Contributing to the Scancer Project
Ambitious goals require a team effort.
The Scancer project aims to bring the power of computer vision to all areas of breast cancer detection that would benefit from it. We have highlighted these areas in purple in the graphic below.
Thus far, we have focused entirely on small subset of histopathology (image classification on patches of slides) and worked out an ML pipeline and prototype web app around it. Everything we’ve built is released open source (MIT License) and in a reproducible form, so that anyone can learn from, use, and contribute to the effort. We encourage the community to contribute models and workflows for other diagnostic procedures.
If you’re a medical domain expert (doctor, radiologist, histopathologist, ...), you can help by:
- Providing your own unique datasets.
- Manually labelling existing datasets.
- Trying out our prototypes and giving us feedback on how well they fit your everyday work.
- If you’re a a machine learning practitioner, you can help train even more robust models.
- Companies are always welcome to help us financially to cover compute and hosting costs.