AVIEW Chest used for lung cancer diagnosis at Hwasun Chonnam National University

AI-Powered Lung Diagnosis in Action

Coreline Soft was selected for the 2024 AI Voucher Support Program, hosted by the National IT Industry Promotion Agency (NIPA), in partnership with Hwasun Chonnam National University Hospital (CNUH). The project, titled "Enhancing Efficiency and Validating Performance of AI-Based Lung Cancer Diagnosis," showcases how AVIEW Chest, Coreline’s advanced chest CT analysis software, is being utilized in real clinical environments.

What is AVIEW Chest?

AVIEW Chest is an AI-powered diagnostic support solution designed for radiologists to read chest CTs with greater speed and precision. Unlike LCS Plus, which is optimized for lung cancer screening programs, AVIEW Chest focuses on enabling comprehensive analysis across multiple chest diseases—such as lung cancer, COPD, and CAC—in a single workflow.

It streamlines the reading process by auto-generating structured reports and visually highlighting key findings. Recently, AVIEW Chest has also added automatic aortic diameter measurement—a critical metric in identifying life-threatening conditions such as aneurysms and dissections.

Clinical Application at Hwasun CNUH

Hwasun CNUH is a leading cancer hospital in Korea’s Honam region, with a multidisciplinary team specializing in lung cancer treatment. Since May 2024, all chest CT scans performed at the hospital have been analyzed by AVIEW Chest. Radiologists then finalize their interpretations based on the AI-generated findings.

In situations where radiologists are unavailable or delayed, the AI outputs are used by the multidisciplinary team to support timely clinical decisions. Professor Wonki Jung (Department of Radiology), the project’s principal investigator, aims to validate whether AI-assisted diagnostics can positively impact the entire treatment workflow—not just image interpretation.

Automated Aortic Diameter Measurement and Its Impact

AVIEW Chest’s aortic segmentation feature enables automated diameter calculation. Professor Jung is currently conducting research comparing the AI measurements with previous manually measured values. The study also examines the relationship between aortic dilation and cardiovascular disease based on patient history and past scans.

These findings are expected to be presented at future academic conferences and will serve as strong evidence of the clinical utility and accuracy of AI-driven measurements.

Enhancing Efficiency Across the Care Continuum

Coreline Soft is committed to continuously enhancing AVIEW Chest to achieve its core mission: identifying all major thoracic conditions from a single CT scan while reducing radiologists’ fatigue and increasing diagnostic speed and accuracy.

This project demonstrates how AI can evolve beyond support tools and become a central element in efficient hospital workflows, ultimately reducing overall treatment time.