(142 days)
No
The description mentions "Magic cut (based on Randomwalk algorithm)", which is a traditional image processing algorithm, not typically considered AI/ML in the context of modern deep learning or machine learning techniques. The rest of the description focuses on standard image processing, segmentation, and mesh manipulation tools. There is no mention of training data, models, or performance metrics commonly associated with AI/ML devices.
No.
The device is used for image review, segmentation, and pre-operative surgical planning, with 3D printed models for visualization and educational purposes only, and not for diagnosis or treatment. This indicates it is a diagnostic/planning tool, not a therapeutic one.
No
The "Intended Use / Indications for Use" section explicitly states that "3D printed models generated from the output file are for visualization and educational purposes only and not for diagnostic use." While the system processes DICOM images and is used for surgical planning, its final output, which could be considered the ultimate result for diagnostic purposes, is excluded from diagnostic use.
Yes
The device description explicitly states "The AVIEW Modeler is a software product which can be installed on a separate PC". While it interacts with DICOM data from medical scanners and its output can be used for 3D printing (which involves hardware), the device itself, as described, is the software running on a general-purpose computer. The performance studies focus on software testing (unit, system, performance, compatibility) and do not describe any hardware components of the device itself.
Based on the provided information, the AVIEW Modeler is likely considered an IVD (In Vitro Diagnostic) device, although it's not a traditional IVD in the sense of analyzing biological samples. Here's why:
- Intended Use: The primary intended use is "as an image review and segmentation system that operates on DICOM imaging information obtained from a medical scanner." While it also mentions surgical planning and visualization/educational models, the core function is processing medical images for review and segmentation.
- Device Description: It's a software product that displays and allows manipulation of patient medical images from an acquisition device. This aligns with the processing and analysis of medical data.
- Input Imaging Modality: It uses DICOM data from medical scanners (CT or MRI). This is the "specimen" or "sample" in this context – the medical image data.
- Image Processing: It explicitly mentions various image processing functions like MPR, rendering, segmentation methods, morphological operations, etc. This is the "in vitro" part – processing data outside the body.
- Predicate Device: The predicate device, K161841 (D2P by 3D Systems, Inc.), is also a software for processing medical images and generating 3D models. This suggests a similar regulatory classification.
However, it's important to note the nuance:
- Not a traditional IVD: It doesn't analyze biological fluids or tissues in the typical laboratory setting.
- Focus on Image Data: The "in vitro" aspect is the processing of the digital image data.
- Exclusion of Diagnostic Use for 3D Models: The statement that 3D printed models are "for visualization and educational purposes only and not for diagnostic use" is a key distinction. This limits the diagnostic claim to the software's image review and segmentation capabilities, not the physical models.
In summary:
While not a traditional IVD, the AVIEW Modeler fits the definition of an IVD because it is a device intended for use in the examination of specimens (medical image data) derived from the human body for the purpose of providing information for medical diagnosis. The fact that the 3D models are not for diagnostic use doesn't negate the IVD classification of the software's image processing and review functions.
The regulatory classification of such software can be complex and depends on the specific claims and intended use. However, based on the provided information, it strongly points towards an IVD classification, likely under a category related to medical image processing and analysis software.
N/A
Intended Use / Indications for Use
The AVIEW Modeler is intended for use as an image review and segmentation system that operates on DICOM imaging information obtained from a medical scanner. It is also used as a pre-operative software for surgical planning. 3D printed models generated from the output file are for visualization and educational purposes only and not for diagnostic use.
Product codes
LLZ
Device Description
The AVIEW Modeler is a software product which can be installed on a separate PC, it displays patient medical images on the screen by acquiring it from image Acquisition Device. The image on the screen can be checked edited, saved and received.
- -Various displaying functions
- Thickness MPR., oblique MPR, shaded volume rendering and shaded surface rendering.
- . Hybrid rendering of simultaneous volume-rendering and surface-rendering.
- -Provides easy to-use manual and semi-automatic segmentation methods
- Brush, paint-bucket, sculpting, thresholding and region growing. "
- . Magic cut (based on Randomwalk algorithm)
- -Morphological and Boolean operations for mask generation.
- Mesh generation and manipulation algorithms. -
- Mesh smoothing, cutting, fixing and Boolean operations.
