Automated COPD Analysis AI Solution

Interstitial Lung Disease Pattern Analysis Solution

Coronary Artery Calcification Analysis Solution

Coronary Artery Disease is the Leading Global Cause of Mortality.
It Can Be Detected by Calcification Analysis from CT examination.
Medical AI Technology Achieves high accuracy of 99.2% in Coronary Artery Calcification Detection.

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aview CAC | Automated COPD Analysis AI Solution

Conformity Certifications

MFDS

Republic of Korea
FDA

United States of America
PMDA

Japan
TFDA

Taiwan
CE

Europe
TGA

Australia
HSA

Singapore
ANVISA

Brazil
HC

Canada

Automate workflows

Reduce Work Fatigue and Save Time

Medical AI Technology Replaces Cumbersome Manual Tasks

Medical AI automatically segments and labels cardiac structures.
In complex cardiac structures, only the calcifications within the coronary arteries can be clearly detected, thereby improving the accuracy of cardiovascular disease analysis.
The task is completed quickly and accurately with low interreader variation.

aview CAC | Reduce Work Fatigue and Save Time

Analysis of chest CT images

Detect and analyze calcium within
the coronary arteries from cardiac exams and chest CT images.

Proprietary kernel conversion technology improves accuracy and performance for quick analysis

Identifying calcium on low-dose chest CT images can be challenging with the naked eye.
Medical AI assists in detecting even those cardiovascular conditions that might be overlooked.

Reading Assistance & Communication

Communication with patients becomes easier.

Accurate reading and swift processing.
Quantified 'Coronary Artery Calcium Score' makes diagnosis results easily comprehensible.

Patients and medical professionals can communicate more effectively and precisely with quantified results during consultations.

Communication

Optimize the Utilization of Diagnosis Analysis Results

Are you working on a clinical study?
Use rich results for your research.

An automated report is generated, providing accurate and detailed results.

The results include a calcification score, along with a detailed risk and age analysis by vessel, to assist patients in understanding their diagnosis. The analyzed result values are extracted as CSV files and PDF files and can be found within the PACS System.

Reading report

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Report

Validations

Our solution demonstrates remarkable concordance,
not just in cardiac CT scans but also in low-dose CT (LDCT) scans.

cardiac CT imaging study

Kappa

0

Risk Classification Consistency
ICC

0

Consistency
Drug Treatment Target Screening

0

accuracy
R2

Correlation

Vonder M, Zheng S, Dorrius MD, van der Aalst CM, de Koning HJ, Yi J, Yu D, Gratama JWC, Kuijpers D, Oudkerk M. Deep Learning for Automatic Calcium Scoring in Population-Based Cardiovascular Screening. JACC Cardiovasc Imaging. 2022 Feb;15(2):366-367. doi: 10.1016/j.jcmg.2021.07.012. Epub 2021 Aug 18.

Aldana-Bitar J, Cho GW, Anderson L, Karlsberg DW, Manubolu VS, Verghese D, Hussein L, Budoff MJ, Karlsberg RP. Artificial intelligence using a deep learning versus expert computed tomography human reading in calcium score and coronary artery calcium data and reporting system classification. Coron Artery Dis. 2023 May 1. doi: 10.1097/MCA.0000000000001244. Epub ahead of print.

LowDose CT Imaging Study

ICC

0

Consistency

Suh YJ, Kim C, Lee JG, Oh H, Kang H, Kim YH, Yang DH. Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT. Eur Radiol. 2023 eb;33(2):1254-1265. doi: 10.1007/s00330-022-09117-3. Epub 2022 Sep 13.

Publications

Refer to the following research papers

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

The objective of this study is to validate an artificial intelligence (AI)–based fully automatic coronary artery calcium (CAC) scoring system on non-electrocardiogram (ECG)–gated low-dose chest computed tomography (LDCT) using multi-institutional datasets with manual CAC scoring as the reference standard.
The Coreline Soft Aview CAC, an AI-based automatic CAC scoring software to LDCT shows good to excellent reliability in CAC score and CAC severity categorization in multi-institutional datasets.

Young Joo Suh, Cherry Kim, June-Goo Lee, Hongmin Oh, Heejun Kang, Young-Hak Kim & Dong Hyun Yang. "Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT" European Radiology volume 33, pages1254–1265 (2023)
The objective of the current study was to evaluate the performance of deep learning–based software (CAC, Corelinesoft) for automatic coronary calcium scoring in a screening setting.
The deep learning–based software for automatic CAC scoring performed excellently in a population-based screening setting to determine risk categorization in asymptomatic participants.
Future deep learning software that is able to assign a limited number of uncertain cases for manual human feedback could improve the calcium scoring process and outperform (a panel of) experienced readers that solely use manual scoring.

Marleen Vonder PhD, Sunyi Zheng PhD, Monique D. Dorrius MD, PhD, Carlijn M. van der Aalst PhD, Harry J. de Koning MD, PhD, Jaeyoun Yi PhD, Donghoon Yu MSc, Jan Willem C. Gratama MD, PhD, Dirkjan Kuijpers MD, PhD, Matthijs Oudkerk MD, PhD "Deep Learning for Automatic Calcium Scoring in Population-Based Cardiovascular Screening" JACC: Cardiovascular Imaging Volume 15, Issue 2, February 2022, Pages 366-367

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