• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.515-520
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• 2016

Volumetric image system has many applications recently in education, 3D movie, medical images but these applications have several problems that need to be overcome. Volumetric display may process a amount of visual data and design the high efficient vision system for realtime display. In case of stereo system for volumetric display motion vectors, disparity vectors from the stereoscopic sequences and residual images with the reference images has been transmitted, and the stereoscopic sequences have been reconstructed at the receiver for volumetric display. So central issue for the design of efficient volumetric image system lies in selecting an appropriate stereo matching and robust vision system. In this paper, we proposed high efficient vision system, which design vision stage with rotating and moving horizontally, and match the successive stereo image efficiently. In experimental results with volumetric image system, the proposed method represents high efficiency with minimizing error and low computational load for volumetric display.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.223-231
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• 1997

In this paper, an interframe coding method for volumetric medical images is proposed. By treating interslice variations as the motion of bones or tissues, we use the motion compensation (MC) technique to predict the current frame from the previous frame. Instead of a block matching algorithm (BMA), which is the most common motion estimation (ME) algorithm in video coding, image warping with biolinear transformation has been suggested to predict complex interslice object variation in medical images. When an object disappears between slices, however, warping prediction has poor performance. In order to overcome this drawback, an overlapped block motion compensation (OBMC) technique is combined with carping prediction. Motion compensated residual images are then encoded by using an embedded zerotree wavelet (EZW) coder with small modification for consistent quality of reconstructed images. The experimental results show that the interframe coding suing warping prediction provides better performance compared with interframe coding, and the OBMC scheme gives some additional improvement over the warping-only MC method.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.476-486
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• 2019

Objective : The functional information of $^{11}C$-methionine positron emission tomography (MET-PET) images can be applied for Gamma knife radiosurgery (GKR) and its image quality may affect defining the tumor. This study conducted the phantom-based evaluation for geometric accuracy and functional characteristic of diagnostic MET-PET image co-registered with stereotactic image in Leksell $GammaPlan^{(R)}$ (LGP) and also investigated clinical application of these images in metastatic brain tumors. Methods : Two types of cylindrical acrylic phantoms fabricated in-house were used for this study : the phantom with an array-shaped axial rod insert and the phantom with different sized tube indicators. The phantoms were mounted on the stereotactic frame and scanned using computed tomography (CT), magnetic resonance imaging (MRI), and PET system. Three-dimensional coordinate values on co-registered MET-PET images were compared with those on stereotactic CT image in LGP. MET uptake values of different sized indicators inside phantom were evaluated. We also evaluated the CT and MRI co-registered stereotactic MET-PET images with MR-enhancing volume and PET-metabolic tumor volume (MTV) in 14 metastatic brain tumors. Results : Imaging distortion of MET-PET was maintained stable at less than approximately 3% on mean value. There was no statistical difference in the geometric accuracy according to co-registered reference stereotactic images. In functional characteristic study for MET-PET image, the indicator on the lateral side of the phantom exhibited higher uptake than that on the medial side. This effect decreased as the size of the object increased. In 14 metastatic tumors, the median matching percentage between MR-enhancing volume and PET-MTV was 36.8% on PET/MR fusion images and 39.9% on PET/CT fusion images. Conclusion : The geometric accuracy of the diagnostic MET-PET co-registered with stereotactic MR in LGP is acceptable on phantom-based study. However, the MET-PET images could the limitations in providing exact stereotactic information in clinical study.

• Progress in Medical Physics
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• v.18 no.3
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• pp.118-125
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• 2007

In this study we estimated a geometric correlation among digitally reconstructed radiographic image (DRRI), kV x-ray image (kVXI) from the On-Board Imager (OBI) and electric portal image (EPI). To verify geometric correspondence of DRRI, kVXI and EPI, specially designed phantom with indexed 6 ball bearings (BBs) were employed. After accurate setup of the phantom on a treatment couch using orthogonal EPIs, we acquired set of orthogonal kVXIs and EPIs then compared the absolute positions of the center of the BBs calculated at each phantom plane for kVXI and EPI respectively. We also checked matching result for obliquely incident beam (gantry angle of $315^{\circ}$) after 2D-2D matching provided by OBI application. A reference EPI obtained after initial setup of the phantom was compared with 10 series of EPIs acquired after each 2D-2D matching. Imaginary setup errors were generated from -5 mm to 5 mm at each couch motion direction. Calculated positions of all center positions of the BBs at three different images were agreed with the actual points within a millimeter and each other. Calculated center positions of the BBs from the reference and obtained EPIs after 2D-2D matching agreed within a millimeter. We could tentatively conclude that the OBI system was mechanically quite reliable for image guided radiation therapy (IGRT) purpose.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.68-71
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• 1997

The early detection of brest cancer is clearly a key ingredient for any strategy designed to reduce breast cancer mortality. Microcalcification(MCC) is one of the primary signatures to discriminate between normal and cancerous tissue. The detection and locating procedures can be automated by digital image processing, however, MCCs have various sizes, shapes, and intensity levels in film images, so it is difficult to find accurate locations and sizes. Firstly, we made quantitative analysis for many characteristic features of mammograms that can be used to segment MCCs from normal tissues. Secondly, we developed algorithms proper to segmentation like pattern matching. The performance was evaluated with TP and FP rates.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.265-266
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• 1998

