Coreline Soft Co., Ltd
Founded in 2012, Coreline Soft provides the AI-based chest CT diagnostic aid suite AVIEW for lung nodules, COPD, and coronary calcification.
As of 2026-10-10, Coreline Soft Co., Ltd has 3 MFDS Innovative Medical Device designations, 38 Korean MFDS device approvals, 12 US FDA clearances/approvals, 41 PubMed-indexed papers on record (counted by the MAA Company Index from its own matching of public databases).
Price
Change
Market cap
Business overview
Source: DART corporate disclosureFounded in 2012 and listed on KOSDAQ in 2023, Coreline Soft is an AI-based medical imaging software company. Its flagship chest CT analysis products are AVIEW LCS (lung nodule diagnosis aid, launched 2016), AVIEW COPD (chronic obstructive pulmonary disease diagnosis aid, 2016), and AVIEW CAC (coronary artery calcification diagnosis aid, 2020), with the product line expanded to include diagnostic aids for cerebral hemorrhage, aortic dissection, and pulmonary embolism. AVIEW LCS began hospital services through Korea's National Cancer Center, and after establishing a European subsidiary in 2020 and a US subsidiary in 2021, the company secured Germany's HANSE lung cancer screening program, Italy's ILSP lung cancer screening project, and the six-country European 4-ITLR multinational lung cancer screening project.
Products & technology
- AVIEW LCSAI-based automatic lung nodule analysis (launched 2016)
- AVIEW LCS PLUSAI-based automatic analysis of Big 3 Disease: lung nodule, emphysema, coronary calcification (launched 2020)
- AVIEW COPDAI-based automatic COPD analysis (launched 2016)
- AVIEW CACAI-based automatic coronary artery calcification analysis (launched 2020)
- AVIEW Lung TextureAI-based automatic interstitial lung disease pattern analysis (launched 2021)
- AVIEW BASAI-based cerebral vascular structure visualization (launched 2021)
- AVIEW NeuroCADAI-based cerebral hemorrhage analysis and diagnosis aid (launched 2021)
- AVIEW RT ACSAI-based automatic organ segmentation for radiotherapy (launched 2020)
- AVIEW ModelerAutomatic/semi-automatic medical image segmentation for 3D modeling and printing (launched 2017)
- AVIEW ResearchResearch medical imaging data management and integrated research platform (launched 2018)
- AVIEW AortaAI-based aortic dissection diagnosis aid (launched 2024)
- AVIEW PEAI-based pulmonary embolism diagnosis aid (launched 2024)
Regulatory approvals
data.go.kr · openFDA3 Innovative Medical Device designations · 2020–2024 / 38 Korean MFDS device approvals · 2016–2026 / 12 US FDA 510(k) · 2018–2025
- InnovativeAVIEW PE2024-06-26Innovative Medical Device designation
- InnovativeAVIEW Aorta2024-02-21Innovative Medical Device designation
- InnovativeAVIEW NeuroCAD2020-11-17Innovative Medical Device designation
- MFDSProduct name not recorded2026-07-10Product approval · Class 2인 26-4028 호
- MFDSProduct name not recorded2026-06-01Product approval · Class 1신 26-61 호
- MFDSProduct name not recorded2026-04-24Product approval · Class 1신 26-49 호
- MFDSProduct name not recorded2026-03-19Product approval · Class 1신 26-32 호
- FDAAVIEW Lung Nodule CAD2025-12-03
- MFDSProduct name not recorded2025-05-02Product approval · Class 1신 25-6 호
- MFDSMedical image, computer aided detection/ diagnosis software, class 32025-03-25Product approval · Class 3제허 25-184 호
- MFDSProduct name not recorded2025-03-25Product approval · Class 3허 25-184 호
- FDAAVIEW2025-03-19
Show 41 more
- FDAAVIEW CAC2025-02-14
