| Autor: |
Qiu, Bingjiang, Guo, Jiapan, Kraeima, J., Borra, R. J. H., Witjes, M. J. H., van Ooijen, P. M. A. |
| Rok vydání: |
2018 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| Popis: |
Segmentation of mandibles in CT scans during virtual surgical planning is crucial for 3D surgical planning in order to obtain a detailed surface representation of the patients bone. Automatic segmentation of mandibles in CT scans is a challenging task due to large variation in their shape and size between individuals. In order to address this challenge we propose a convolutional neural network approach for mandible segmentation in CT scans by considering the continuum of anatomical structures through different planes. The proposed convolutional neural network adopts the architecture of the U-Net and then combines the resulting 2D segmentations from three different planes into a 3D segmentation. We implement such a segmentation approach on 11 neck CT scans and then evaluate the performance. We achieve an average dice coefficient of $ 0.89 $ on two testing mandible segmentation. Experimental results show that our proposed approach for mandible segmentation in CT scans exhibits high accuracy. |
| Databáze: |
arXiv |
| Externí odkaz: |
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