Medical imaging data labeling services
Jul 6 – Oct 20, 2026Updated Oct 20, 2026
Reviewed by Dimitry Apollonsky
Which brands AI mentions
Mentioned in
ChatGPTChatGPTGoogle AI ModeGoogle AI Mode
Widest split: Med Annotate, 77% on ChatGPT and 23% on Google AI Mode.
- #1tiediMeritChatGPT 68%Google AI Mode 95%
- #1tiedCogitoTechChatGPT 77%Google AI Mode 77%
- #3tiedShaipChatGPT 59%Google AI Mode 68%
- #3tiedMed AnnotateChatGPT 77%Google AI Mode 23%
- #5tiedAngo HubChatGPT 23%Google AI Mode 45%
Questions and answers
Google AI ModeOct 11, 2026
Several specialized data labeling and annotation companies incorporate "
clinician-in-the-loop" or "radiologist-in-the-loop" workflows, employing board-certified radiologists, pathologists, and clinical specialists to ensure diagnostic precision for healthcare AI.Prominent data labeling and curation services that explicitly utilize certified medical specialists and radiologists for medical imaging include:
- Cogito Tech : Utilizes a dedicated Medical AI Innovation Hub featuring multidisciplinary networks of board-certified radiologists, cardiologists, and specialists. They handle complex modalities like X-rays, CT scans, MRIs, and PET scans with HIPAA-compliant and FDA-ready frameworks.
- Doctors in the Loop : Focuses specifically on clinician-annotated medical datasets. Their workflows match specific imaging modalities (such as complex 3D MRI/CT volumes or X-rays) to domain-expert annotators and licensed medical specialists who review and validate the annotations.
- Scale AI (Healthcare Division) : While known as a general enterprise data platform, Scale AI deploys specialized medical annotation workflows utilizing healthcare professionals and adherence to Radiological Society of North America (RSNA) standards for DICOM and radiological imaging data.
Note: For highly regulated diagnostic AI models, it is standard practice to request a pilot project or verify the specific credentials (e.g., ABR board certification or local equivalent) of the reviewing physicians assigned to your data tier.
If you're working on a specific project, let me know:
- What imaging modalities you are using (e.g., 3D CT, MRI, X-ray)
- Whether you need pixel-level semantic segmentation or bounding/classification
I can help you narrow down which service best fits your workflow and compliance requirements (such as HIPAA or FDA readiness).
Sources cited in this answer5
- cogitotech.comMedical Data Annotation and Labeling Services | AI in Healthcare
- doctorsintheloop.comMedical AI Data Annotation | Doctors in the Loop
- cogitotech.comGenerative AI in Radiology | Radiology Image Annotation
- medical-innovation-hub.cogitotech.comMedical AI Innovation Hub for Data Annotation | Cogito Tech
- cogitotech.comMedical Image Annotation and Labeling Services for AI & ML
ChatGPTOct 11, 2026
Several companies offer medical imaging data annotation with radiologists or other qualified medical specialists involved in labeling, validation, and quality assurance. The key distinction is whether board-certified radiologists personally create or validate the annotations, rather than general annotators simply following medical guidelines.
Based on publicly available service descriptions, these are the strongest candidates to investigate.
Leading data labeling services with radiologist expertise
1. Cogito Tech
(Board-certified radiologists)
Offers medical image annotation for X-rays, CT, MRI, and other healthcare data. Its published service description specifically identifies board-certified radiologists who benchmark labels and supervise medically trained annotators and auditors.
Best for: Enterprise-scale annotation and medically supervised quality assurance.
2. Medcase
Provides medical imaging annotation for CT, MRI, X-rays, and ultrasound. It matches projects to clinicians by specialty and subspecialty, and explicitly describes access to US board-certified radiologists for suitable imaging projects.
Best for: Access to specialty-matched clinicians and radiologists for clinical ground truth.
3. Graid
Provides radiologist-validated imaging datasets, with a European radiologist network offering single-reader, double-reader, and adjudicated reference standards for X-ray, CT, and MRI.
Best for: Clinical ground-truth datasets and multi-reader validation.
4. IngeData
Provides medical imaging annotation with radiologists and other medical specialists involved in protocol definition, annotation, and quality review. Its published examples include CT annotation and breast cancer imaging work.
Best for: Custom imaging projects requiring specialist-led workflows and ongoing quality control.
5. Radinate
Founded by radiologists, physicians, engineers, and technologists. Its published description says board-certified radiologists oversee annotation and quality assurance, including workflows that combine AI-assisted pre-labeling with expert review.
Best for: Radiologist-supervised annotation and AI-assisted labeling workflows.
