Annotating Radiology Images with V7: An Annotator's Guide
Radiology image annotation requires a high level of expertise and is often time-consuming. However, thanks to new developments in artificial intelligence, the process can be streamlined with semi-automatic annotation tools.
In today's video, we are exploring V7—an online training data platform that allows for very accurate medical image annotation for AI. We are going to take a look at some CT scans and test the automatic annotation functionality for one-click instance segmentation.
Chapters are:
0:00 Introduction
1:07 CT Image Stack annotation
1:55 Auto-annotation
2;58 Overlapping regions of interest
4:20 Layered semantic segmentation maps
5:00 Final thoughts
This platform can improve the radiology image annotation process by providing an easy-to-use interface for creating and managing annotations, as well as a variety of tools for specific annotation tasks.
If you would like to use V7 for your research, try out the free educational plan: https://www.v7labs.com/verify-academia
Datasets used in this tutorial are as follows:
https://drive.google.com/file/d/1bum9...
(related notebook) https://www.kaggle.com/code/ahmedkhai...