Mar 17, 2019

Fast and Precise Hippocampus Segmentation Through Deep Convolutional Neural Network Ensembles and Transfer Learning

Neuroinformatics
Dimitrios AtaloglouPetros Daras

Abstract

Automatic segmentation of the hippocampus from 3D magnetic resonance imaging mostly relied on multi-atlas registration methods. In this work, we exploit recent advances in deep learning to design and implement a fully automatic segmentation method, offering both superior accuracy and fast result. The proposed method is based on deep Convolutional Neural Networks (CNNs) and incorporates distinct segmentation and error correction steps. Segmentation masks are produced by an ensemble of three independent models, operating with orthogonal slices of the input volume, while erroneous labels are subsequently corrected by a combination of Replace and Refine networks. We explore different training approaches and demonstrate how, in CNN-based segmentation, multiple datasets can be effectively combined through transfer learning techniques, allowing for improved segmentation quality. The proposed method was evaluated using two different public datasets and compared favorably to existing methodologies. In the EADC-ADNI HarP dataset, the correspondence between the method's output and the available ground truth manual tracings yielded a mean Dice value of 0.9015, while the required segmentation time for an entire MRI volume was 14.8 seconds. ...Continue Reading

  • References10
  • Citations

Citations

  • This paper may not have been cited yet.

Mentioned in this Paper

INTS6
Magnetic Resonance Imaging
Three-dimensional
Centrosomin protein, Drosophila
Depth
Learning
Psychological Transfer
Neural Networks (Anatomic)
Hippocampus (Brain)

Related Feeds

Cell Adhesion Molecules in the Brain

Cell adhesion molecules found on cell surface help cells bind with other cells or the extracellular matrix to maintain structure and function. Here is the latest research on their role in the brain.

Related Papers

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Lydia LindnerJan Egger
IEEE Journal of Biomedical and Health Informatics
Yu ZhaoBjoern Menze
© 2020 Meta ULC. All rights reserved