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Medical Data Annotation Services

Build reliable training datasets for healthcare AI with expert medical data annotation. We annotate medical images, DICOM and NIfTI scans, clinical text, surgical videos and multimodal healthcare data using project-specific guidelines, secure workflows and rigorous quality control.

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Anatomical medical imaging of brain dissection with surgical instruments

🧵 Medical annotation tailored to your use case

Precise medical annotations, adapted to your use cases, formats (DICOM, NifTI, HL7, etc.) and clinical requirements. Ideal for training your health AI models. In the healthcare sector, medical data labeling requires absolute accuracy to support accurate diagnosis and avoid misdiagnosis.

Structure My Medical Data for AI models

🥇 Medical domain expertise

Build a project team combining trained medical data annotators with relevant domain specialists. We support complex requirements involving anatomy, radiology, pathology, medical terminology and clinical documentation.

Build My Medical Annotation Team

🧬 Annotate complexity

Neurosurgery, pathology, clinical reports: our experts know how to annotate rich and sensitive medical data, whether it is images, videos or specialized texts. Protect sensitive medical data through controlled access, confidentiality measures and appropriate anonymization requirements.

Entrust My Complex Cases to Specialists

Medical Data Annotation for Healthcare

Chest CT scan showing lung anatomy with red highlighted region

Bounding Boxes (or boundary boxes) in medical image annotation

In medical annotation, “Bounding Boxes” make it possible to precisely locate anatomical structures, anomalies or instruments on medical images, in order to prepare datasets 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

Hand with medical data annotation (polygon)

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

Dental X-ray showing lower implant measurements and severe bone loss

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:

Body joint annotation for posture analysis, motion tracking, or detection of biomechanical abnormalities

Precise facial landmarking (eyes, nose, mouth) for facial recognition or emotion analysis

Dental keypoint annotation (crown, gum, root) for 3D modeling, orthodontic planning, or computer-assisted surgery

CT scan showing a red-highlighted tumor in the abdomen

Free contours

Free 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:

Manual delineation of irregular tumors or lesions on MRI or CT scans for precise clinical monitoring

Fine segmentation of soft tissues or complex organs (brain, liver, lungs) with non-standard shapes

Detailed annotation of wounds, burns, or pathological skin areas in dermatological imaging

Chest X-ray showing lungs with red outline and potential dark area highlighted

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:

Precise annotation of vascular networks (arteries, veins, capillaries) on angiographic images for blood flow analysis

Tracing of nerves or muscle fibers in MRI scans for neurological or surgical studies

Delineation of branched structures in lungs or bronchi for respiratory anomaly detection

3D brain scans showing anatomical views from different perspectives

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:

3D segmentation of brain tumors on MRI scans for surgical planning or radiotherapy preparation

Volumetric reconstruction of the heart or lungs from CT scans for functional and morphological analysis

3D annotation of internal organs (liver, kidneys, pancreas) to create anatomical models for medical AI training

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, CT scans, or MRIs to identify anomalies (tumors, nodules, lesions) via specific areas. Bounding Boxes are applied to imaging data such as CT scans and radiographs, supporting medical applications and medical technology while improving diagnostic accuracy through healthcare innovation.

📦 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 for Healthcare AI

Annotations of x-rays, scanners, and MRIs associated with their radiological reports help train machine learning algorithms for medical applications, support medical ai development, and improve diagnostic accuracy through natural language processing that links images with clinical notes, medical documentation, and insights used by healthcare professionals.

📦 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.

3/3

📋 Extracting information from electronic medical records (EMRs) using data annotation

Annotating unstructured medical documents for Medical AI Development, combining imaging with Natural Language Processing to train an NLP model to identify entities in radiological reports, clinical notes, electronic health records, patient records, and pathology reports, such as diagnoses, treatments, dosages, histories, and fields used in medical coding.

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

Chest X-ray series showing progression of lung imaging techniques

Why choose Innovatiana for Medical Data Annotation?

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, and adapt to your existing FDA-compliant data labeling workflow.

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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.

Turn Complex Medical Data Into Reliable AI Training Data!

👉 Request a Free Quote
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