Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural network

We investigated a novel method using a 2D convolutional neural network (CNN) to identify superior and inferior vertebrae in a single slice of CT images, and a post-processing for 3D segmentation and separation of cervical vertebrae. The cervical spines of patients (N == 17, 1684 slices) from Severan...

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Veröffentlicht in:	Computer methods and programs in biomedicine 2020-02, Vol.184, p.105119-105119, Article 105119
Hauptverfasser:	Bae, Hyun-Jin, Hyun, Heejung, Byeon, Younghwa, Shin, Keewon, Cho, Yongwon, Song, Young Ji, Yi, Seong, Kuh, Sung-Uk, Yeom, Jin S., Kim, Namkug
Format:	Artikel
Sprache:	eng
Schlagworte:	Automation Case-Control Studies Cervical vertebrae Cervical Vertebrae - diagnostic imaging Convolutional neural network Datasets as Topic Deep learning Humans Image Processing, Computer-Assisted - methods Neural Networks, Computer Reproducibility of Results Spine CT Spine segmentation Tomography, X-Ray Computed - methods
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