- -Exports 3d-printable models in open formats, such as STL.
- DICOM 3.0 compliant (C-STORE, C-FIND) -
Mentions image processing
Yes
Mentions AI, DNN, or ML
Not Found
Input Imaging Modality
DICOM imaging information obtained from a medical scanner.
Anatomical Site
Not Found
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Not Found
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Verification, validation and testing activities were conducted to establish the performance, functionality and reliability characteristics of the modified device passed all of the tests based on pre-determined Pass/Fail criteria.
- Unit test: Conducting Unit Test using Google C++ Unit Test Framework on major software components identified by software development team. List of Unit Test includes Functional test condition for software component unit, Performance test condition, and part of algorithm analysis for image processing algorithm.
- System test: In accordance with the document 'integration Test Cases' discussed in advanced by software development team and test team, test is conducted by installing software to hardware with recommended system specification. Despite Test case recognized in advance was not in existence. New software error discovered by 'Exploratory Test' conducted by test team will be registered and managed as new test case after discussion between development team and test team. Discovered software error will be classified into 3 categories as severity and managed. Major defects, which are impacting the product's intended use and no workaround is available. Moderate defects, which are typically related to user-interface or general quality of product, while workaround is available. Minor defects, which aren't impacting the product's intended use. Not significant. Success standard of System Test is not finding 'Major'. 'Moderate' defect.
- Performance test: In order to check whether the non-functional requirement indicated in section 'Performance and Non-Functional Requirements is satisfied, operate a test according to the performance evaluation standard and method that has been determined with prior consultation between software development team and testing team.
- Compatibility test: All 3D printer software's should validate imported STL file before 3D printing. STL data which is created by AVIEW Modeler imported into Stratasys printing Software, Object Studio to validate the STL before 3d-printing with Objet260 Connex3. (data compatibility between two software's).
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2050 Medical image management and processing system.
(a)
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.(b)
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).
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, with the letters "FDA" in a blue box, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue. The words "FOOD & DRUG" are larger than the other words.
December 20, 2019
Coreline Soft Co., Ltd. % Hyeyi Park Deputy General Manager/ Strategic Business Dept. 4, 5F (Yeonnam-dong), 49, World Cup buk-ro 6-gil, Mapo-gu Seoul, 03991 KOREA
Re: K192040
Trade/Device Name: AVIEW Modeler Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: October 25, 2019 Received: November 26, 2019
Dear Hyeyi 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 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-reporting
1
combination-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 medical devices and radiation-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) K192040
Device Name AVIEW Modeler
Indications for Use (Describe)
The AVIEW Modeler is intended for use as an image review and segmentation system that operates on DICOM imaging information obtained from a medical scanner. It is also used as a pre-operative software for surgical planning. 3D printed models generated from the output file are for visualization and educational purposes only and not for diagnostic use.
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.
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*DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW! *
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FORM FDA 3881 (7/17)
3
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: July 30.2019
DEVICE 2
Name of Device: AVIEW Modeler Common or Usual Name: AVIEW Modeler Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ
PREDICATE DEVICE 3
D2P by 3D Systems, Inc. (K161841) This predicate has not been subject to a design-related recall
REFERENCE DEVICE 4
Mimics inPrint by Materialise N.V. (K173619) AVIEW by Coreline Soft Co., Ltd. (K171199) This reference device has not been subject to a design-related recall
5 DEVICE DESCRIPTION
The AVIEW Modeler is a software product which can be installed on a separate PC, it displays patient medical images on the screen by acquiring it from image Acquisition Device. The image on the screen can be checked edited, saved and received.
- -Various displaying functions
- Thickness MPR., oblique MPR, shaded volume rendering and shaded surface rendering.
- . Hybrid rendering of simultaneous volume-rendering and surface-rendering.
- -Provides easy to-use manual and semi-automatic segmentation methods
- Brush, paint-bucket, sculpting, thresholding and region growing. "
- . Magic cut (based on Randomwalk algorithm)
4
- -Morphological and Boolean operations for mask generation.
- Mesh generation and manipulation algorithms. -
- Mesh smoothing, cutting, fixing and Boolean operations.
- -Exports 3d-printable models in open formats, such as STL.
