Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks
Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
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Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks. / Sigurdsson, Björn; Darkner, Sune; Sommer, Stefan Horst; Mortensen, Kristian Nygaard; Sanggaard, Simon; Kostrikov, Serhii; Nedergaard, Maiken.
2018. Abstract fra Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, Frankrig.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning › fagfællebedømt
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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 -
ID: 204115825