- MFDSMedical image, picture archiving and communication system, software, class 12024-12-02Product approval · Class 1제신 24-1499 호
- MFDSProduct name not recorded2024-12-02Product approval · Class 1신 24-1499 호
- MFDSMedical image, analysis software2024-08-08Product approval · Class 2제인 24-767 호
- MFDSProduct name not recorded2024-08-08Product approval · Class 2인 24-767 호
- MFDSMedical image, computer aided detection/ diagnosis software, class 22024-07-26Product approval · Class 2제허 24-504 호
- MFDSProduct name not recorded2024-07-26Product approval · Class 2허 24-504 호
- MFDSCardiovascular image, computer aided detection/ diagnosis software2024-04-30Product approval · Class 3제허 24-301 호
- MFDSProduct name not recorded2024-04-30Product approval · Class 3허 24-301 호
- MFDSMedical image, computer aided detection/ diagnosis software, class 22024-04-29Product approval · Class 2제인 24-446 호
- MFDSProduct name not recorded2024-04-29Product approval · Class 2인 24-446 호
- FDAAVIEW CAC2024-03-29
- MFDSMedical image, analysis software2024-01-16Product approval · Class 2제인 24-55 호
- MFDSProduct name not recorded2024-01-16Product approval · Class 2인 24-55 호
- MFDSMedical image, analysis software2023-09-01Product approval · Class 2제인 23-5060 호
- MFDSProduct name not recorded2023-09-01Product approval · Class 2인 23-5060 호
- FDAAVIEW Lung Nodule CAD2023-02-24
- MFDSCardiovascular image, analysis software2023-02-01Product approval · Class 2제인 23-4121 호
- MFDSProduct name not recorded2023-02-01Product approval · Class 2인 23-4121 호
- FDAAVIEW2022-12-23
- FDAAVIEW RT ACS2022-11-10
- MFDSNeural image, computer aided detection/diagnosis software2021-12-15Product approval · Class 3제허 21-1013 호
- MFDSProduct name not recorded2021-12-15Product approval · Class 3허 21-1013 호
- MFDSCardiovascular image, computer aided detection/ diagnosis software2021-07-02Product approval · Class 3제허 21-554 호
- MFDSProduct name not recorded2021-07-02Product approval · Class 3허 21-554 호
- MFDSNeural image, analysis software2021-04-19Product approval · Class 2제인 21-4318 호
- MFDSProduct name not recorded2021-04-19Product approval · Class 2인 21-4318 호
- FDAA View LCS2020-10-16
- FDAAVIEW2020-08-26
- MFDSMedical image, analysis software2020-07-16Product approval · Class 2제인 20-4631 호
- MFDSProduct name not recorded2020-07-16Product approval · Class 2인 20-4631 호
- MFDSMedical image, computer aided detection/ diagnosis software, class 22020-06-16Product approval · Class 2제허 20-484 호
- MFDSProduct name not recorded2020-06-16Product approval · Class 2허 20-484 호
- FDAAVIEW LCS2020-05-05
- MFDSMedical image, computer aided detection/ diagnosis software, class 22020-04-21Product approval · Class 2제허 20-298 호
- MFDSProduct name not recorded2020-04-21Product approval · Class 2허 20-298 호
- FDAAVIEW Modeler2019-12-20
- FDAAVIEW2018-10-31
- MFDSGuide for medical useRevoked2016-12-12Product approval · Class 1제신 16-1472 호
- MFDSMedical image, analysis software2016-07-21Product approval · Class 2제인 16-4603 호
- MFDSProduct name not recorded2016-07-21Product approval · Class 2인 16-4603 호
Key disclosures
KRX KIND via OpenDARTShow 6 more events
Publications
PubMed · affiliation-matched- Automated artificial intelligence performance for longitudinal pulmonary nodule matching in lung cancer screening.
European radiology · 2026-08 · Jiang B, Lancaster HL, Davies MPA 외 9
- Negligible impact of perifissural nodules in an AI-first reader workflow from UK lung screening trial.
