Solutions

Annotate
medical images
at scale

90% of all healthcare data is medical images. Whether generated by smartphones or regulated medical imaging devices, this imaging data represents a significant opportunity for AI development. 

Our annotation platform enables clients to structure medical images by both classifying images and segmenting regions of interest.

Use cases

External images

Tag skin images for the presence and severity of lesions i.e. lacerations, psoriasis, acne or rashes. Classify skin tone for granular color matching. Classify and segment bodily wastes and fluids to determine interventions.

Ultrasound

Identify pleural and b-lines in lung ultrasounds. Segment areas of abnormal blood flow, fetal abnormalities, or gallstones.

X-ray

Identify the presence of a lesion, e.g. cavity, septal lines or broken bone. Segment the location of that lesion.

Pathology slide

Identify cellular processes e.g. mitosis, to determine mitotic rate of a cancer. Classify cells as high or low grade, to determine differentiation from tumor cells from healthy cells. Classify the presence of and segment other cellular or molecular features.

MRI, CT and PET

Identify the presence of a lesion, e.g. tumor, lung nodule, brain bleed, or area of decreased blood flow. C

Annotation types

Classification
Polygon segmentation
Box segmentation
Line segmentation
Circle segmentation

Testimonials

Trusted by AI leaders across healthcare

"Segmenting graft-versus-host skin disease is a complex and time consuming task. Centaur collected over 10 vetted opinions per image from their network, and combining those segmentations together produced amazingly high-quality annotations."

Director, Vanderbilt Dermatology Translational Research Clinic

"The Centaur Labs platform enabled us to quickly and conveniently gather results from our residents. We've accelerated our research by building and refining our ML models on COVID-19 pathologies in near real time. Centaur Labs has been a crucial partner throughout."

Director of Emergency Ultrasound, Emergency Medicine, Brigham & Women's Hospital

"Centaur Labs leverages an ensemble of physicians to annotate medical data for machine learning, which makes their approach highly accurate and scalable."

Head of AI, Dasa

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