Who is the manufacturer of AVIEW LCS?

Coreline Soft Co., Ltd. filed the 510(k) submission for AVIEW LCS (K193220).

What is the FDA product code for AVIEW LCS?

LLZ. It is classified under 21 CFR 892.2050 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for AVIEW LCS?

510(k) clearance (submission type: Traditional).

Does AVIEW LCS use AI or machine learning?

Yes. AVIEW LCS (K193220) is flagged as an AI/ML-enabled medical device in the FDA's AI/ML device list.

Who can help prepare an FDA 510(k) submission like AVIEW LCS?

Innolitics — a medical-device software consultancy — provides regulatory and engineering support for FDA 510(k) submissions. See https://innolitics.com/services/510ks/ or contact https://innolitics.com/contact.

Can an AI/ML device like AVIEW LCS get a guaranteed FDA 510(k) clearance?

Yes. Innolitics offers a guaranteed FDA 510(k) clearance engagement for AI/ML Software as a Medical Device — combining engineering and regulatory execution under one agreement with a guaranteed clearance outcome. Eligibility: the device must be an AI/ML Software as a Medical Device (SaMD), and its performance must meet the criteria Innolitics determines during an initial regulatory strategy engagement to be necessary for FDA clearance. See https://innolitics.com/services/end-to-end-samd/ or contact https://innolitics.com/contact.

AVIEW LCS

K193220 · Coreline Soft Co., Ltd. · LLZ · May 5, 2020 · Radiology

Device Facts

Record ID	K193220
Device Name	AVIEW LCS
Applicant	Coreline Soft Co., Ltd.
Product Code	LLZ · Radiology
Decision Date	May 5, 2020
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.2050
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device, Real-World Evidence

Real-World Evidence

Submission	Device	Sponsor	RWD Sources	RWE Use Summary	Key Tags
K193220 · May 5, 2020	AVIEW LCS	Coreline Soft Co., Ltd.	National Lung Screening Trial (NLST) cohort; Korean clinical chest CT datasets (COPD patients); PanCan clinical data; BCCA clinical data	Retrospective clinical data from the NLST and Korean clinical cohorts were used to validate the accuracy of the device's deep-learning-based lung/lobe segmentation and to support the clinical validity of the PANCAN malignancy risk calculation model.	Retrospective cohort; Algorithm validation; Deep learning; Clinical performance

Clinical Evidence

Study Design	Population	Comparator	Key Endpoints
NLST Cohort Segmentation Validation; Retrospective validation	80 patients enrolled in the National Lung Screening Trial (NLST); Sample Size: 80 patients	Manual segmentation by experienced radiographer/radiologist	Dice similarity coefficient
Korean COPD Patient Segmentation Validation; Retrospective validation	192 suspected COPD patients; Sample Size: 192 patients	Expert radiologist review	Qualitative classification (0: Not good, 1: need adjustment, 2: very good)

AI Performance

Output	Algorithm	Acceptance	Observed	Dev DS	Dev Readers	Test DS	Test Readers
Lung and lobe segmentation	Deep-learning algorithms	—	—	192 suspected COPD patients (Korean Data); 80 patients enrolled in NLST (NLST Data).	>1 (specialist and radiologist) + 1 (experienced radiolographer) + 1 (experienced radiologist)	—	—

Indications for Use

AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major, length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part. measured in sections perpendicular to the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).

Device Story

AVIEW LCS is a software-based diagnostic tool for thoracic CT image analysis. It processes DICOM-formatted thoracic CT scans to perform semi-automatic nodule segmentation and measurement (size, volume, density, VDT). The device integrates with third-party CAD (Mevis Visia) for automated nodule detection. It calculates malignancy risk using the PANCAN model and categorizes findings according to Lung-RADS. The system supports longitudinal follow-up by automatically retrieving past data and matching nodules across studies. Used in clinical settings by radiologists/physicians, the software provides structured PDF reports and DICOM-compatible images. By standardizing measurements and risk assessment, it assists clinicians in diagnostic decision-making and lung cancer screening workflows.

Clinical Evidence

Bench testing only. No clinical trials were conducted. Performance was validated through software verification, unit testing, and system testing. Accuracy of nodule segmentation was verified against sphere phantoms (volume error <10%). Lung/lobe segmentation (deep learning) was validated using 192 COPD patient scans (expert qualitative assessment) and 80 NLST patient scans (Dice similarity coefficient). PANCAN risk model and Lung-RADS implementation were verified against established datasets and regulatory guidelines.

Technological Characteristics

Software-only device for PC/network deployment. Inputs: DICOM thoracic CT images. Features: Deep-learning based lung/lobe segmentation, semi-automatic nodule segmentation, PANCAN malignancy risk calculation, Lung-RADS categorization. Connectivity: DICOM 3.0 standard. Output: Structured PDF reports and DICOM files. No hardware components.