This paper describes a depth extraction algorithm in the stereo endoscopic images using adaptive window. First, The relation between the 3D coordinates in the world and the 2D coordinates in the image plane is estimated using camera calibration. Next, stereo matching is performed to find the conjugate pairs in the left and right images. To improve the precision of the matching result, adaptive window which can be varied on the shape as well as on the size according to the area characteristics is used. Finally, the result from the stereo matching and that of camera modeling are combined to extract the real depth information.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.97-105
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• 2018

Purpose : Proton Therapy using Bragg-peak, because it has distinct characteristics in providing maximum dosage for tumor and minimal dosage for normal tissue, a medical imaging system that can quantify changes in patient position or treatment area is of paramount importance to the treatment of protons. The purpose of this research is to evaluate the usefulness of the algorithm by comparing the image matching through the set-up and in-house code through the existing dips program by producing a Matlab-based in-house registration code to determine the error value between dips and DRR to evaluate the accuracy of the existing treatment. Materials and Methods : Thirteen patients with brain tumors and head and neck cancer who received proton therapy were included in this study and used the DIPS Program System (Version 2.4.3, IBA, Belgium) for image comparison and the Eclipse Proton Planning System (Version 13.7, Varian, USA) for patient treatment planning. For Validation of the Registration method, a test image was artificially rotated and moved to match the existing image, and the initial set up image of DIPS program of existing set up process was image-matched with plan DRR, and the error value was obtained, and the usefulness of the algorithm was evaluated. Results : When the test image was moved 0.5, 1, and 10 cm in the left and right directions, the average error was 0.018 cm. When the test image was rotated counterclockwise by 1 and $10^{\circ}$, the error was $0.0011^{\circ}$. When the initial images of four patients were imaged, the mean error was 0.056, 0.044, and 0.053 cm in the order of x, y, and z, and 0.190 and $0.206^{\circ}$ in the order of rotation and pitch. When the final images of 13 patients were imaged, the mean differences were 0.062, 0.085, and 0.074 cm in the order of x, y, and z, and 0.120 cm as the vector value. Rotation and pitch were 0.171 and $0.174^{\circ}$, respectively. Conclusion : The Matlab-based In-house Registration code produced through this study showed accurate Image matching based on Intensity as well as the simple image as well as anatomical structure. Also, the Set-up error through the DIPS program of the existing treatment method showed a very slight difference, confirming the accuracy of the proton therapy. Future development of additional programs and future Intensity-based Matlab In-house code research will be necessary for future clinical applications.

• Progress in Medical Physics
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• v.32 no.2
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• pp.40-49
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• 2021

Purpose: This study aimed to develop a surface-guided radiosurgery system customized for a neurosurgery clinic that could be used as an auxiliary system for improving the accuracy, monitoring the movements of patients while performing hypofractionated radiosurgery, and minimizing the geometric misses. Methods: RGB-D cameras were installed in the treatment room and a monitoring system was constructed to perform a three-dimensional (3D) scan of the body surface of the patient and to express it as a point cloud. This could be used to confirm the exact position of the body of the patient and monitor their movements during radiosurgery. The image from the system was matched with the computed tomography (CT) image, and the positional accuracy was compared and analyzed in relation to the existing system to evaluate the accuracy of the setup. Results: The user interface was configured to register the patient and display the setup image to position the setup location by matching the 3D points on the body of the patient with the CT image. The error rate for the position difference was within 1-mm distance (min, -0.21 mm; max, 0.63 mm). Compared with the existing system, the differences were found to be as follows: x=0.08 mm, y=0.13 mm, and z=0.26 mm. Conclusions: We developed a surface-guided repositioning and monitoring system that can be customized and applied in a radiation surgery environment with an existing linear accelerator. It was confirmed that this system could be easily applied for accurate patient repositioning and inter-treatment motion monitoring.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.189-190
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• 1998

In this paper, we show the realtime 3D reconstruction algorithm with the sliced CT images. The preprocessing is thresholding, labeling, contouring, and extracting dominant point. we reconstruct 3D image with dominant points using dynamic matching technique. The software implemented in Visualc++ 5.0 as a window-based application program.

• Progress in Medical Physics
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• v.23 no.1
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• pp.8-14
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• 2012

In order to develop a Patient respiratory management system includinga biofeedback function for4-dimentional radiation therapy, this study investigated anoptimal tracking algorithmfor moving target using IR (Infra-red) camera as well as commercial camera. A tracking system was developed by LabVIEW 2010. Motion phantom images were acquired using a camera (IR or commercial). After image process were conducted to convert acquired image to binary image by applying a threshold values, several edge enhance methods such as Sobel, Prewitt, Differentiation, Sigma, Gradient, Roberts, were applied. The targetpattern was defined in the images, and acquired image from a moving targetwas tracked by matching pre-defined tracking pattern. During the matching of imagee, thecoordinateof tracking point was recorded. In order to assess the performance of tracking algorithm, the value of score which represents theaccuracy of pattern matching was defined. To compare the algorithm objectively, we repeat experiments 3 times for 5 minuts for each algorithm. Average valueand standard deviations (SD) of score were automatically calculatedsaved as ASCII format. Score of threshold only was 706, and standard deviation was 84. The value of average and SD for other algorithms which combined edge detection method and thresholdwere 794, 64 in Sobel, 770, 101 in Differentiation, 754, 85 in Gradient, 763, 75 in Prewitt, 777, 93 in Roberts, and 822, 62 in Sigma, respectively. According to score analysis, the most efficient tracking algorithm is the Sigma method. Therefore, 4-dimentional radiation threapy is expected tobemore efficient if threshold and Sigma edge detection method are used together in target tracking.