• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.245-252
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• 2020

The purpose of this study was intended to recognize the importance of quality control (QC) in order to reduce exposure and improve image quality by comparing the center-point (CP) of according to hospital grade and the difference between X-ray field (XF) and light field (LF) in diagnostic digital X-ray devices. XF and LF size, CP were measured in 12 digital X-ray devices at 10 hospitals located in 00 metropolitan cities. Phantom was made in different width respectively, using 0.8 mm wire after attaching to the standardized graph paper on transparent plastic plate and marked as cross wire in the center of the phantom. After placing the phantom on the table of the digital X-ray device, the images were obtained by shooting it vertically each field of survey. All images were acquired under the same conditions of exposure at distance of 100cm between the focus-detector. XF and LF size, CP error were measured using the picture archiving communication system. data were expressed as mean with standard error and then analyzed using SPSS ver. 22.0. The difference in field between the XF and LF size was the smallest in clinic, followed by university hospitals, hospitals and general hospitals. Based on the university hospitals with the least CP error, there was a statistically significant difference in CP error between university hospitals and clinics (p=0.024). Group less than 36-month after QC had fewer statistical errors than 36-month group (0.26 vs. 0.88, p=0.036). The difference between the XF and LF size was the lowest in clinic and CP error was the lowest in university hospital. Moreover, hospitals with short period of time after QC have fewer CP error and it means that introduction of timely QC according to the QC items is essential.