Landmark assignment

This workflow predict landmark positions on images by using MSET landmark detection models.

This workflow trains MSET landmark detection models from a dataset of annotated images.

It is a trainable interest point (anatomical landmarks) detection algorithm. It requires images and interest point coordinates. It can run independantly (using csv files to describe coordinates) or it can be executed using Cytomine.

Typical application: Morphometric studies (e.g. in zebrafish/drosphila development)

Used in: Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge http://dx.doi.org/10.1109/TMI.2015.2412951 Automatic localization of interest points in zebrafish images with tree-based methods