人工智能
分割
计算机视觉
预处理器
模式识别(心理学)
计算机科学
主成分分析
噪音(视频)
图像分割
稳健主成分分析
各项异性扩散
GSM演进的增强数据速率
边缘检测
图像(数学)
图像处理
作者
Podchara Klinwichit,John Gatewood Ham,Krisana Chinnasarn
标识
DOI:10.1109/jcsse53117.2021.9493831
摘要
Dual Energy X-ray Absorptiometry (DEXA) images can be obtained by using low radiation, so it's safer for patients. An automatic image vertebra pose segmentation can help to identify the disorder of the spine. But DEXA images are low-quality and noisy images, so it's hard to work with. This paper proposed a method to label vertebrae edges. The proposed method consists of 3 parts. First, preprocessing by using an anisotropic diffusion to reduced noise but preserved an edge. Second, segmentation by using a gradient to identify an edge. Finally, cleansing by using morphological operation and principal component analysis to clean unwanted information. The output of this algorithm is a spine image that labeled edges of the lumbar with 84.14% accuracy, 87.01% recall, 96.22% precision, and 12.55% false negative.
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