Lung Cancer Screening
AI Solution

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

aview LCS | Lung Cancer Screening AI Solution
aview LCS

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

01

Automated Nodule Detection and Lung-RADS Calculation

Detecting and Analyzing Easy to miss Lung Nodules on Low-Dose Chest CT with Imaging Artificial Intelligence.

Efficiently diagnose with awareness of patient conditions.

Finding microscopic nodules provides a variety of information, including basic, number of nodules, size and status, and RADS category. Findings that are likely to develop into lung cancer can also be checked in advance, reducing working time and allowing efficient reading depending on the case. Microscopic Nodule Detection: Providing Comprehensive Information on Number of Nodules, Size, Status, and RADS Category Early Detection of Potential Lung Cancer Development Enables Time-efficient Scans Reading.
aview LCS | Automated Nodule Detection and Lung-RADS Calculation
aview LCS | Automated Nodule Detection and Lung-RADS Calculation
aview LCS | Automated Nodule Detection and Lung-RADS Calculation

Detecting Nodules of Various Sizes, from Small to Large

  • aview LCS | Detecting Nodules of Various Sizes, from Small to Large aview LCS | Detecting Nodules of Various Sizes, from Small to Large
  • aview LCS | Detecting Nodules of Various Sizes, from Small to Large aview LCS | Detecting Nodules of Various Sizes, from Small to Large
  • aview LCS | Detecting Nodules of Various Sizes, from Small to Large aview LCS | Detecting Nodules of Various Sizes, from Small to Large
  • aview LCS | Detecting Nodules of Various Sizes, from Small to Large aview LCS | Detecting Nodules of Various Sizes, from Small to Large
  • aview LCS | Detecting Nodules of Various Sizes, from Small to Large aview LCS | Detecting Nodules of Various Sizes, from Small to Large

02

Follow up mode

Automated Matching of Follow-up with Previous Lung CT Scans Instantly Assess Nodule Changes.

Monitoring Nodule Growth is Vital for Accurate Readings.

It autonomously assesses growth and changes by matching lung nodules, going beyond mere image comparisons.
aview LCS efficiently 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
aview LCS | Automated Matching of Follow-up with Previous Lung CT Scans Instantly Assess Nodule Changes
aview LCS | Automated Matching of Follow-up with Previous Lung CT Scans Instantly Assess Nodule Changes
aview LCS | Automated Matching of Follow-up with Previous Lung CT Scans Instantly Assess Nodule Changes

03

Clinical Viewer

CT Findings are visualized in 3D.
User-Friendly Viewer for Medical Professionals and Patients.

Advanced 3D Rendering of Patient’s Lung.

2D Images May Not Provide Adequate Information of Abnormal Findings Visualized 3D Model of Patient’s Lung is much more informative and intuitive. Abnormal findings can be easily explained by demonstration of the 3D Model.
aview LCS | CT Findings are visualized in 3D, User-Friendly Viewer for Medical Professionals and Patients
aview LCS | CT Findings are visualized in 3D, User-Friendly Viewer for Medical Professionals and Patients
aview LCS | CT Findings are visualized in 3D, User-Friendly Viewer for Medical Professionals and Patients
aview LCS | CT Findings are visualized in 3D, User-Friendly Viewer for Medical Professionals and Patients

04

Delivering Comprehensive Analysis Results

Automatically Analyze Lung Cancer Screening Results and
Generate Comprehensive Reports.

Automate Tedious manual Tasks to Save Time.

  • Reading report

    Effortless Generation of Lung Cancer Screening Results for Patient Records and Official Reports.

    aview LCS | Effortless Generation of Lung Cancer Screening Results 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 (
    |
  • Patient Reports and insurance reimbursement reports

    Automatically generated reports with detail assist patients understand examination results.

    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results
    aview LCS | Automatically generated reports with detail assist patients understand examination results

Validations

Clinically Proven: AI Medical Technology Saves
Time and Enhances Reading Accuracy.

  • aview LCS | Validations | Time Saving

    0

    Time Saving

  • aview LCS | Validations | Sensitivity

    0

    Sensitivity

  • aview LCS | Validations | false positivity rate

    23

    false positivity rate

  • aview LCS | Validations | Reduce Workload

    Reduce Workload

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https://dailybulletin.rsna.org/db22/index.cfm?pg=22fri07

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Lancaster HL, Zheng S, Aleshina OO, Yu D, Yu Chernina V, Heuvelmans MA, de Bock GH, Dorrius MD, Willem Gratama J, Morozov SP, Gombolevskiy VA, Silva M, Yi J, Oudkerk M. Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification. Lung Cancer. 2022 Jan 6;165:133-140

Publications

Refer to the following research papers

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