Indications for Use

Indicated for review, analysis, and reporting of thoracic CT images to characterize lung nodules in single or longitudinal studies. Intended for use by clinicians for nodule measurement, malignancy risk assessment, and Lung-RADS categorization.

Regulatory Classification

Identification

A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.

Special Controls

*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).

Predicate Devices

Lung Nodule Assessment and Comparison Option (LNA) (K162484)

Reference Devices

Lung Analysis Software (K151283)
AVIEW (K171199)
Mevis CAD (K043617)

Submission Summary (Full Text)

{0}------------------------------------------------ Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue. May 5, 2020 Coreline Soft Co., Ltd. % Hye Yi Park Deputy General Manager Strategic Business Dept. 4, 5F (Yeonnam-dong), 49, World Cup buk-ro 6-gil, Mapo-gu Seoul. 03991 REPUBLIC OF KOREA Re: K193220 Trade/Device Name: AVIEW LCS Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ, JAK Dated: April 2, 2020 Received: April 6, 2020 Dear Hye Yi Park: We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading. If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register. Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for {1}------------------------------------------------ devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems. For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100). Sincerely. For Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health Enclosure {2}------------------------------------------------ ## DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration ## Indications for Use Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2020 See PRA Statement below. ### 510(k) Number (if known) K193220 Device Name AVIEW LCS ### Indications for Use (Describe) AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major, length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part. measured in sections perpendicular to the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617). Type of Use (Select one or both, as applicable) > Prescription Use (Part 21 CFR 801 Subpart D) Over-The-Counter Use (21 CFR 801 Subpart C) ## CONTINUE ON A SEPARATE PAGE IF NEEDED. This section applies only to requirements of the Paperwork Reduction Act of 1995. ### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: > Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." {3}------------------------------------------------ # K193220 # 510(k) Summary #### SUBMITTER 1 Coreline Soft Co., Ltd. 4,5F (Yeonnam-dong), 49 World Cup buk-ro 6-gil, Mapo-gu, Seoul, 03991, Republic of Korea. Phone: 82.2.517.7321 Fax: 82.2.571.7324 Contact Person: hyeyi. Park Date Prepared: 11.15.2019 #### DEVICE 2 Name of Device: AVIEW LCS Common or Usual Name: Image Processing Software Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ, JAK #### PREDICATE DEVICE 3 Lung Nodule Assessment and Comparison Option by Philips Medical System Nederland B.V. (K 162484) Name of Device: Lung Nodule Assessment and Comparison Option (LNA) Common or Usual Name: Lung Nodule Assessment and Comparison Option (LNA) Classification Name: System, image processing, radiological (21CFR 892.1750) Regulatory Class: II Product Code: LLZ, JAK This predicate has not been subject to a design-related recall #### REFERENCE DEVICE 4 Lung Analysis Software by Vital Images, Inc. (K151283) Name of Device: Lung Analysis Software Common or Usual Nmae: Radilolgical Image Processing Software Classification Name: System, Image Processing, Radiological Regulatory Class: II Product Code: JAK, LLZ {4}------------------------------------------------ ## AVIEW by Coreline Soft Co., Ltd. (K171199) Name of Device: AVIEW Common or Usual Name: Image Processing Software Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ This reference device has not been subject to a design-related recall #### DEVICEW DESCRIPTION 5 AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides following features as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules detection by integration with 3th party CAD. Also provides cancer risk based on PANCAN risk model which calculates the malignancy score based on numerical or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality assurance tool designed to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change and other findings that is reported. - -Nodule measurement - Adding nodule by segmentation or by lines . - Semi-automatic nodule measurement (segmentation) " - . Maximal plane measure, 3D measure and volumetric measure. - . Automatic large vessel removal. - י Provides various features calculated per each nodule such as size, major(longest diameter measured in 2D/3D), minor (shortest diameter measured in 2D/3D), maximal plane, volume, mean HU, minimum HU, maximum HU for solid nodules and ratio of the longest axis for solid to non solid for paritla solid nodules. - . Fully supporting Lung-RADS workflow: US Lung-RADS and KR Lung-RADS. - . Nodule malignancy score (PANCAN model) calculation. - . Importing from CAD results - -Follow-up - ' Automatic retrieving the past data - י Follow-up support with nodule matching and comparison - Automatic calculation of VDT (volume doubling time) - Automatic nodule detection (CADe) - - Seamless integration with Mevis Visia (FDA 510k Cleared) . - -Lungs and lobes segmentation - Better segmentation of lungs and lobes based on deep-learning algorithms. - -Report - PDF report generation . {5}------------------------------------------------ - . It saves or sends the pdf report and captured images in DICOM files. - . It provides structured report including following items such as nodule location and, also input finding on nodules. - Reports are generated using the results of all nodules nodules detected so far (Lung RADS) . - -Save Result - . It saves the results in internal format #### INDICATIONS FOR USE 6 AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major axis), estimated effective diameter from the volume of