Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks

Björn Sigurdsson, Sune Darkner, Stefan Horst Sommer, Kristian Nygaard Mortensen, Simon Sanggaard, Serhii Kostrikov, Maiken Nedergaard

Research output: Contribution to conferenceConference abstract for conferenceResearch

Abstract

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 Expo Porte de Versailles, Paris, France
Duration: 16 Jun 201821 Jun 2018
https://www.ismrm.org/18m/

Conference

ConferenceJoint Annual Meeting ISMRM-ESMRMB 2018
LocationParis Expo Porte de Versailles
CountryFrance
CityParis
Period16/06/201821/06/2018
Internet address

Fingerprint Dive into the research topics of 'Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks'. Together they form a unique fingerprint.

Cite this