Additional providers worth evaluating
6. Skillora Experts
Supplies credential-verified radiologists for imaging AI training data, segmentation, ground-truth creation, and model evaluation. It describes verification against official medical registers and calibration using reference cases.
7. HUMXN
Offers radiologist-created imaging labels, segmentations, report annotations, and model evaluations, with credential checks, provenance tracking, and second-reader review.
8. LabelCore.AI
Advertises subspecialty-matched radiologists for CT, MRI, X-ray, ultrasound, PET, and mammography, with DICOM-native annotation and physician-review options. Confirm the applicable credentialing standard and staffing arrangements directly.
9. Softuvo
Offers CT and MRI segmentation, detection, classification, and report structuring. Its published workflow describes independent reads, radiologist adjudication, and batch-level agreement metrics.
10. MedAnnotate
Provides radiology annotation supervised by consultant radiologists and medical imaging specialists, covering CT, MRI, X-ray, ultrasound, and DICOM datasets. Its service description also mentions specialist review for quality assurance.
Which providers should you shortlist first?
Your requirement Start with Explicit board-certified radiologist involvement Cogito Tech, Medcase, Radinate Verified radiologist credentials and subspecialty matching Skillora Experts, Medcase, HUMXN Double reading and adjudicated ground truth Graid, Softuvo DICOM workflows and detailed CT/MRI segmentation LabelCore.AI, Softuvo, MedAnnotate Larger managed annotation operations Cogito Tech, IngeData These are preliminary matches based on vendors' published descriptions, not independent audits of their staffing or credentials.
Questions to ask before selecting a vendor
A vendor saying it employs medical experts does not necessarily mean every image is labeled by a board-certified radiologist. Ask for written confirmation of:
- Credentials: Are the actual annotators board-certified radiologists, licensed radiologists in another jurisdiction, radiology trainees, or radiologic technologists?
- Responsibility: Do radiologists create each label, review a sample, or adjudicate disagreements only?
- Subspecialty: Can you request neuroradiologists, breast imagers, musculoskeletal radiologists, or thoracic radiologists?
- Quality metrics: Will you receive inter-reader agreement, adjudication rates, and segmentation metrics such as Dice scores?
- Data security: Can the provider meet your requirements for HIPAA, de-identification, data residency, and contractual handling of patient data?
- Evidence: Can the provider supply redacted credential-verification records and a pilot batch reviewed by your own clinical team?
My recommendation: Begin with Cogito Tech, Medcase, Graid, and Skillora Experts for an initial vendor comparison. Request a small pilot using the same images and annotation guidelines from each provider; compare clinical accuracy, inter-reader agreement, turnaround time, and total cost.
Sources cited in this answer16
- cogitotech.comMedical Data Annotation and Labeling Services | AI in Healthcare
- cogitotech.comGenerative AI in Radiology | Radiology Image Annotation
- medcase.healthMedical data annotation & labeling | Medcase
- medcase.healthAbout Us | Medcase
- medcase.healthMedical data annotation | Medcase
- graid.ioGraid - Data Annotation Services
ChatGPTOct 20, 2026
Several companies offer medical imaging annotation services with qualified radiologists, including board-certified radiologists who create or validate labels for medical AI training, testing, and clinical validation.
The key distinction is whether radiologists perform the annotations themselves, review work done by other annotators, or provide independent clinical ground truth. Based on the companies' published service descriptions, these are the strongest candidates to investigate.
Companies to shortlist
1. Medcase
(Strong match)
Connects AI companies with licensed clinicians, including US board-certified radiologists matched by subspecialty. Offers clinician-led medical imaging annotation and clinical AI validation. Its network model is particularly useful when a project requires specific expertise, such as thoracic radiology.
Best for: Subspecialty-matched radiologists and flexible clinical annotation teams.
Website ·
Source:
2. Cogito Tech
Provides medical image annotation for X-rays, CT scans, and MRIs, with board-certified radiologists supporting benchmarking, validation, supervision, and quality control. It also supports formats such as DICOM and NIfTI.
Best for: Scalable annotation operations with clinical expert oversight.
Source:
3. Image Core Lab
Offers radiologist-led annotation, board-certified radiologist review, multi-reader adjudication, lesion detection, volumetric assessment, and 3D anatomical mapping. Also provides ground-truth validation and reader studies.
Best for: Clinically rigorous datasets and validation of radiology AI algorithms.
Clinical services in radiology AI
Source:
4. Graid
Provides radiologist-validated datasets and clinical ground truth through a European radiologist network. Its offerings include single-reader and double-reader annotation, senior adjudication, and custom datasets for X-ray, CT, and MRI.
Best for: Double-reading workflows, adjudication, and custom imaging datasets.
