Presentation Information
[8a-PA3-7]Segmentation of X-ray CT Images Using Integrated Features from Absorption and Phase-Contrast Images
〇Ryosuke Ueda1, Yuki Goto2, Hideki Tsuruta2, Chika Kamezawa1, Junya Kowa2, Wataru Yashiro1 (1.Tohoku Univ., 2.IHI)
Keywords:
X-ray Computed Tomography,X-ray Phase Imaging,Segmentation
X-ray CT enables three-dimensional visualization of internal structures; however, segmentation is often difficult for samples composed mainly of light elements because of their low absorption contrast. In this study, we investigated a segmentation method using integrated features from absorption-contrast and phase-contrast CT images. Segmentation was performed using a random forest classifier and evaluated using CT data acquired at the BL09W beamline of NanoTerasu. The results showed that phase-contrast features achieved higher classification performance than absorption-contrast features alone, while the integrated feature set provided the best performance. These findings suggest that absorption and phase information complement each other and improve segmentation accuracy.