lung quantitative analysis software based on chest CT. Through joint research with a U.S. research team, the company aims to validate the accuracy of automated analysis of CT-based lung quantitative biomarkers and pursue FDA 510(k) clearance and publication in an academic journal.

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