the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max (mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2™ Major: The length of the longest diameter of the solid part, measured in sections perpendicular to the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617). ## COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 7 THE PREDICATE DEVCIE AVIEW LCS has the same intended use and the principle of operation, and also has similar features to the predicate devices. Lung Nodule Assessment and Comparison Option (LNA) (K162484) There might be slight differences in features and menu, but these differences between the predicate device and the proposed device are not so significant since they do not raise any new or potential safety risks to the user or patient and questions of safety or effectiveness. Based on the results of software validation and verification tests, we conclude that the proposed device is substantially equivalent to the predicate devices. | Characteristic | Subject Device | Primary Predicate Device | Reference Device | Reference Device | |------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------|---------------------------------------------|---------------------------------------------| | Device Name | AVIEW LCS | Lung Nodule Assessment and Comparison Option (LNA) | Lung Analysis Software | AVIEW | | Classification Name | System, image Processing Radiological | System, image Processing Radiological | System, image Processing Radiological | System, image Processing Radiological | | Regulatory Number | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | | Product Code | LLZ, JAK | LLZ, JAK | LLZ, JAK | LLZ | | Review Panel | Radiology | Radiology | Radiology | Radiology | | 510k Number | - | K162484 | K151283 | K171199 | | Indications for use | AVIEW LCS AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several | | | | {6}------------------------------------------------ | thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major axis, minor axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617). Lung Nodule Assessment and Comparison Option (LNA) The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient- imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume and volume over time. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed. Toshiba's Lung Analysis Software The separately licensed Lung Analysis option is intended for the review and analysis of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterization include diameter, volume and volume over time. The system automatically performs the measurement, allowing lung nodules and measurement to be displayed. AVIEW | | | | | |----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | AVIEW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be used to support the physician quantitatively in the diagnosis. Follow-up evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in the left and right lung (e.g., the five lobes and airway), volumetric and structural analysis, density evaluations and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data sets. AVIEW is not meant for primary image Interpretation in mammography. | | | | | | Platform | IBM-compatible PC or PC network | IBM-compatible PC or PC network | IBM-compatible PC or PC network | | | User Interface | Monitor, Mouse, Keyboard | Monitor, Mouse, Keyboard | Monitor, Mouse, Keyboard | | | Image Input Sources | Images can be scanned, loaded from card readers, or imported from a radiographic imaging device | Images can be scanned, loaded from card readers, or imported from a radiographic imaging device | Images can be scanned, loaded from card readers, or imported from a radiographic imaging device | | | Image format | DICOM | DICOM | DICOM | | | Intended body part | Chest | Chest | Chest | | | Type of scans | Thoracic CT images | Thoracic CT images | Thoracic CT images | | | General Description | AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides following features as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules detection by integration with 3rd party CAD. Also provides cancer risk based on PANCAN risk model which calculates the malignancy score based on numerical or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality assurance tool designed to standardize lung cancer screening CT reporting and | | | | | Key Functions | | | | | | | management recommendations that is based on type, size, size change and other findings that is reported. | | | | | | Lung Nodule Assessment and Comparison Option (LNA) | | | | | | The Lung Nodule Assessment and Comparison Option application is intended for use as a diagnostic patient imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed. The user interface and automated tools help to determine growth patterns and compose comparative reviews. The Lung | | | | | | Nodule Assessment and Comparison Option application requires the user to identify a nodule and to determine the type of nodule in order to use the appropriate characterization tool. Lung Nodule Assessment and Comparison Option may be utilized in both diagnostic and screening evaluations supporting Low Dose CT Lung Cancer Screening | | | | | | Lung Analysis Software | | | | | | Lung Analysis aids in measuring and characterizing lung nodules. The interface and automated tools help to efficiently determine growth patterns and compose comparative reviews. Lung Analysis is intended for the review and analysis of thoracic CT images for the purpose of characterizing nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume and volume over time. The system automatically performs the | | | | | | measurements, allowing lung nodules and measurements to be displayed. The Lung Analysis Software requires the user to identify a nodule and to determine whether it is a GGO or solid nodule in order to use the appropriate characterization too. | | | | | | AVIEW | | | | | | The AVIEW is a software product which can be installed on a PC. It sh…

AVIEW LCS

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