European radiology · 2026-08 · Jiang B, Han D, Cai J 외 10
- Standardizing attenuation across tube voltages and vertebral levels for opportunistic osteoporosis screening on low-dose chest CT.
Radiology advances · 2026-05 · Kim Y, Hong S, Chee CG 외 4
- Bronchiectasis in patients with chronic obstructive pulmonary disease: AI-based CT quantification using the bronchial tapering ratio.
European radiology · 2026-03 · Park H, Choe J, Lee SM 외 11
- Artificial intelligence as an independent reader of risk-dominant lung nodules: influence of CT reconstruction parameters.
European radiology · 2026-03 · Mao Y, Heuvelmans MA, van Tuinen M 외 6
- Automatic segmentation and labeling of T1, T7, and T12 thoracic vertebrae in neonatal chest radiographs: a deep learning approach using nnU-Net framework.
Frontiers in pediatrics · 2026-01 · Jung S, Yun H, Cho HW 외 4
- AI performance for nodule volume doubling time in the follow-up of the UKLS lung cancer screening study compared to expert consensus and histological validation.
European journal of cancer (Oxford, England : 1990) · 2026-01 · Jiang B, Lancaster HL, Davies MPA 외 9
- Differentiation of pulmonary tuberculosis from non-tuberculous solid lung lesions using radiomics and clinical-semantic features on contrast-enhanced CT.
Frontiers in medicine · 2026-01 · Zheng S, Wang J, Liang J 외 9
- Leveraging deep learning-based kernel conversion for more precise airway quantification on CT.
European radiology · 2025-11 · Choe J, Yun J, Kim MJ 외 6
- Comparison of nodule volumetric classification by using two different nodule segmentation algorithms in an LDCT lung cancer baseline screening dataset.
European journal of radiology · 2025-10 · Mao Y, Lancaster HL, Heuvelmans MA 외 8
Show 31 more publications
- Impact of Deep Learning-Based Image Conversion on Fully Automated Coronary Artery Calcium Scoring Using Thin-Slice, Sharp-Kernel, Non-Gated, Low-Dose Chest CT Scans: A Multi-Center Study.
Korean journal of radiology · 2025-08 · Kim C, Hong S, Choi H 외 10
- Longitudinal Tracking of Emphysema Holes at Noncontrast CT: Dynamic Patterns and Clinical Relationships.
Radiology · 2025-07 · Ahn Y, Lee EJ, Yun J 외 8
- Age-dependent changes in CT vertebral attenuation values in opportunistic screening for osteoporosis: a nationwide multi-center study.
European radiology · 2025-06 · Kim Y, Kim HY, Lee S 외 2
- Feasibility of deep learning algorithm in diagnosing lumbar central canal stenosis using abdominal CT.
Skeletal radiology · 2025-05 · Jeon Y, Kim BR, Choi HI 외 4
- Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.
European journal of cancer (Oxford, England : 1990) · 2025-05 · Lancaster HL, Jiang B, Davies MPA 외 8
- Artificial intelligence system for identification of overlooked lung metastasis in abdominopelvic computed tomography scans of patients with malignancy.
Diagnostic and interventional radiology (Ankara, Turkey) · 2025-03 · Cho HS, Hwang EJ, Yi J 외 2
- Improving functional correlation of quantification of interstitial lung disease by reducing the vendor difference of CT using generative adversarial network (GAN) style conversion.
European journal of radiology · 2025-02 · Choe J, Hwang HJ, Kim MS 외 9
- Deep-Learning-Based Multi-Class Classification for Neonatal Respiratory Diseases on Chest Radiographs in Neonatal Intensive Care Units.
Neonatology · 2025-01 · Cho HW, Jung S, Park KH 외 7
- Experience of Implementing Deep Learning-Based Automatic Contouring in Breast Radiation Therapy Planning: Insights From Over 2000 Cases.
International journal of radiation oncology, biology, physics · 2024-08 · Lee BM, Kim JS, Chang Y 외 6
- Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.
