(265 days)
K220727 – inHEART MODELS, inHEART
Not Found
Yes
The device description explicitly states that the "inHEART MODELS AI" module uses a "machine-learning based approach" and details the training process, including the algorithm (UNet) and training data.
No
Explanation: The device is a medical imaging software intended to aid qualified medical professionals in reading, interpreting, and treatment planning. It does not directly provide therapy or treatment.
Yes
The Intended Use/Indications for Use states that the software provides "tools to aid them [medical professionals] in reading, interpreting, and treatment planning." The "reading" and "interpreting" aspects indicate its use in understanding a patient's condition, which aligns with the definition of a diagnostic device. While it also aids in "treatment planning," the core function involves deriving insights from medical images for clinical assessment.
Yes
The device is described as a "suite of medical image processing software tools" and explicitly states it is composed of "three software as a medical device components". While it processes images from hardware devices (CT and MR), the device itself is the software.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs are used to examine specimens derived from the human body. The intended use and device description clearly state that inHEART MODELS processes medical images (CT and MR) acquired from imaging devices. It does not analyze biological samples like blood, urine, or tissue.
- The purpose of this device is image processing and visualization for treatment planning. The software aids qualified medical professionals in reading, interpreting, and planning treatment based on anatomical structures visualized from medical images. This is distinct from the diagnostic purpose of an IVD, which is to provide information about a patient's health status based on in vitro testing.
The device falls under the category of medical image processing software, which is a different type of medical device than an IVD.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The 'Control Plan Authorized (PCCP) and relevant text' section is marked as "Not Found".
Intended Use / Indications for Use
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, and treatment planning, inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models AI software module is indicated for adults only and is designed for CT images only.
CONTRAINDICATIONS:
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
Product codes (comma separated list FDA assigned to the subject device)
QIH, LLZ
Device Description
inHEART MODELS is a suite of medical image processing software tools that enables 3D visualization and analysis of anatomical structures.
This software suite is composed of three software as a medical device components:
-
. inHEART MODELS AI: a medical image processing software for automatic 3D modelling, used to pre-process medical images (acquired only by CT devices).
This software module uses a machine-learning based approach with the following characteristics: -
Training dataset: 796 cases (3D CT original images and the segmentation । masks) from previously manually performed segmentations (time period 2018-2022); origins of the data are public and private clinical and hospital institutions located in US (40%) and Europe (60%).
-
-Training process: Machine learning algorithm (UNet) is trained applying data augmentation (including patch mirroring) and regularization (including Instance Normalization, Dropout, Data Augmentation, Weight Initialization, Leaky ReLU Activation) methods. Loss functions (soft dice loss and binary cross entropy) and optimization methods (stochastic gradient descent) are used during learning over a fixed number of 1000 epochs, each consisting of 250 iterations with a batch size of 2.
-
Data anonymized prior to its processing by inHEART team, therefore no । personal data (gender, age, ethnicity) is exploitable. CT scanner manufacturers include Siemens (40%). GE Medical Systems (30%). Toshiba (10%) and other manufacturers (20%) among which Philips and Canon.
-
inHEART MODELS Shaper: a standalone image processing software used to . generate digital 3D models of the patient heart from medical images acquired by CT and/or MR devices and;
-
inHEART MODELS Explorer: a web-based 3D visualization software that permits . display, review, analysis, annotation and export of the cardiac 3D models generated from inHEART MODELS Shaper.
Specifically, these software modules read DICOM compatible pre-operative CT and MR images acquired by commercially available imaging devices. These images are then processed to generate 3D models of the anatomy to allow qualified medical professionals to display, review, analyze, annotate, interpret, export, and plan therapeutic interventions.
inHEART MODELS software suite also includes two non-device Medical Device Data Systems (MDDS) modules that are only intended to transfer, store and convert formats.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT and MR
Anatomical Site
Heart (cardiac 3D models)
Indicated Patient Age Range
Adults only
Intended User / Care Setting
Qualified medical professionals (including physicians, cardiologists, radiologists, and technicians)
Description of the training set, sample size, data source, and annotation protocol
Training dataset: 796 cases (3D CT original images and the segmentation masks) from previously manually performed segmentations (time period 2018-2022); origins of the data are public and private clinical and hospital institutions located in US (40%) and Europe (60%).
