Search Word(s) in Title, Keywords, Authors, and Abstract: Computed Tomography

3D Segmentation for High-Resolution Image Datasets Using a Commercial Editing Tool in the IoT Environment
Koojoo Kwon and Byeong-Seok Shin
Page: 1126~1134, Vol. 13, No.5, 2017
10.3745/JIPS.02.0070
Keywords: Segmentation, Large-Scale Image, Photo Editing, Visible Korean, Volume Rendering
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A variety of medical service applications in the field of the Internet of Things (IoT) are being studied. Segmentation is important to identify meaningful regions in images and is also required in 3D images. Previous methods have been based on gray value and shape. The Visible Korean dataset consists of serially sectioned high-resolution color images. Unlike computed tomography or magnetic resonance images, automatic segmentation of color images is difficult because detecting an object’s boundaries in colored images is very difficult compared to grayscale images. Therefore, skilled anatomists usually segment color images manually or semi-automatically. We present an out-of-core 3D segmentation method for large-scale image datasets. Our method can segment significant regions in the coronal and sagittal planes, as well as the axial plane, to produce a 3D image. Our system verifies the result interactively with a multi-planar reconstruction view and a 3D view. Our system can be used to train unskilled anatomists and medical students. It is also possible for a skilled anatomist to segment an image remotely since it is difficult to transfer such large amounts of data.


Simulation of the Digital Image Processing Algorithm for the Coating Thickness Automatic Measurement of the TRISO-coated Fuel Particle
Woong-Ki Kim, Young-Woo Lee and Sung-Woong Ra
Page: 36~40, Vol. 1, No.1, 2005
None
Keywords: TRISO-coated Fuel Particle, Coating Thickness, X-ray CT, Computed Tomography, Filtered Backprojection, Automatic Measurement
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TRISO (Tri-Isotropic)-coated fuel particle is widely applied due to its higher stability at high temperature and its efficient retention capability for fission products in the HTGR (high temperature gas-cooled reactor), one of the highly efficient Generation IV reactors. The typical balltype TRISO-coated fuel particle with a diameter of about 1 mm is composed of a nuclear fuel particle as a kernel and of outer coating layers. The coating layers consist of a buffer PyC, inner PyC, SiC, and outer PyC layer. In this study, a digital image processing algorithm is proposed to automatically measure the thickness of the coating layers. An FBP (filtered backprojection) algorithm was applied to reconstruct the CT image using virtual X-ray radiographic images for a simulated TRISO-coated fuel particle. The automatic measurement algorithm was developed to measure the coating thickness for the reconstructed image with noises. The boundary lines were automatically detected, then the coating thickness was circularly by the algorithm. The simulation result showed that the measurement error rate was less than 1.4%.