Solutions
The majority of healthcare data consists of medical images, providing a prime opportunity for AI advancement. Our platform allows clients to organize and analyze these images by classifying and segmenting regions of interest.
Tag skin images to identify lesions such as lacerations, psoriasis, acne, or rashes, and classify skin tone for precise color matching. Additionally, classify and segment bodily wastes and fluids to determine appropriate interventions.
Identify pleural and b-lines in lung ultrasounds, as well as segment areas of abnormal blood flow, fetal abnormalities, or gallstones.
Determine the presence of a lesion, such as a cavity, septal lines, or broken bone, and isolate the location of the lesion.
Cellular processes such as mitosis can be used to determine the mitotic rate of a cancer, while cell classification can determine differentiation between tumor and healthy cells. Other cellular and molecular features can also be identified and categorized.
Locate and identify the presence of a lesion, such as a tumor, lung nodule, brain bleed, or area of decreased blood flow. Segment the location of the lesion.
ClassificationPolygon SegmentationBox SegmentationLine SegmentationCircle SegmentationXANA accelerates AI development with speedy access to millions of diverse data points. Rooted in quality, it ensures consistent performance, advanced insights, and top-notch privacy across various industries and data types.
Stop annotating data slowly with in-house teams or outsourcing to teams whose quality you can't control.
Access the Centaur Labs network of thousands of medical doctors, professionals, researchers and students for skilled annotation
You define quality. We rigorously measure and manage it.
Incentivize labeler performance with small batch, mobile-first competitions. Labelers are only paid for performance and give 100% of their effort on every case
Proactively understand the nuances of your dataset, so your data works with you, not against you.
Leverage case-level insights to inform model development e.g. precision-recall curves, label distribution, labeler agreement
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