BMC pulmonary medicine · 2024-07 · Lee JU, Park JS, Seo E 외 5
- Development and validation of a reliable method for automated measurements of psoas muscle volume in CT scans using deep learning-based segmentation: a cross-sectional study.
BMJ open · 2024-05 · Choi W, Kim CH, Yoo H 외 3
- Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals.
Korean journal of radiology · 2024-03 · Kim K, Cho K, Jang R 외 6
- Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers.
Diseases (Basel, Switzerland) · 2024-03 · Kwon OB, Lee HU, Park HE 외 4
- Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease.
Scientific reports · 2024-02 · Choe J, Choi HY, Lee SM 외 9
- Comparing chair stand test protocols: Fifth stand versus fifth sit.
Geriatrics & gerontology international · 2023-12 · Ji S, Jang R, Roh H 외 5
- Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease.
Korean journal of radiology · 2023-08 · Hwang HJ, Kim H, Seo JB 외 20
- Influence of computed tomography slice thickness on deep learning-based, automatic coronary artery calcium scoring software performance.
Quantitative imaging in medicine and surgery · 2023-07 · Kim SY, Suh YJ, Lee HJ 외 4
- Interstitial lung abnormalities (ILA) on routine chest CT: Comparison of radiologists' visual evaluation and automated quantification.
European journal of radiology · 2022-12 · Kim MS, Choe J, Hwang HJ 외 7
- Automated Computer-Aided Detection of Lung Nodules in Metastatic Colorectal Cancer Patients for the Identification of Pulmonary Oligometastatic Disease.
International journal of radiation oncology, biology, physics · 2022-12 · Lee JJB, Suh YJ, Oh C 외 7
- A Challenge for Emphysema Quantification Using a Deep Learning Algorithm With Low-dose Chest Computed Tomography.
Journal of thoracic imaging · 2022-07 · Choi H, Kim H, Jin KN 외 14
- Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification.
Lung cancer (Amsterdam, Netherlands) · 2022-03 · Lancaster HL, Zheng S, Aleshina OO 외 11
- Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy.
Radiation oncology (London, England) · 2021-10 · Byun HK, Chang JS, Choi MS 외 8
- New Method for Combined Quantitative Assessment of Air-Trapping and Emphysema on Chest Computed Tomography in Chronic Obstructive Pulmonary Disease: Comparison with Parametric Response Mapping.
Korean journal of radiology · 2021-10 · Hwang HJ, Seo JB, Lee SM 외 6
- Optimum diameter threshold for lung nodules at baseline lung cancer screening with low-dose chest CT: exploration of results from the Korean Lung Cancer Screening Project.
European radiology · 2021-09 · Hwang EJ, Goo JM, Kim HY 외 2
- Variability in interpretation of low-dose chest CT using computerized assessment in a nationwide lung cancer screening program: comparison of prospective reading at individual institutions and retrospective central reading.
European radiology · 2021-05 · Hwang EJ, Goo JM, Kim HY 외 4
- Implementation of the cloud-based computerized interpretation system in a nationwide lung cancer screening with low-dose CT: comparison with the conventional reading system.
European radiology · 2021-01 · Hwang EJ, Goo JM, Kim HY 외 3
- Correction of malocclusion using sliding fibula osteotomy with sagittal split ramus osteotomy after mandible reconstruction.
Maxillofacial plastic and reconstructive surgery · 2020-12 · Lee DH, Kim SR, Jang S 외 2
- Evaluation of Effective Condyle Positioning Assisted by 3D Surgical Guide in Mandibular Reconstruction Using Osteocutaneous Free Flap.
Materials (Basel, Switzerland) · 2020-05 · Kim SR, Jang S, Ahn KM 외 1
- Mirror Image Based Three-Dimensional Virtual Surgical Planning and Three-Dimensional Printing Guide System for the Reconstruction of Wide Maxilla Defect Using the Deep Circumflex Iliac Artery Free Flap.
