Medicine

Use our image annotation services for your machine learning projects in medicine.

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Let's annotate some images!

Choose the most suitable annotation service for your project, or contact us to find the best fit together.

Image Annotations Services

We can provide any annotation service you imagine - from simpler methods at a lower cost to advanced expensive methods with high accuracy. Combine our experience with your needs to achieve the best possible results.

Bounding Boxes

Accurate and Correct Annotations. Guaranteed!

Our in-house professionals, using our image annotation tools with built-in machine learning and multiple layers of quality control, create the tightest and most accurately bounding boxes for computer vision and deep learning applications.

Instance Segmentation

Accurate and Correct Annotations. Guaranteed!

Each pixel in an image is mapped into specific classes; for example 'cars' and 'pedestrians' in autonomous driving data.

Semantic Segmentation

Accurate and Correct Annotations. Guaranteed!

Every pixel in an image is mapped to specific classes. Regularly used in drone and autonomous driving technology.

Video Annotation

Accurate and Correct Annotations. Guaranteed!

Each frame or key-frames annotated with or without object tracking.

Use Cases

Timely Diagnosis

Computer vision can support clinicians and researchers in the diagnosis of diseases and in the pursuit of new routes of treatment. Diseases could be diagnosed faster and more precisely with the help of artificial intelligence, comparing to the conventional procedures.

Surgery Simulation

Machine learning can be used in surgeons’ training processes and as assistance during complicated surgeries. It reduces the risk of advanced surgeries, saves resources, and lowers trauma consequences.

Medical Imaging

Computer vision takes this process to the next level. Models can be trained to recognize and diagnose diseases on MRI, CT, and X-ray scans. They can recognize changes very fast, which helps with accuracy and semi-automatization.

COVID-19 Machine learning training data

Machine learning models can spot visual patterns very accurately, and quickly, but they are not intelligent in any way. X-Rays images must be manually annotated so that AI's know which parts to focus on, such as the lungs and heart.

Why Segmentation?

Segmentation of the Lungs in X-Rays ensures the AI is only recognizing patterns in the Lungs and not accidentally being trained on something else (such as text in the X-Ray!).

Use Cases

Lung Segmentations, labelled with a patients sex, age and days since hospitalization can train models to predict the type of infection, a patients possible ventilator needs, and probability of survival.

Before After
Why Segmentation?

Segmentation of the Lungs in X-Rays ensures the AI is only recognizing patterns in the Lungs and not accidentally being trained on something else (such as text in the X-Ray!).

Use Cases

Lung Segmentations, labelled with a patients sex, age and days since hospitalization can train models to predict the type of infection, a patients possible ventilator needs, and probability of survival.

Are you a Radiologist?

We are looking for radiologists to help us annotate X-ray images of lungs, and to defeat COVID-19 together. If you are at home due to restrictions in your country you can stay in the fight.

Contact Us