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Whole Heart Segmentation from CT images Using 3D U-Net architecture (CROSBI ID 682047)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Habijan, Marija ; Leventic, Hrvoje ; Galic, Irena ; Babin, Danilo Whole Heart Segmentation from CT images Using 3D U-Net architecture // 2019 International Conference on Systems, Signals and Image Processing (IWSSIP). Osijek: Institute of Electrical and Electronics Engineers (IEEE), 2019. str. 121-126 doi: 10.1109/iwssip.2019.8787253

Podaci o odgovornosti

Habijan, Marija ; Leventic, Hrvoje ; Galic, Irena ; Babin, Danilo

engleski

Whole Heart Segmentation from CT images Using 3D U-Net architecture

Recent studies have demonstrated the importance of neural networks in medical image processing and analysis. However, their great efficiency in segmentation tasks is highly dependent on the amount of training data. When these networks are used on small datasets, the process of data augmentation can be very significant. We propose a convolutional neural network approach for the whole heart segmentation which is based upon the 3D U-Net architecture and incorporates principle component analysis as an additional data augmentation technique. The network is trained end-to-end i.e. no pre-trained network is required. Evaluation of the proposed approach is performed on 20 3D CT images from MICCAI 2017 Multi-Modality Whole Heart Segmentation Challenge dataset, divided into 15 training and 5 validation images. Final segmentation results show a high Dice coefficient overlap to ground truth, indicating that the proposed approach is competitive to state-of-the-art Additionally, we provide the discussion of the influence of different learning rates on the final segmentation results.

CT ; data augmentation ; heart segmentation ; medical image segmentation ; neural networks ; volumetric segmentation

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Podaci o prilogu

121-126.

2019.

objavljeno

10.1109/iwssip.2019.8787253

Podaci o matičnoj publikaciji

2019 International Conference on Systems, Signals and Image Processing (IWSSIP)

Osijek: Institute of Electrical and Electronics Engineers (IEEE)

978-1-7281-3253-2

2157-8702

Podaci o skupu

26th International Conference on Systems, Signals and Image Processing (IWSSIP 2019)

predavanje

05.06.2019-07.06.2019

Osijek, Hrvatska

Povezanost rada

Računarstvo

Poveznice