Training process: Machine learning algorithm (UNet) is trained applying data augmentation (including patch mirroring) and regularization (including Instance Normalization, Dropout, Data Augmentation, Weight Initialization, Leaky ReLU Activation) methods. Loss functions (soft dice loss and binary cross entropy) and optimization methods (stochastic gradient descent) are used during learning over a fixed number of 1000 epochs, each consisting of 250 iterations with a batch size of 2.
Data anonymized prior to its processing by inHEART team, therefore no personal data (gender, age, ethnicity) is exploitable. CT scanner manufacturers include Siemens (40%). GE Medical Systems (30%). Toshiba (10%) and other manufacturers (20%) among which Philips and Canon.
Description of the test set, sample size, data source, and annotation protocol
Testing dataset: 100 CT cases were randomly selected on the time period year -2023 to ensure independence of training/testing datasets; the sources are similar to the training dataset including new clients. In order to use this as a ground truth, two external experts evaluated the concordance of the manual segmentations for the task in which the use of this software is inscribed.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
The study consists in the following steps:
- Approval by external experts (radiologists) of segmentations previously obtained with the predicate device, that will constitute the Ground Truth (GT)
- Comparison of unprocessed outputs of the new automated software module results with the GT to establish the internal validation of the tool performance
- Comparison of new automated software module segmentations after their review and edition by expert users using predicate device with the GT validated in step 1 to establish substantial equivalence to the predicate and proposed device.
Sample size: 100 CT cases
Key results: Average Dice score is 0.94, average ASSD is 1.17mm, average volume variations is 9,18mL and 7%.
All validation criteria were met, and the performance evaluation study demonstrated that output segmentations and measurements on these segmentations for inHEART MODELS were substantially equivalent to previously cleared legally marketed software devices.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Dice coefficient, Average Symmetric Surface Distance (ASSD), volumetric analysis
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
K220727 – inHEART MODELS, inHEART
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
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, 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.
inHEART, SAS Audrey Labeque Quality and Regulatory Affairs Manager IHU LIryc - Hôpital Xavier Arnozan-Avenue du Haut Lévêque Pessac. 33600 France
February 29, 2024
Re: K231683 Trade/Device Name: inHEART Models Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QIH, LLZ Dated: January 25, 2024 Received: January 25, 2024
Dear Audrey Labeque:
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 (the 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 available 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.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
1
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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.
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
2
Indications for Use
510(k) Number (if known) K231683
Device Name inHEART MODELS
Indications for Use (Describe)
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, and treatment planning, inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models AI software module is indicated for adults only and is designed for CT images only.
CONTRAINDICATIONS:
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
| Type of Use (Select one or both, as applicable) |
|---|
| ------------------------------------------------- |
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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3
Image /page/3/Picture/0 description: The image shows the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is a gradient of blue and white, and the word "inHEART" is in a light blue sans-serif font. The "E" in HEART is stylized with three horizontal lines.
K231683
510(k) Premarket Notification inHEART MODELS
510(k) Summary
| Submitter's Name: | inHEART, SAS |
|---|---|
| Address: | IHU Liryc – Hôpital Xavier Arnozan |
| Avenue du Haut Lévêque | |
| 33600 Pessac, France | |
| Contact: | |
| Telephone: | |
| Fax: | Audrey Labèque, Quality and Regulatory Affairs Manager |
| +33 5 35 38 19 72 | |
| +33 5 57 10 28 86 | |
| Date: | February 29, 2024 |
| Trade Name: | inHEART MODELS |
| Model No: | N/A |
| Regulation Description: | Medical Image Management and Processing System |
| Regulation number: | 21 CFR 892.2050 |
| Product Code: | Primary product code : QIH |
| Secondary product code : LLZ | |
| Regulatory Class: | Class II |
| Predicate Device: | K220727 – inHEART MODELS, inHEART |
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Image /page/4/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, and is positioned to the right of the heart shape.
