Medical Image Classification

Specify how you want to classify your medical data and we'll assign these categories to your data within days, not weeks or months. We structure your data to ensure quality and efficient data labeling—pre-processing it and assigning binary or multi-class labels.

medical text annotation

Binary Classification

Classification of medical images including CT, MRI, whole slide imagery, NIFTI, DICOM and video

Multiclass Classification

Identification of all findings present in an image from a predetermined list of options

Video Classification

Video processing and classification, including smart selection of frames and clips

Medical Image Classification


"Does this slide show malignant cells?"

  • Classified cells as benign or malignant in cervical pap smear slides
misinformation example

"Is metastatic tissue present?"

  • Detected the presence of metastatic tissue in lymph node tissue slides
  • Collected over 770k opinions on thousands of pathology slide patches
classify citation

"Is this lesion benign or malignant?"

  • Classified thousands of skin lesions as cancerous or non-cancerous
  • Sorted lesions into seven lesion types, including benign nevus and malignant melanoma or actinic keratosis
  • Rated the presence of extra-clinical features such as hair and rulers

"Select all x-ray finding(s)."

  • Classified chest x-rays as having no findings, or chose abnormalities observed from a set of options (including support devices, fracture, lung opacity, cardiomegaly, pneumothorax, or pleural effusion/other effusion}
  • Collected over 400k opinions on thousands of chest x-rays
Want to see more of our work? View Projects →

About Centaur Labs

Centaur Labs focuses exclusively on medical data annotation to enable breakthroughs in medical AI. Our unique approach combines multiple opinions from our network of medical experts to deliver accurate segmentations.

Get started with Centaur Labs today