- DICOM 3.0 compliant (C-STORE, C-FIND) -
INDICATIONS FOR USE 6
The AVIEW Modeler is intended for use as an image review and segmentation system that operates on DICOM imaging information obtained from a medical scanner. It is also used as a pre-operative software for surgical planning.
3D printed models generated from the output file are for visualization and educational purposes only and not for diagnostic use.
COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 7 THE PREDICATE DEVCIE
AVIEW Modeler has the same intended use and principle of operation, and also has similar features to the predicate devices, D2P(K161841)
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 Modeler | D2P | Mimics inPrint | 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 | LLZ | LLZ | LLZ |
| Review Panel | Radiology | Radiology | Radiology | Radiology |
| 510k Number | - | K161841 | K173619 | K171199 |
| Indications for | ||||
| use | The AVIEW Modeler | |||
| is intended for use as a | ||||
| software interface and | ||||
| image segmentation | ||||
| system that send | ||||
| DICOM imaging | ||||
| information through | ||||
| output file on a | ||||
| medical scanner. 3D | ||||
| model and 3D printed | ||||
| models generated by | ||||
| our software can also | The D2P Software is | |||
| intended for use as a | ||||
| software interface and | ||||
| image segmentation | ||||
| system for the transfer | ||||
| of imaging | ||||
| information from a | ||||
| medical scanner such | ||||
| as a CT scanner to an | ||||
| output file it is also | ||||
| intended as pre- | ||||
| operative software for | Mimics inPrint is | |||
| intended for use as a | ||||
| software interface and | ||||
| image segmentation | ||||
| system for the | ||||
| transfer of DICOM | ||||
| imaging information | ||||
| from a medical | ||||
| scanner to an output | ||||
| file it is also used as | ||||
| pre-operative | ||||
| software for treatment | 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 | ||||
| be used for a surgical | ||||
| plan and simulation | ||||
| use. | surgical planning. 3D | |||
| printed models | ||||
| generated from the | ||||
| output file are meant | ||||
| for visual, non- | ||||
| diagnostic use. | planning for this | |||
| purpose, the Mimics | ||||
| output file can be | ||||
| used for the | ||||
| fabrication of | ||||
| physical replicas of | ||||
| the output file using | ||||
| traditional or additive | ||||
| manufacturing | ||||
| methods. | 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 | IBM-compatible PC | |||
| or PC network | ||||
| User Interface | Monitor, Mouse, | |||
| Keyboard | 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 | Images can be | |||
| scanned, loaded from | ||||
| card readers, or | ||||
| imported from a | ||||
| radiographic imaging | ||||
| device | ||||
| 32bit/64bit | 64bit | 64bit | 32t/4bit | 64bit |
| Image format | DICOM | DICOM | DICOM | DICOM |
| Image viewing | Axial, sagittal, and | |||
| coronal image, | ||||
| oblique slice, 3D | Axial, sagittal and | |||
| coronal images, | ||||
| oblique slice, 3D | Axial, sagittal and | |||
| coronal images, | ||||
| oblique slice, 3D | Axial, sagittal and | |||
| coronal images, | ||||
| oblique slice, cube | ||||
| view, 3D | ||||
| Image | ||||
| manipulation | Panning, rotating, | |||
| zooming, windowing, | ||||
| Coloring, Oblique, | ||||
| Note (text overlay), | ||||
| Coloring (volume of | ||||
| interest overlay) | Panning, rotating, | |||
| zooming, windowing, | ||||
| region of interest | ||||
| overlay (ROI) | Panning, rotating, | |||
| zooming, windowing, | ||||
| region of interest | ||||
| overlay (ROI) | Panning, rotating, | |||
| zooming, windowing, | ||||
| inverting, Coloring, | ||||
| Oblique, Note (text | ||||
| overlay), Coloring | ||||
| (volume of interest | ||||
| overlay) | ||||
| General | ||||
| Description | The AVIEW Modeler | |||
| is a software product | ||||
| which can be installed | ||||
| on a separate PC, it | ||||
| displays patient | ||||
| medical images on the | ||||
| screen by acquiring it | ||||
| from Image | ||||
| Acquisition Device. | ||||
| The image on the | ||||
| screen can be checked | ||||
| edited, saved and | The D2P software is a | |||
| stand-alone modular | ||||
| software package that | ||||
| allows easy to use and | ||||
| quick digital 3D | ||||
| model preparation for | ||||
| printing or use by | ||||
| third party | ||||
| applications. The | ||||
