Vertebrae Pose Segmentation based on Temporal Anisotropic Diffusion and Ensembled Gradient

Abstract

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.