Preliminary Study on Intervertebral Disk Segmentation from Videofluorography by Multi Channelization and CNN
Preliminary Study on Intervertebral Disk Segmentation from Videofluorography by Multi Channelization and CNN
复制标题
多通道化和CNN视频透视椎间盘分割的初步研究
DOI：
10.12792/icisip2019.050
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
H. Kudo
中科院分区：
文献类型：
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作者：
Ayano Fujinaka;Kojiro Mekata;H. Takizawa;H. Kudo
吞咽困难对患者个体和社会都有很大影响。然而，还没有对整个机制进行分析。为了了解吞咽困难，描述吞咽过程中颈部结构的解剖特征是必不可少的。本研究旨在利用多通道(MC)和卷积神经网络(CNN)对视频透视(VF)中的颈椎间盘(ID)进行分割。VF的帧图像是灰度图像。在MC过程中，通过对VF的帧图像应用图像滤波，如Sobel滤波和形态TOPHAT变换滤波来生成特征图像。在特征图像中，选择三个图像，然后通过将所选择的图像设置为彩色图像的RGB通道来生成彩色图像。彩色图像被输入到CNN进行分割。将该方法应用于实际的变频器，并给出了实验结果。
Dysphagia has a large impact on individual patients and the society. However, the whole mechanism has not been analyzed. In order to understand dysphagia, it is essential to describe the anatomical features of cervical structures during swallowing. This study aims to segment cervical intervertebral disks (IDs) in videofluorography (VF) by multi channelization (MC) and convolutional neural network (CNN). The frame images of VF are gray-scale images. In the MC process, feature images are generated by applying image filters, such as the sobel filter and morphological tophat transform filter, to the frame images of VF. Among the feature images, three images are selected, and then color images are generated by setting the selected images to the RGB channels of the color images. The color images are input into CNN for segmentation. The proposed method is applied to actual VF, and experimental results are shown.