| software is aimed at | ||||
| usage by medical | ||||
| staff, technicians, | Materialise's | |||
| Interactive Medical | ||||
| image Control | ||||
| System (mimics) is a | ||||
| software tool for | ||||
| visualizing and | ||||
| segmenting medical | ||||
| images (such as CT | ||||
| and MRI) and | ||||
| rendering 3D objects. | ||||
| Mimics inPrint may | ||||
| be used as a medical | The AVIEW is a | |||
| software product | ||||
| which can be installed | ||||
| on a PC. It shows | ||||
| images taken with the | ||||
| interface from various | ||||
| storage devices using | ||||
| DICOM 3.0 which is | ||||
| the digital image and | ||||
| communication | ||||
| standard in medicine. | ||||
| It also offers functions | ||||
| received. | nurses, researchers or | |||
| lab technicians thatlab technicians that | ||||
| wish to create patient | ||||
| specific | ||||
| digital | ||||
| anatomical models for | ||||
| variety of uses such as | ||||
| training, education, | ||||
| and pre-operative | ||||
| surgical planning. The | ||||
| patient specific digital | ||||
| anatomical models | ||||
| may be further used as | ||||
| an input to a 3D | ||||
| printer to create | ||||
| physical models for | ||||
| visual, non-diagnostic | ||||
| use. This modular | ||||
| package includes, but | ||||
| is not limited to the | ||||
| following functions: | ||||
| •DICOM viewer and | ||||
| analysis | ||||
| •Automated | ||||
| segmentation | ||||
| •Editing and pre- | ||||
| printing | ||||
| •Seamless | ||||
| integration with 3D | ||||
| Systems printers | ||||
| •Seamless | ||||
| integration with 3D | ||||
| Systems software | ||||
| packages | device. Within the | |||
| limits of the described | ||||
| below intended use | ||||
| statement. | ||||
| Mimics may be used | ||||
| to load and process | ||||
| stack of 2D images | ||||
| from numerous | ||||
| formats including | ||||
| DICOM 3.0 format, | ||||
| BMP, TIFF, JPG and | ||||
| raw images. Once | ||||
| images are processed, | ||||
| they can be used | such as reading. | |||
| Manipulation, | ||||
| analyzing, post- | ||||
| processing, saving and | ||||
| sending images by | ||||
| using the software | ||||
| tools. | ||||
| DICOM | This receives DICOM | |||
| data from CT or MRI | ||||
| by DICOM | ||||
| communication | ||||
| Conducts DICOM | ||||
| data communication | ||||
| with PACS. It also | ||||
| imports DICOM file | ||||
| directly, saves by | ||||
| using export function. | Retrieve image data | |||
| over the network via | ||||
| DICOM | Retrieve image data | |||
| over the network via | ||||
| DICOM | This receives DICOM | |||
| data from CT or MRI | ||||
| by DICOM | ||||
| communication | ||||
| Conducts DICOM | ||||
| data communication | ||||
| with PACS. It also | ||||
| imports DICOM file | ||||
| directly, saves by | ||||
| using export function. | ||||
| 3D Modeling | ||||
| Functions | Providing ray sum | |||
| image, axial, sagittal, | ||||
| coronal, and oblique | ||||
| planes. | ||||
| Rotating to Anterior, | ||||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | Providing axial, | |||
| sagittal, coronal, and | ||||
| oblique planes | ||||
| Rotating to Anterior, | ||||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | Providing axial, | |||
| sagittal, coronal, | ||||
| Rotating to Anterior, | ||||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | Providing ray sum | |||
| image, axial, sagittal, | ||||
| coronal, and oblique | ||||
| planes | ||||
| Rotating to Anterior, | ||||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | ||||
| Providing VR | Providing VR | Providing VR | Providing VR | |
| (Volume render), MIP (Maximum Intensity Projection), MinIP (Minimum Intensity Projection) image | (Volume render) | (Volume render) | (Volume render), MIP (Maximum Intensity Projection), MinIP (Minimum Intensity Projection) image | |
| Changing the color and transparency of the VR image by adjusting the OTF (Opacity Transfer Function) and saving as a preset to easily apply in the VR setting. | Changing the color and transparency of the VR image by adjusting the OTF (Opacity Transfer Function) and saving as a preset to easily apply in the VR setting. | - | Changing the color and transparency of the VR image by adjusting the OTF (Opacity Transfer Function) and saving as a preset to easily apply in the VR setting. | |
