You will get Data annotation "Image classification"
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Top Rated
Project details
Our expert team is dedicated to delivering precise and reliable annotation solutions to meet the diverse needs of our clients. Whether you're in the fields of computer vision, machine learning, or artificial intelligence, our tailored bounding box annotations are designed to enhance the accuracy and efficiency of your data processing. With a focus on quality and attention to detail, we ensure that your annotated data sets are optimized for training and testing algorithms. Partner with us for exceptional data annotation services that elevate your projects to new heights of success.
What's included
| Service Tiers |
Starter
$30
|
Standard
$40
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 5 days | 5 days | 7 days |
Number of Revisions | 2 | 2 | 2 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
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HO
Harris O.
Oct 20, 2025
Machine Learning Data Annotator - Image & Video Labeling (Encord Experience)
YS
Yujan S.
Jun 6, 2025
Body Composition on L3 (2D single slice)
Superb work. Mohammed and his team did a stellar job. Quality is top notch, speed is great, and he corrected some issues my ML engineers were facing.
JS
Jael S.
May 28, 2025
(Project Cmon) - Arabic Data Annotation Project - Only UAE, Bahrain or Qatar
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Kathy J.
May 19, 2025
Image Segmentation Specialist for Vascular Networks in CT Images
Mohamed delivered exceptional results on our 3D CT segmentation project, particularly for the coronary arteries. He was communicative, detail-oriented, and delivered ahead of schedule. Highly recommend working with him
YS
Yujan S.
May 17, 2025
Segmentation Trial
Mohamed was responsive and did my medical imaging segmentation task with ease. The quality, speed, and price point was perfect.
About Mohamed
Data annotation project manager | Medical AI expert | Dentist
100%
Job Success
Dubai, United Arab Emirates - 6:54 pm local time
With over seven years of hands-on experience in medical data annotation project management, I specialize in leading high-complexity annotation initiatives across 2D and 3D medical imaging domains. I partner with AI developers, research labs, and med-tech companies to deliver clinically accurate, expertly curated datasets that power the next generation of healthcare AI solutions.
✅Advanced Annotation Tool Proficiency
Skilled in a wide range of industry-grade and medical-specialized platforms, including:
Labelbox
Label Studio
Hasty
Supervisely
Segment.ai
CVAT
V7
Encord
Redbrick AI
ITK-SNAP
3D Slicer
✅ Diverse Annotation Types (2D & 3D Imaging)
Comprehensive experience in labeling and segmentation for:
Organ and tissue segmentation
Lesion detection and classification
Dental structure annotation (tooth segmentation, caries detection)
3D volume labeling & multi-slice annotations
Bounding boxes, polygons, masks, keypoints
Semantic & instance segmentation
Radiology report tagging & medical text classification
✅ Multi-Specialty Medical Domain Experience
Successfully managed annotation pipelines across key healthcare verticals:
Radiology (CT, MRI, X-ray, PET)
Dentistry (2D & 3D CBCT)
Cardiology
Pathology (WSI & cellular-level annotation)
Gastroenterology
Hematology
This broad exposure allows rapid onboarding into new clinical contexts with strict compliance and precision.
✅ Project Leadership & Quality Assurance
As a senior project manager, I provide end-to-end management and QA services, including:
Medical expert recruitment & training
SOPs & annotation protocols tailored to clinical standards
Workflow automation & team scalability
Clinical QC reviews (by licensed professionals when required)
Delivery of HIPAA-compliant, audit-ready datasets
Consistent output accuracy >99%
Steps for completing your project
After purchasing the project, send requirements so Mohamed can start the project.
Delivery time starts when Mohamed receives requirements from you.
Mohamed works on your project following the steps below.
Revisions may occur after the delivery date.
1. initial batch delivery. "10% of the project"
Deliver 10% of the dataset for initial review to ensure that the quality matches your expectation
Entire project annotation
apply the required correction for the initial 10% submission, then annotate the rest of the Dataset