Paper
27 March 2019 Automatic segmentation of the orbital bone in 3D maxillofacial CT images with double-bone-segmentation network
Author Affiliations +
Proceedings Volume 11050, International Forum on Medical Imaging in Asia 2019; 110500N (2019) https://doi.org/10.1117/12.2523714
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore
Abstract
We propose an automatic segmentation of the orbital bone in 3D maxillofacial CT image with double-bone-segmentation network for reconstruction of the orbital bone. Due to similar intensity value with surrounding tissues and low intensity value in thin bone, there is a limitation of under-segmentation in thin bone. To improve segmentation of thin bone, we divide into cortical and thin bone and apply to single-bone-segmentation network respectively. Experimental results show that our DBS-Net results in the improved segmentation of the orbital bone, especially in thin bone of orbital medial wall and the orbital floor.
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Soyoung Lee, Min Jin Lee, Helen Hong, Kyu Won Shim, and Seongeun Park "Automatic segmentation of the orbital bone in 3D maxillofacial CT images with double-bone-segmentation network", Proc. SPIE 11050, International Forum on Medical Imaging in Asia 2019, 110500N (27 March 2019); https://doi.org/10.1117/12.2523714
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KEYWORDS
Bone

Image segmentation

Computed tomography

3D image processing

Convolution

Network architectures

Tissues

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