The Journal of craniofacial surgery · 2019-09 · Jang WH, Lee JM, Jang S 외 3
- Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.
Medical image analysis · 2019-01 · Yun J, Park J, Yu D 외 6
- Automated Detection Algorithm of Breast Masses in Three-Dimensional Ultrasound Images.
Healthcare informatics research · 2016-10 · Jeong JW, Yu D, Lee S 외 1
Patents
KIPRIS · applicant-matchedUS · Published · 2025-05 · Application 19195914
US · Published · 2025-04 · Application 19180318
Published · 2024-12 · Application 1020240197351
US · Published · 2024-08 · Application 18800105
US · Published · 2024-07 · Application 18790053
EP · Published · 2024-07 · Application 24192132.9
EP · Published · 2024-07 · Application 24191189.0
Registered · 2024-05 · Application 1020240058373
US · Registered · 2024-04 · Application 18647161
Published · 2024-04 · Application 1020240049577
Show 86 more patents
Published · 2024-03 · Application 1020240043736
US · Published · 2024-03 · Application 18621438
US · Published · 2024-03 · Application 18621487
Published · 2024-03 · Application 1020240043747
Published · 2024-02 · Application 1020240030124
Rejected · 2023-08 · Application 1020230105223
Registered · 2023-07 · Application 1020230099656
Rejected · 2023-07 · Application 1020230098226
US · Registered · 2023-06 · Application 18334617
US · Published · 2023-04 · Application 18307444
Registered · 2023-03 · Application 1020230039720
Published · 2023-03 · Application 1020230036174
US · Registered · 2023-03 · Application 18123853
US · Published · 2023-01 · Application 18154967
Published · 2022-12 · Application 1020220191265
US · Registered · 2022-12 · Application 18091828
US · Registered · 2022-12 · Application 18076513
Registered · 2022-09 · Application 1020220118113
Registered · 2022-09 · Application 1020220118135
Registered · 2022-08 · Application 1020220108510
Withdrawn · 2022-07 · Application 1020220081962
Published · 2022-05 · Application 1020220061893
US · Registered · 2022-05 · Application 17746347
Registered · 2021-12 · Application 1020210173370
US · Registered · 2021-11 · Application 17538625
US · Registered · 2021-11 · Application 17538627
Registered · 2021-11 · Application 1020210156771
Registered · 2021-10 · Application 1020210130548
Withdrawn · 2021-07 · Application 1020210097065
Registered · 2021-06 · Application 1020210081539
EP · Published · 2021-05 · Application 21842070.1
PCT · Published · 2021-05 · Application PCT/KR2021/006670
Published · 2021-05 · Application 1020210067351
Registered · 2021-05 · Application 1020210063580
Registered · 2021-03 · Application 1020210030389
US · Registered · 2020-12 · Application 17139361
US · Registered · 2020-12 · Application 17132086
Registered · 2020-11 · Application 1020200164449
Registered · 2020-11 · Application 1020200164594
US · Registered · 2020-11 · Application 16953175
Withdrawn · 2020-09 · Application 1020200127430
Registered · 2020-07 · Application 1020200088088
US · Registered · 2020-06 · Application 16896801
US · Registered · 2020-06 · Application 16896790
US · Published · 2020-05 · Application 15931083
Registered · 2019-12 · Application 1020190179252
Registered · 2019-12 · Application 1020190179240
Registered · 2019-12 · Application 1020190177122
Registered · 2019-11 · Application 1020190148489
Registered · 2019-07 · Application 1020190092909
Registered · 2019-07 · Application 1020190091525
Rejected · 2019-07 · Application 1020190091538
US · Published · 2019-06 · Application 16431018
US · Registered · 2019-06 · Application 16430971
Registered · 2019-05 · Application 1020190056152
US · Registered · 2019-05 · Application 16411378
PCT · Published · 2018-11 · Application PCT/KR2018/014305
Registered · 2018-06 · Application 1020180070722
Registered · 2018-06 · Application 1020180064258
Withdrawn · 2018-06 · Application 1020180064259
Registered · 2018-05 · Application 1020180054924
