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

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

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 language	English
Publication date	2018
Publication status	Published - 2018
Event	Joint Annual Meeting ISMRM-ESMRMB 2018 - Paris, France Duration: 16 Jun 2018 → 21 Oct 2018

Conference

Conference	Joint Annual Meeting ISMRM-ESMRMB 2018
Country/Territory	France
City	Paris
Period	16/06/2018 → 21/10/2018

Cite this

@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",

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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 -

Brain Segmentation in Rodent MR-Images Using Convolutional Neural Networks

Abstract

Conference

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