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Medical annotation

Optimize your medical data for AI and diagnostic support. Our medical annotation services guarantee precise structuring in accordance with industry standards (FDA, HIPAA, etc.), providing high-quality datasets to train and improve your specialized artificial intelligence models.

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Image of an AI wave
Background image of medical instruments (maryland dissectors) annotated with bounding boxes

🧵 Customized annotation

Precise medical annotations, adapted to your use cases, formats (DICOM, NiFTI, HL7, etc.) and clinical requirements. Ideal for training your health AI models.

Structuring my medical data for AI models

🥇 Expertise and excellence

Our annotators, from the medical community (doctors, radiologists, health students), combine clinical expertise and mastery of medical data annotation tools.

Building my medical annotation team

🧬 Annotate the demanding

Neurosurgery, pathology, clinical reports: our experts know how to annotate rich and sensitive medical data, whether it is images, videos or specialized texts.

Entrust my complex cases to specialists

Annotation techniques

2d CR scan annotated with a bounding box

Bounding Boxes (or boundary boxes)

In medical annotation, “Bounding Boxes” make it possible to precisely locate anatomical structures, anomalies or instruments on medical images, in order to train AI models.

⚙️ Process steps:

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪 Practical applications:

Radiology - Detection and location of tumors, nodules or fractures on images (MRI, CT, radiographs)

AI-assisted surgery - Real-time identification of surgical instruments in surgical videos

Digital pathology - Framing suspicious areas on scanned slides for histological analysis

2 hand scans annotated with polygons

Polygons

Polygons allow precise delineation of medical structures with irregular shapes — tumors, organs, lesions or bone structures — by following their exact outline on medical images (MRI, CT, etc.).

⚙️ Process steps:

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪 Practical applications:

Annotation of bone structures (vertebrae, joints, fractures) for orthopedic or postural analysis

Precise delineation of tumors on MRIs or scanners, to measure their size and monitor their evolution

Organ segmentation (liver, lungs, heart, etc.) with complex contours, for training diagnostic models

Image of annotated tooth implants

Keypoints

Keypoints are used to mark specific positions on an object or body, such as joints, facial features, or anatomical landmarks. They allow a detailed analysis of shapes, movements or postures.

⚙️ Process steps:

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪 Practical applications:

Autonomous driving: Detection and tracking of vehicles, pedestrians and cyclists

E-commerce: Localization of products for inventory automation

Oversight: Tracking movements in public environments

Contour annotated on a 2d medical scan (mask)

Free contours

The free contours (”Freehand Contours”) allow complex shapes to be manually drawn directly onto an image, with great precision. This method is particularly useful for segmenting irregular structures.

⚙️ Process steps:

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪 Practical applications:

Autonomous driving: Detection and tracking of vehicles, pedestrians and cyclists

E-commerce: Localization of products for inventory automation

Oversight: Tracking movements in public environments

Lungs scan annotated with polylines

Polylines

Polylines are series of connected line segments used to accurately annotate linear or sinuous structures. In particular, they make it possible to follow blood vessels, nerves, or even to delimit complex areas within organs such as the lungs.

⚙️ Process steps;

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪Practical applications:

Autonomous driving: Detection and tracking of vehicles, pedestrians and cyclists

E-commerce: Localization of products for inventory automation

Oversight: Tracking movements in public environments

Images of a brain in 3d and 2d slices extracted from a tool such as 3d slicer

3D Volumes

3D volumes (“3D Volumes”) allow structures to be annotated in volumetric data such as MRIs or scanners, taking into account depth and different sections.

⚙️Process steps:

Identifying objects to be annotated

Precise framing of objects

Category labeling

Validating annotations

🧪Practical applications:

Autonomous driving: Detection and tracking of vehicles, pedestrians and cyclists

E-commerce: Localization of products for inventory automation

Oversight: Tracking movements in public environments

Use cases

Our expertise covers a wide range of AI use cases, regardless of the domain or the complexity of the data. Here are a few examples:

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Analysis of medical images for the detection of pathologies

Annotation of x-rays, scanners or MRIs to identify anomalies (tumors, nodules, lesions) via specific areas.

📦 Dataset: Medical images (DICOM, PNG), annotated in bounding boxes or segmentation, with clinical labels and validation by experts.

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🧠 Training a visual and textual medical assistant

Annotations of medical images associated with their radiological reports to train a multimodal model capable of automatically generating a medical interpretation in natural language.

📦 Dataset: Chest radiographs with associated clinical descriptions, annotations of visible clinical objects (pathological areas, organs) linked to text segments via a system of image-text relationships.

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📋 Extracting information from electronic medical records (EMRs)

Annotating unstructured medical documents (reports, hospital letters) to train an NLP model to automatically identify entities such as diagnoses, treatments, dosages, or histories.

📦 Dataset: Raw medical texts annotated into entities named according to a medical ontology (e.g. diseases, drugs, dates, biological values), with possible standardization to standardized terminologies (UMLS, SNOMED, ICD-10).

Medical annotation of lungs with bounding boxes

Why choose Innovatiana?

Our added value

Extensive technical expertise in data annotation

Specialized teams by sector of activity

Customized solutions according to your needs

Rigorous and documented quality process

State-of-the-art annotation technologies

Measurable results

Boost your model’s accuracy with quality data, for model training and custom fine-tuning

Reduced processing times

Optimizing annotation costs

Increased performance of AI systems

Demonstrable ROI on your projects

Customer engagement

Dedicated support throughout the project

Transparent and regular communication

Continuous adaptation to your needs

Personalized strategic support

Training and technical support

Compatible with
your stack

We use all the data annotation platforms of the market to adapt us to your needs and your most specific requests!

labelboxcvatencord
v7prodigyubiAI
roboflowImage illustrating Label Studio, an annotation platform

Secure data

We pay particular attention to data security and confidentiality. We assess the criticality of the data you want to entrust to us and deploy best information security practices to protect it.

No stack? No prob.

Regardless of your tools, your constraints or your starting point: our mission is to deliver a quality dataset. We choose, integrate or adapt the best annotation software solution to meet your challenges, without technological bias.

Feed your AI models with high-quality, expertly crafted training data!

👉 Ask us for a quote
En cliquant sur "Accepter ", vous acceptez que des cookies soient stockés sur votre appareil afin d'améliorer la navigation sur le site, d'analyser son utilisation et de contribuer à nos efforts de marketing. Consultez notre politique de confidentialité pour plus d'informations.