US · Registered · 2018-05 · Application 15977064
US · Registered · 2018-04 · Application 15964796
Registered · 2017-11 · Application 1020170155988
US · Registered · 2017-05 · Application 15609785
Registered · 2017-05 · Application 1020170059292
Registered · 2017-04 · Application 1020170054789
PCT · Published · 2017-04 · Application PCT/KR2017/004298
Withdrawn · 2016-08 · Application 1020160110311
Expired · 2016-07 · Application 1020160094506
Registered · 2016-06 · Application 1020160077348
Registered · 2016-05 · Application 1020160067139
US · Registered · 2016-05 · Application 15168857
Expired · 2016-05 · Application 1020160061461
US · Published · 2016-05 · Application 15153061
Expired · 2015-11 · Application 1020150159889
CN · Published · 2015-06 · Application 201580039787.5
PCT · Published · 2015-06 · Application PCT/KR2015/006086
Registered · 2015-05 · Application 1020150076450
Registered · 2015-05 · Application 1020150076492
Registered · 2015-05 · Application 1020150065752
US · Published · 2015-04 · Application 14698019
Expired · 2014-07 · Application 1020140090123
Registered · 2014-04 · Application 1020140051760
Rejected · 2014-04 · Application 1020140050921
Registered · 2014-04 · Application 1020140043240
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Connect it to ChatGPT or Claude, and your AI queries the full record — profiles, financials, stock data, regulatory approvals, clinical trials, publications and patents — for Coreline Soft Co., Ltd and every listed Korean medical, bio and AI company.
How to connect (MCP)Companies approved for the same productsMedical AI
Ranked by how many MFDS product categories overlap. Not a ranking — a pointer to where to look.
Founded in 2008 and listed on KOSDAQ in 2021, DEEPNOID develops medical and industrial AI imaging solutions like DEEP:NEURO.
JLK offers the stroke AI solution MEDIHUB STROKE and holds 78 global regulatory approvals, including US FDA and Japan PMDA clearances.
Founded in 2014, VUNO provides AI-based vital-sign and medical imaging diagnostic solutions, including VUNO Med-DeepCARS and VUNO Med-Fundus AI.
Founded in 2016 and listed on KOSDAQ in 2025, Neurophet develops AI brain-imaging solutions AQUA, SCALE PET, and AQUA AD.
Founded in 2000 and KOSDAQ-listed in 2013, Corentec makes artificial joints; hip and knee implants exceed 85% of revenue.
KOSDAQ-listed X-ray imaging solution company with a full lineup of medical, dental, veterinary, and industrial X-ray detectors.
Provides EMS and SMT manufacturing services for TFT-LCD and OLED panel driver PBAs.
Founded in 1997 and KOSDAQ-listed in 2015, CG MedTech makes orthopedic medical devices and also operates an electric energy business.
Founded in 1982 and KOSDAQ-listed in 2008, Sewoon Medical manufactures medical aspirators and catheters/tubes.
Founded in 2016 and listed on KOSDAQ in 2017, DENTIS manufactures dental implants, medical LED lighting, and dental 3D printers.
Dong-A ST, spun off from Dong-A Socio Holdings in 2013 and KOSPI-listed, makes prescription drugs like Growtropin, Stillen, and Bacchus.
Uses AI analysis of medical imaging to 3D-print patient-specific surgical guides, implants, and simulators.
Sources and updates
Counts on this page are not company-reported figures. MAA matched records from DART, the Korean MFDS, the US FDA, ClinicalTrials.gov, PubMed and KIPRIS to this company itself, by business registration number or registered name, never by name similarity. They may differ from figures the company publishes.
- Company basics
- Korea Exchange · DART
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- Approvals & clinical trials
- Korean MFDS (data.go.kr) · US FDA openFDA — updated weekly
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- DART corporate disclosure filings — annual
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