Xuelong Wu¹, Junsheng Wang^1,*, Zhongyao Li¹, Yisheng Miao¹, Chengpeng Xue¹, Yuling Lang², Decai Kong², Xiaoying Ma², Haibao Qiao²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3703-3720, 2024, DOI:10.32604/cmc.2024.047027

Abstract X-ray Computed Tomography (XCT) enables non-destructive acquisition of the internal structure of materials, and image segmentation plays a crucial role in analyzing material XCT images. This paper proposes an image segmentation method based on the Segment Anything model (SAM). We constructed a dataset of carbide in nickel-based single crystal superalloys XCT images and preprocessed the images using median filtering, histogram equalization, and gamma correction. Subsequently, SAM was fine-tuned to adapt to the task of material XCT image segmentation, resulting in Material-SAM. We compared the performance of threshold segmentation, SAM, U-Net model, and Material-SAM. Our method achieved 88.45% Class Pixel Accuracy… More >

Hu Xiaofang, Xu Feng, Wang Ming, Wu Xiaoping

The International Conference on Computational & Experimental Engineering and Sciences, Vol.18, No.4, pp. 119-120, 2011, DOI:10.3970/icces.2011.018.119

Abstract The Synchrotron Radiation X-ray Computed Tomography (SR-CT) technique is a non- destructive detection technology which can give the in-situ observation of microstructure evolution of materials under the external field (e.g., high pressure, high temperature, electromagnetic field, intense radiation, etc.), and it has a significant application in the area of plants and crops, advanced manufacturing, advanced materials, biomedicine, mechanics, archaeology and so on. More >