Canopus is a software kit that we built with machine learning programs and deep learning algorithms. It captures physical raw images and removes unwanted image noise to detect cancer with improved accuracy.
We broke down the cancer-detecting process into three essential parts. They are pre-processing, image segmentation and post-processing.
Pre-processing deals with removing noise from the image captured. Image segmentation deals with further processing of the image to separate Region of Interest (ROI) from the unwanted image background. Post-processing deals with grabbing the labeled features of cancer to detect them precisely.
USP of our Project
Results – A journey from Ideas to Success
Technologies we used
“Medical imaging with deep learning almost sounded impossible. Through Canopus, SoluLab has made medical imaging look easy and convenient to use. They have taken healthcare industry to the next level”