Diagnostic Assistance Solution for Big 3 Chest Disease

Automated COPD Analysis AI Solution

Lung Cancer Screening
AI Solution

aview LCS: An AI Solution for Detection and Analysis of
Lung Nodules from Chest CT.

Automated Nodule Detection and Lung-RADS Calculation

AI-powered detection and analysis of lung nodules on chest CT.

Assist clinicians in evaluating detected nodules and calculating Lung-RADS scores.

Detecting lung nodules provides information including number of nodules, size, and Lung-RADS category.

aview LCS | Automated Nodule Detection and Lung-RADS Calculation

Detecting Nodules of Various Sizes, from Small to Large

Follow up mode

Automated matching of follow-up CT scans with previous scans to assess changes in nodules.

Support monitoring of nodule growth using follow-up CT scans.

It autonomously assesses growth and changes by matching lung nodules, going beyond mere image comparisons.
aview LCS classifies lung nodules into the relevant categories according to the Lung CT Screening Reporting and Data System (Lung-RADS ver 1.1) guidelines as recommended by the American College of Radiology.

Follow-up CT Scan

Previous CT Scan

aview LCS | Automated Matching of Follow-up with Previous Lung CT Scans Instantly Assess Nodule Changes

Clinical Viewer

CT Findings are visualized in 3D.
Viewer for visualization of CT findings by medical professionals.

Advanced 3D Rendering of Patient’s Lung.

While 2D images may offer limited perspective, 3D models provide a more comprehensive spatial context.

aview LCS | CT Findings are visualized in 3D, User-Friendly Viewer for Medical Professionals and Patients

Delivering Comprehensive Analysis Results

Automatically analyze detected lung nodules and
generate comprehensive reports.

Reading report

Automatically generate lung CT screening reports for patient records and official reports.

Baseline CT
CTDIvo1: 0.32 mGy

Radiological Finding
RLL (#198), Non-Solid 32 mm, Category: 3
RLL (#200), Non-Solid 26 mm, Category: 3
LLL (|
Reports for patient records and clinical documentation

Automatically generated detailed reports summarize examination results.

Publications

Refer to the following research papers

These contents represent summaries of scientific
publications and are unrelated to any form of advertising.

To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (aview LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists’ workload could be drastically diminished by up to 86.7%.

Harriet L. Lancaster, Sunyi Zheng, et al. “Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification.” Lung Cancer
The Korean Lung Cancer Screening Project (K-LUCAS) is a single-arm cohort study that was conducted from February 2017 to evaluate the feasibility of implementing an organized national lung cancer screening program in Korea High-risk population aged 55–74 years with more than a 30-pack-year smoking history was recruited. The screening results were reported using the Lung Imaging Reporting and Data System (Lung-RADS), suggested by the American College of Radiology. K-LUCAS was performed by a network-based diagnosis supporting system using a computer-aided detection (CAD) program (aview LCS, Corelinesoft) to maintain screening quality. K-LUCAS provided promising evidence supporting the implementation of a national lung cancer screening program to detect lung cancer at an early stage and promote smoking cessation for participants in Asian population.

Lee J, Kim Y, Kim HY, et al. “Feasibility of implementing a national lung cancer screening program: Interim results from the Korean Lung Cancer Screening Project (K-LUCAS). Transl Lung Cancer Res.” 2021;10(2):723-736.

More Publications

Intended purpose

AVIEW is intended to support CT interpretation by providing information on the detection of pulmonary nodules and the analysis of coronary artery calcification, and by enabling inquiry and analysis of medical images through functions such as zoom in/out, segmentation, and quantification. It also provides capabilities to store, transfer, and display output results.

Intended user

Healthcare professionals, such as radiologists, physicians, can interpret thoracic CT with or without abnormal findings.

Warning

Please use the product for its intended purpose when in use.
Software installed on a PC can be infected by malicious software if it is connected to a network with the following conditions
1. In case of exposure to malicious code
2. In case of absence of PC security solution installation
If the software is installed on a PC is infected with malicious software, normal software use might be unavailable, or the integrity of the saved data could become corrupt.
Any serious incident that has occurred in relation to the device should be reported to the manufacturer and the competent authority of the Member State in which the user and/or patient is established.

Caution

For detailed information on cautions, please refer to the instructions for use.

Lung Cancer Screening AI Solution

aview LCS: An AI Solution for Detection and Analysis of Lung Nodules from Chest CT.