Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

This study compares two different methods for the task of brain segmentation in rodent MR-images, a convolutional neural network (CNN) and majority voting of a registration based atlas (RBA) , and how limited training data affect their performance. The CNN was implemented in Tensorflow.

The RBA performs better on average when using a training set with fewer than 20 images but the CNN achieves a higher median dice-score with a training set of 19 images.
Original languageEnglish
Publication date2018
Publication statusPublished - 2018
EventJoint Annual Meeting ISMRM-ESMRMB 2018 - Paris, France
Duration: 16 Jun 201821 Oct 2018


ConferenceJoint Annual Meeting ISMRM-ESMRMB 2018

ID: 204115825