1. Device Description
inHEART MODELS is a suite of medical image processing software tools that enables 3D visualization and analysis of anatomical structures.
This software suite is composed of three software as a medical device components:
-
. inHEART MODELS AI: a medical image processing software for automatic 3D modelling, used to pre-process medical images (acquired only by CT devices).
This software module uses a machine-learning based approach with the following characteristics: -
Training dataset: 796 cases (3D CT original images and the segmentation । masks) from previously manually performed segmentations (time period 2018-2022); origins of the data are public and private clinical and hospital institutions located in US (40%) and Europe (60%).
-
-Training process: Machine learning algorithm (UNet) is trained applying data augmentation (including patch mirroring) and regularization (including Instance Normalization, Dropout, Data Augmentation, Weight Initialization, Leaky ReLU Activation) methods. Loss functions (soft dice loss and binary cross entropy) and optimization methods (stochastic gradient descent) are used during learning over a fixed number of 1000 epochs, each consisting of 250 iterations with a batch size of 2.
-
Data anonymized prior to its processing by inHEART team, therefore no । personal data (gender, age, ethnicity) is exploitable. CT scanner manufacturers include Siemens (40%). GE Medical Systems (30%). Toshiba (10%) and other manufacturers (20%) among which Philips and Canon.
-
inHEART MODELS Shaper: a standalone image processing software used to . generate digital 3D models of the patient heart from medical images acquired by CT and/or MR devices and;
-
inHEART MODELS Explorer: a web-based 3D visualization software that permits . display, review, analysis, annotation and export of the cardiac 3D models generated from inHEART MODELS Shaper.
Specifically, these software modules read DICOM compatible pre-operative CT and MR images acquired by commercially available imaging devices. These images are then processed to generate 3D models of the anatomy to allow qualified medical professionals to display, review, analyze, annotate, interpret, export, and plan therapeutic interventions.
inHEART MODELS software suite also includes two non-device Medical Device Data Systems (MDDS) modules that are only intended to transfer, store and convert formats.
5
Image /page/5/Picture/0 description: The image contains the logo for "inHEART". The logo consists of a stylized heart shape on the left, rendered in shades of blue, with the word "inHEART" to the right of the heart shape. The text is also in shades of blue, matching the color scheme of the heart shape.
inHEART MODELS complies with the following standards:
- ISO, 14971 Third Edition 2019-12, Medical devices - Application of Risk Management to medical devices
- ISO, 15223-1 Third Edition 2016-11-01, Medical devices Symbols to be used ● with information to be supplied by the manufacturer - Part 1: General requirements
- IEC, 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION: Medical device ● software - Software life cycle processes
- . IEC, 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION: Medical devices - Part 1 : application of usability engineering to medical devices
- IEC, /TR 80002-1 Edition 1.0 2009-09, Medical device software Part 1 : ● Guidance of the application of ISO 14971 to medical devices
- IEC, 82304-1 Edition 1.0 2016-10, Health software Part 1 : General . requirements for product safety
- IEC 81001-5-1 Edition 1.0 2021-12, Health software and health IT systems . safety, effectiveness and security - Part 5-1 Security - Activities in the product life cycle
2. Indications for Use
inHEART MODELS comprises a suite of medical imaging software modules that are intended to provide qualified medical professionals with tools to aid them in reading, interpreting, reporting, and treatment planning. inHEART MODELS accepts DICOM compliant medical images acquired from a variety of imaging devices, including CT and MR*. The software is designed to be used by qualified medical professionals (including physicians, cardiologists, radiologists, and technicians) and the users are solely responsible for making all final patient management decisions.
- inHEART Models Al software module is indicated for adults only and is designed for CT images only.
CONTRAINDICATIONS:
This product is not intended for use with or for the primary diagnostic interpretation of Mammography images.
6
Image /page/6/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, with the "in" slightly darker than the "HEART".