| Providing options of ambient, diffuse, specular, gradient, shininess, lighting and transient quality in the Camera setting | - | - | Providing options of ambient, diffuse, specular, gradient, shininess, lighting and transient quality in the Camera setting | |
| Saving the segmented region from the whole volume and converting to the surface model | Saving the segmented region from the whole volume and converting to the surface model | Saving the segmented region from the whole volume and converting to the surface model | - | |
| Saving the surface model in STL format | Saving the surface model in STL format | Saving the surface model in STL format | - | |
| The decimation and smoothing options can be applied when saving in STL format | The fixed decimation and smoothing options can be applied when saving in STL format | The decimation and smoothing options can be applied when saving in STL format | - | |
| Providing a model fixing function that can detect and correct errors on the surface model. | - | Model fixing of Surface model | - | |
| Boolean operation (Union, Subtract, Intersect) and segmentation function between models. | - | Boolean operation (Union, Subtract, Intersect) | - | |
| Creating Box, Sphere, Pipe, or Cone shape surface model | Creating Pipe shape surface model | Creating Box, Sphere, Pipe, or Cone shape surface model | - | |
| AVIEW Modeler provide segmentation function in the CT image. Key Features; Threshold, Region Grow 3D Pick ROI | The D2P provide segmentation function in the CT image. Key Features; Threshold, Brush, (3D) Pick | The Mimics inPrint provide segmentation function in the CT image. Key Features; Threshold, Brush, Lasso, 3D | - |
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7
8
| Draw, Erase, Selective
Brush, (3D) Sculpt &
Paint, (2D,3D) Pick,
Fill hole, Magic
cut(semi-auto) | interpolates,
split(semi-auto),
Combine, Unite,
Intersect, Subtract |
|--------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
| | |
PERFORMANCE DATA 8
Verification, validation and testing activities were conducted to establish the performance, functionality and reliability characteristics of the modified device passed all of the tests based on pre-determined Pass/Fail criteria.
-
-Unit test
Conducting Unit Test using Google C++ Unit Test Framework on major software components identified by software development team. List of Unit Test includes Functional test condition for software component unit, Performance test condition, and part of algorithm analysis for image processing algorithm. -
-System test
In accordance with the document 'integration Test Cases' discussed in advanced by software development team and test team, test is conducted by installing software to hardware with recommended system specification. Despite Test case recognized in advance was not in existence. New software error discovered by 'Exploratory Test' conducted by test team will be registered and managed as new test case after discussion between development team and test team.
Discovered software error will be classified into 3 categories as severity and managed.
-
Major defects, which are impacting the product's intended use and no workaround is available.
- く Moderate defects, which are typically related to user-interface or general quality of product, while workaround is available.
- イ Minor defects, which aren't impacting the product's intended use. Not significant.
Success standard of System Test is not finding 'Major'. 'Moderate' defect.
-
Performance test -
In order to check whether the non-functional requirement indicated in section 'Performance and Non-Functional Requirements is satisfied, operate a test according to the performance evaluation standard and method that has been determined with prior consultation between software development team and testing team -
Compatibility test -
All 3D printer software's should validate imported STL file before 3D printing. STL data which is created by AVIEW Modeler imported into Stratasys printing Software, Object Studio to validate the STL before 3d-printing with Objet260 Connex3. (data compatibility between two software's)
9 CONCLUSIONS
The new device and predicate device are substantially equivalent in the areas of technical characteristics, general functions, application, and intended use. The new device does not introduce a fundamentally new scientific technology, and the nonclinical tests demonstrate that the device is safe and effective. Therefore, it is our opinion that the AVIEW Modeler described in this substantially equivalent to the predicate device