Project: Multi-Network Bone Segmentation using MonailLabel

[hmralavi]

Draft Status

Draft - team will hold off on page creation

Category

Segmentation / Classification / Landmarking

Key Investigators

• Hamid Alavi (University of Twente, The Netherlands)
• Gabrielle Tuijthof (University of Twente, The Netherlands)
• Nico Venrdonschot (University of Twente, The Netherlands)
• Malte Asseln (University of Twente, The Netherlands)

Project Description

The aim of this project is to develop a pipeline for large-scale bone segmentation using MonaiLabel. We aim to employ multiple trained segmentation models (totalsegmentator, moose, etc.), and leverage human-in-loop feature of MonaiLabel to review the quality of the predicted segmentation.

Objective

1. A MonaiLabel application equipped with multiple segmentation models.

Approach and Plan

1. Describe specific steps of what you plan to do to achieve the above described objectives.

Progress and Next Steps

1. Describe specific steps you have actually done.

Illustrations

No response

Background and References

No response