3. Comparison of technological characteristics with the predicate device
| Technological
characteristics | inHEART MODELS
(this submission) | inHEART MODELS
(K220727)
Predicate |
|----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Basic imaging tools | | |
| Processing tools | | |
| Filtering tools | Yes | Yes |
| Reformat tools | Yes | Yes |
| Meshing tools | Yes | Yes |
| Registration tools | Yes | Yes |
| Visualization tools | | |
| 2D viewer | Yes | Yes |
| 3D viewer | Yes | Yes |
| Export capabilities | Yes | Yes |
| Reporting of results | Yes | Yes |
| Advanced imaging tools | | |
| Segmentation | Yes
(manually, semi-automated and
fully automated
some segmentations are
automated using the new
software module "inHEART
Models Al") | Yes
(manually and semi-
automated) |
| Quantitative analysis | Yes | Yes |
| Product characteristics | | |
| Mode of operation | Standalone and web-based
software suite | Standalone and web-based
software suite |
| Operating system | macOS for imaging processing
software module
Windows or macOS for web-
based platform and compatible
with following browser: Google
Chrome, Apple Safari (for
macOS), Microsoft Edge (for
Windows) | macOS for imaging
processing software module
Windows or macOS for
web-based platform and
compatible with following
browser: Google Chrome,
Apple Safari (for macOS),
Microsoft Edge (for
Windows) |
| IT network | A standard internet connection is
needed for the web-based
platform. | A standard internet
connection is needed for the
web-based platform. |
| Input data | DICOM compliant medical
images acquired from a variety of
imaging devices including, CT,
MR | DICOM compliant medical
images acquired from a
variety of imaging devices
including CT MB |
Table 1 Device Features and Technical Characteristic comparison matrix
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Image /page/7/Picture/0 description: The image shows a logo with a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is composed of two overlapping sections, with the left section being a lighter shade of blue and the right section being a darker shade of blue. The word "inHEART" is written in a sans-serif font, with each letter being a slightly different shade of blue.
The following technological differences exist between the subject and predicate device:
- The predicate uses a combination of manual and semi-automated processing . and segmentation. The proposed device uses fully automated reformatting (reslice tool) and segmentation steps using a new software module "inHEART MODELS AI", followed by review and additional manual and semi-automated processing and segmentation through existing and already cleared software module "inHEART MODELS Shaper".
The original processing and updated processing sequences have been validated to demonstrate that the outputs are substantially equivalent.
The indications for Use statement for the subject and predicate devices is similar.
4. Performance data and assessment
The following performance data were provided in support of the substantial equivalence determination:
Software verification and validation testing were conducted on all ● inHEART MODELS software modules and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices."
inHEART MODELS was considered as a "moderate" level of concern.
In addition, accuracy of segmentations for inHEART MODELS was . compared to ground truth and to predicate device inHEART MODELS (K220727). In this study, the ability of the new automated software module was assessed to perform initial segmentations of medical images that, in conjunction with predicate device, allow to produce results comparable to what is obtained using FDAapproved predicate device alone.
The study consists in the following steps:
- Approval by external experts (radiologists) of segmentations previously obtained with the predicate device, that will constitute the Ground Truth (GT) 2. Comparison of unprocessed outputs of the new automated software module results with the GT to establish the internal validation of the tool performance 3. Comparison of new automated software module segmentations after their review and edition by expert users using predicate device with the GT validated in step 1 to establish substantial equivalence to the predicate and proposed device.
Details about this performance validation study:
- Testing dataset: 100 CT cases were randomly selected on the time period year -2023 to ensure independence of training/testing datasets; the sources are similar to the training dataset including new clients. In order to use this as a ground truth, two external experts evaluated the concordance of the manual segmentations for the task in which the use of this software is inscribed.
- Testing criteria: since the objective is to provide the expert segmenter with an initialization of the segmentation required for producing the 3D models, the
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Image /page/8/Picture/0 description: The image contains the logo for inHEART. The logo consists of a stylized heart shape on the left and the word "inHEART" on the right. The heart shape is rendered in shades of blue, with a gradient effect that gives it a three-dimensional appearance. The word "inHEART" is written in a sans-serif font, also in shades of blue, and is positioned to the right of the heart shape.
criteria used for performance are Dice coefficient (>0.9 for acceptance without manual correction), Average Symmetric Surface Distance (ASSD) (