AUTOMATIC DETECTION OF THE NASAL CAVITIES AND PARANASAL SINUSES USING DEEP NEURAL NETWORKS

被引:0
|
作者
Laura, Cristina Oyarzun [1 ,2 ]
Hofmann, Patrick [1 ]
Drechsler, Klaus [3 ]
Wesarg, Stefan [1 ]
机构
[1] Fraunhofer Inst Comp Graph Res IGD, Darmstadt, Germany
[2] Tech Univ Darmstadt, Graph Interakt Syst, Darmstadt, Germany
[3] Aachen Univ Appl Sci, Aachen, Germany
来源
2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019) | 2019年
关键词
Deep learning; Nasal cavity; Paranasal sinus; Organ detection; YOLO; LOCALIZATION; REGRESSION;
D O I
10.1109/isbi.2019.8759481
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The nasal cavity and paranasal sinuses present large interpatient variabilities. Additional circumstances like for example, concha bullosa or nasal septum deviations complicate their segmentation. As in other areas of the body a previous multi structure detection could facilitate the segmentation task, In this paper an approach is proposed to individually detect all sinuses and the nasal cavity. For a better delimitation of their borders the use of an irregular polyhedron is proposed. For an accurate prediction the Darknet-19 deep neural network is used which combined with the You Only Look Once method has shown very promising results in other fields of computer vision, 57 CT scans were available of which 85% were used for training and the remaining 15% for validation.
引用
收藏
页码:1154 / 1157
页数:4
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