• Journal of Biomedical Engineering Research
• /
• v.24 no.2
• /
• pp.77-82
• /
• 2003

Virtual colonoscopy is a non-invasive computerized procedure to detect polyps by examining the colon from a CT data set. To fly through the inside of colons. the extraction of a suitable flight-path is necessary to Provide the viewpoint and view direction of a virtual camera. However. manual path extraction by Picking Points is a very time-consuming and difficult task due 1,c, the long and complex shape of colon. Also, existing automatic methods are computationally complex. and tend to generate an improper and/or discontinuous path for complicated regions. In this paper, we propose a fast flight-path generation algorithm using the distance and order maps. The order map Provides all Possible directions of a path. The distance map assigns the Euclidean distance value from each inside voxel to the nearest background voxel. By jointly using these two maps. we can obtain a proper centerline regardless of thickness and curvature of an object. Also, we Propose a simple smoothing technique that guarantees not to collide with the surface of an object. The phantom and real colon data are used for experiments. Experimental results show that for a set of human colon data, the proposed algorithm can provide a smoothened and connected flight-path within a minute on an 800MHz PC. And it is proved that the obtained flight-Path provides successive volume-rendered images satisfactory for virtual navigation.

• Journal of Biomedical Engineering Research
• /
• v.38 no.3
• /
• pp.116-122
• /
• 2017

Physical breast phantoms would be useful for the development of a dedicated breast computed tomography (BCT) system and its optimization. While the conventional breast phantoms are available in compressed forms, which are appropriate for the mammography and digital tomosynthesis, however, the BCT requires phantoms in uncompressed forms. Although simple cylindrical plastic phantoms can be used for the development of the BCT system, they will not replace the roles of uncompressed phantoms describing breast anatomies for a better study of the BCT. In this study, we have designed a numerical voxel breast phantom accounting for the random nature of breast anatomies and applied it to the 3D printer to fabricate the uncompressed anthropomorphic breast phantom. The numerical voxel phantom mainly consists of the external skin and internal anatomies, including the ductal networks, the glandular tissues, the Cooper's ligaments, and the adipose tissues. The voxel phantom is then converted into a surface data in the STL file format by using the marching cube algorithm. Using the STL file, we obtain the skin and the glandular tissue from the 3D printer, and then assemble them. The uncompressed breast phantom is completed by filling the remaining space with oil, which mimics the adipose tissues. Since the breast phantom developed in this study is completely software-generated, we can create readily anthropomorphic phantoms accounting for diverse human breast anatomies.

• Progress in Medical Physics
• /
• v.19 no.2
• /
• pp.102-112
• /
• 2008

We developed a high-resolution micro-CT system based on rotational gantry and flat-panel detector for live mouse imaging. This system is composed primarily of an x-ray source with micro-focal spot size, a CMOS (complementary metal oxide semiconductor) flat panel detector coupled with Csl (TI) (thallium-doped cesium iodide) scintillator, a linearly moving couch, a rotational gantry coupled with positioning encoder, and a parallel processing system for image data. This system was designed to be of the gantry-rotation type which has several advantages in obtaining CT images of live mice, namely, the relative ease of minimizing the motion artifact of the mice and the capability of administering respiratory anesthesia during scanning. We evaluated the spatial resolution, image contrast, and uniformity of the CT system using CT phantoms. As the results, the spatial resolution of the system was approximately the 11.3 cycles/mm at 10% of the MTF curve, and the radiation dose to the mice was 81.5 mGy. The minimal resolving contrast was found to be less than 46 CT numbers on low-contrast phantom imaging test. We found that the image non-uniformity was approximately 70 CT numbers at a voxel size of ${\sim}55{\times}55{\times}X100\;{\mu}^3$. We present the image test results of the skull and lung, and body of the live mice.

• Progress in Medical Physics
• /
• v.24 no.1
• /
• pp.48-53
• /
• 2013

Monte Carlo method has been known as the most accurate method for calculating absorbed dose in the human body, and an anthropomorphic phantom has been mainly used as a method of simulating internal organs for using such a calculation method. However, various efforts are made to extract data on several internal organs in the human body directly from CT DICOM files in recent Monte Carlo calculation using Geant4 code and to use by converting them into the geometry necessary for simulation. Such a function makes it possible to calculate the internal absorbed dose accurately while duplicating the actual human anatomical structure. Thus, this study calculated the absorbed dose in the human body by using Geant4 associating with DICOM files, and aimed to confirm the usefulness by compare the result with the measured dose using a Gafchromic EBT2 film. This study compared the dose calculated using simulation and the measured dose in beam central axis using the EBT2 film. The results showed that the range of difference was an average of 3.75% except for a build-up region, in which the dose rapidly changed from skin surface to the depth of maximum dose. In addition, this study made it easy to confirm the target absorbed dose by internal organ and organ through the output of the calculated value of dose by CT slice and the dose value of each voxel in each slice. Thus, the method that outputs dose value by slice and voxel through the use of CT DICOM, which is actual image data of human body, instead of the anthropomorphic phantom enables accurate dose calculations of various regions. Therefore, it is considered that it will be useful for dose calculation of radiotherapy planning system in the future. Moreover, it is applicable for currently-used several energy ranges in current use, so it is considered that it will be effectively used in order to check the radiation absorbed dose in the human body.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.16 no.1
• /
• pp.12-16
• /
• 2012

Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.