Source:
5. Q-Rad
A radiology-focused medical service provider offering board-certified radiologist annotations, reference standards, consensus reads, expert review, and reader studies. It emphasizes documented reader qualifications and regulatory-quality evidence.
Best for: FDA or EU MDR-oriented AI development and clinical evidence.
AI ground truth and evaluation
Source:
6. HUMXN
Commissions credential-checked radiologists to label imaging studies, write and grade reports, and review other readers' work. Its workflow emphasizes study-level and series-level context rather than isolated image slices.
Best for: Radiologist-generated labels and report-quality evaluation for imaging AI.
Source:
7. Servion
Advertises a radiologist annotation service using a vetted network of board-certified radiologists. Capabilities include bounding boxes, 2D and 3D segmentation, classification, and consensus reads, with double-reading quality assurance.
Best for: Annotation plus imaging data access and AI validation support.
Source:
8. MedAnnotate
Offers radiology annotation supervised by consultant radiologists and medical imaging specialists, including segmentation and labeling of lesions, tumors, fractures, organs, and anatomical structures across several imaging modalities.
Best for: DICOM-based workflows and consultant-supervised image labeling.
Source:
How I would prioritize them
Your requirement Start with Certified radiologists directly performing annotations Medcase, Graid, HUMXN Board-certified radiologist review and scalable annotation Cogito Tech, Image Core Lab Multi-reader consensus and adjudication Graid, Q-Rad, Image Core Lab Regulatory-quality clinical ground truth Q-Rad, Image Core Lab Combined imaging data sourcing and annotation Servion These are preliminary matches based on published service descriptions, not independently audited assessments of their staffing.
Questions to ask before selecting a vendor
A company saying “radiologist-led” does not necessarily mean every image is annotated by a board-certified radiologist. I recommend asking each vendor:
- Credentials: Are the annotators board-certified radiologists, and can you verify their qualifications?
- Direct involvement: Does the radiologist annotate every case, review technician-produced labels, or adjudicate disagreements?
- Subspecialty matching: Can you provide neuroradiologists, musculoskeletal radiologists, breast imagers, or other relevant specialists?
- Quality assurance: Do you offer double reads, inter-reader agreement metrics, and a documented consensus process?
- Technical capabilities: Do you support DICOM, 3D volumetric segmentation, bounding boxes, and your preferred annotation platform?
- Data governance: What are your HIPAA, de-identification, access-control, and data-retention arrangements?
My recommendation: Start with Medcase, Graid, and Image Core Lab if the central requirement is radiologist expertise rather than simply medically trained annotators. Request a paid or sample pilot and require evidence of annotator credentials and case-level review procedures.
Sources cited in this answer22
Google AI ModeOct 20, 2026
Several specialized companies and data-labeling providers explicitly incorporate board-certified radiologists and clinical specialists into their medical imaging annotation workflows to ensure ground-truth accuracy for healthcare AI.
- Cogito Tech — Provides medical image annotation (X-ray, CT, MRI, ultrasound, PET) and digital pathology labeling. Their workflow relies on networks of board-certified radiologists , pathologists, and cardiologists for specialist-supervised data curation and validation . Check out their Cogito Tech Medical Image Annotation overview.
- Centric Labs — Offers healthcare AI data annotation with a vetted network explicitly including board-certified radiologists , medical coders, and registered nurses mapped directly to specific imaging projects. They integrate with medical tools like ITK-SNAP and DICOM-SEG formats; see more at Centric Labs Healthcare AI Data Annotation.
- MedAnnotate — Focuses specifically on expert-led X-ray and diagnostic imaging annotation services performed by consultant radiologists and medical imaging specialists for radiographic findings (fractures, lung opacities, tumors). Learn more via MedAnnotate Radiology Annotation.
- Mindy Support — Delivers end-to-end medical data preparation and annotation across CT, MRI, X-ray, and ultrasound. They utilize a multi-level quality assurance process backed by medical expert reviews from licensed doctors and radiologists . Details can be found at Mindy Support Medical Data Annotation.
- iMerit — Employs a hybrid medical data labeling approach combining trained data specialists with an internal network of radiologists and clinical professionals to handle digital radiology AI datasets. Explore their capabilities on the iMerit Healthcare AI Blog.
If you're planning a specific project, let me know:
- What imaging modalities (CT, MRI, X-ray, Ultrasound) are you working with?
- Are you looking for bounding boxes, semantic segmentation, or landmark keypoints?
I can help you narrow down which of these providers aligns best with your technical scope and compliance needs (like HIPAA or FDA-support frameworks).
Sources cited in this answer4
Also asked as
- I need to find data annotation providers that use board-certified radiologists to label medical images for training sets.
