Sigurdsson, B., Darkner, S., Sommer, S. H., Mortensen, K. N., Sanggaard, S., Kostrikov, S., & Nedergaard, M. (2018). Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks. Abstract fra Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig.
Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks. / Sigurdsson, Björn
; Darkner, Sune; Sommer, Stefan Horst et al.
2018. Abstract fra Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig.
Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › peer review
Sigurdsson, B, Darkner, S, Sommer, SH, Mortensen, KN, Sanggaard, S, Kostrikov, S & Nedergaard, M 2018, 'Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks', Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig, 16/06/2018 - 21/10/2018.
Sigurdsson B, Darkner S, Sommer SH, Mortensen KN, Sanggaard S, Kostrikov S et al.. Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks. 2018. Abstract fra Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig.
Sigurdsson, Björn ; Darkner, Sune ; Sommer, Stefan Horst et al. / Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks. Abstract fra Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig.
@conference{c40f4bf218a347d7827a9989919e2c32,
title = "Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks",
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.",
author = "Bj{\"o}rn Sigurdsson and Sune Darkner and Sommer, {Stefan Horst} and Mortensen, {Kristian Nygaard} and Simon Sanggaard and Serhii Kostrikov and Maiken Nedergaard",
year = "2018",
language = "English",
note = "Joint Annual Meeting ISMRM-ESMRMB 2018 ; Conference date: 16-06-2018 Through 21-10-2018",
}
TY - ABST
T1 - Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks
AU - Sigurdsson, Björn
AU - Darkner, Sune
AU - Sommer, Stefan Horst
AU - Mortensen, Kristian Nygaard
AU - Sanggaard, Simon
AU - Kostrikov, Serhii
AU - Nedergaard, Maiken
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
M3 - Conference abstract for conference
T2 - Joint Annual Meeting ISMRM-ESMRMB 2018
Y2 - 16 June 2018 through 21 October 2018
ER -