• Radiation Oncology Journal
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• v.25 no.1
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• pp.54-61
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• 2007

[ $\underline{Purpose}$ ]: The purpose of this study is to develop a practical method for determining accurate marker positions for prostate cancer radiotherapy using CT images and kV x-ray images obtained from the use of the on- board imager (OBI). $\underline{Materials\;and\;Methods}$: Three gold seed markers were implanted into the reference position inside a prostate gland by a urologist. Multiple digital image processing techniques were used to determine seed marker position and the center-of-mass (COM) technique was employed to determine a representative reference seed marker position. A setup discrepancy can be estimated by comparing a computed $COM_{OBI}$ with the reference $COM_{CT}$. A proposed algorithm was applied to a seed phantom and to four prostate cancer patients with seed implants treated in our clinic. $\underline{Results}$: In the phantom study, the calculated $COM_{CT}$ and $COM_{OBI}$ agreed with $COM_{actual}$ within a millimeter. The algorithm also could localize each seed marker correctly and calculated $COM_{CT}$ and $COM_{OBI}$ for all CT and kV x-ray image sets, respectively. Discrepancies of setup errors between 2D-2D matching results using the OBI application and results using the proposed algorithm were less than one millimeter for each axis. The setup error of each patient was in the range of $0.1{\pm}2.7{\sim}1.8{\pm}6.6\;mm$ in the AP direction, $0.8{\pm}1.6{\sim}2.0{\pm}2.7\;mm$ in the SI direction and $-0.9{\pm}1.5{\sim}2.8{\pm}3.0\;mm$ in the lateral direction, even though the setup error was quite patient dependent. $\underline{Conclusion}$: As it took less than 10 seconds to evaluate a setup discrepancy, it can be helpful to reduce the setup correction time while minimizing subjective factors that may be user dependent. However, the on-line correction process should be integrated into the treatment machine control system for a more reliable procedure.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.805-813
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• 2012

In this paper, we have designed and developed a middleware for an effectively approaching database to the existed brain disease clinical research system. The brain disease clinical research system was consisted of two parts i.e., a register and an analyzer. Since the register collects the registration data the analyzer yields a statistical data which based on the diverse variables. The middleware has designed to database management and a large data query processing of clients. By separating the function of each feature as a module, the module which was weakened connectivity between functionalities has been implemented the re-use module. And image data module used a new compression method from image to text for an effective management and storage in database. We tested the middleware system using 700 actual clinical medical data. As a result, the total data transmission time was improved maximum 115 times faster than the existing one. Through the improved module structures, it is possible to provide a robust and reliable system operation and enhanced security functionality. In the future, these middleware importances should be increased to the large medical database constructions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.209-216
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• 2018

High-resolution satellite imagery is used in diverse fields such as meteorological observation, topography observation, remote sensing (RS), military facility monitoring and protection of cultural heritage. In satellite imagery, low-resolution imagery can take place depending on the conditions of hardware (e.g., optical system, satellite operation altitude, image sensor, etc.) even though the images were obtained from the same satellite imaging system. Once a satellite is launched, the adjustment of the imaging system cannot be done to improve the resolution of the degraded images. Therefore, there should be a way to improve resolution, using the satellite imagery. In this study, a super resolution (SR) algorithm was adopted to improve resolution, using such low-resolution satellite imagery. The SR algorithm is an algorithm which enhances image resolution by matching multiple low-resolution images. In satellite imagery, however, it is difficult to get several images on the same region. To take care of this problem, this study performed the SR algorithm by calibrating geometric changes on images after applying automatic extraction of feature points and projection transform. As a result, a clear edge was found just like the SR results in which feature points were manually obtained.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.453-462
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• 2022

In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

• Progress in Medical Physics
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• v.24 no.2
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• pp.85-91
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• 2013

At present, megavoltage computed tomography (MVCT) is the only method used to correct the position of tomotherapy patients. MVCT produces extra radiation, in addition to the radiation used for treatment, and repositioning also takes up much of the total treatment time. To address these issues, we suggest the use of a video image-guided setup (VIGS) system for correcting the position of tomotherapy patients. We developed an in-house program to correct the exact position of patients using two orthogonal images obtained from two video cameras installed at $90^{\circ}$ and fastened inside the tomotherapy gantry. The system is programmed to make automatic registration possible with the use of edge detection of the user-defined region of interest (ROI). A head-and-neck patient is then simulated using a humanoid phantom. After taking the computed tomography (CT) image, tomotherapy planning is performed. To mimic a clinical treatment course, we used an immobilization device to position the phantom on the tomotherapy couch and, using MVCT, corrected its position to match the one captured when the treatment was planned. Video images of the corrected position were used as reference images for the VIGS system. First, the position was repeatedly corrected 10 times using MVCT, and based on the saved reference video image, the patient position was then corrected 10 times using the VIGS method. Thereafter, the results of the two correction methods were compared. The results demonstrated that patient positioning using a video-imaging method ($41.7{\pm}11.2$ seconds) significantly reduces the overall time of the MVCT method ($420{\pm}6$ seconds) (p<0.05). However, there was no meaningful difference in accuracy between the two methods (x=0.11 mm, y=0.27 mm, z=0.58 mm, p>0.05). Because VIGS provides a more accurate result and reduces the required time, compared with the MVCT method, it is expected to manage the overall tomotherapy treatment process more efficiently.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.319-323
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• 2012

Objective: To explore the feasibility of shrinking field technique after 40 Gy radiation through 18F-FDG PET/CT during treatment for patients with stage III non-small cell lung cancer (NSCLC). Methods: In 66 consecutive patients with local-advanced NSCLC, 18F-FDG PET/CT scanning was performed prior to treatment and repeated after 40 Gy. Conventionally fractionated IMRT or CRT plans to a median total dose of 66Gy (range, 60-78Gy) were generated. The target volumes were delineated in composite images of CT and PET. Plan 1 was designed for 40 Gy to the initial planning target volume (PTV) with a subsequent 20-28 Gy-boost to the shrunken PTV. Plan 2 was delivering the same dose to the initial PTV without shrinking field. Accumulated doses of normal tissues were calculated using deformable image registration during the treatment course. Results: The median GTV and PTV reduction were 35% and 30% after 40 Gy treatment. Target volume reduction was correlated with chemotherapy and sex. In plan 2, delivering the same dose to the initial PTV could have only been achieved in 10 (15.2%) patients. Significant differences (p<0.05) were observed regarding doses to the lung, spinal cord, esophagus and heart. Conclusions: Radiotherapy adaptive to tumor shrinkage determined by repeated 18F-FDG PET/CT after 40 Gy during treatment course might be feasible to spare more normal tissues, and has the potential to allow dose escalation and increased local control.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.295-296
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• 2016

본 연구에서는 LED 광 자극이 뇌의 어느 영역을 자극하여 신경신호를 전달하는지에 관해서 관찰하고자 연구를 진행하였다. 광 자극에 의한 뇌 영역의 활성변화를 관찰하기 위하여 실험용 소동물과 영상장비인 9.4T MRI를 이용하여 연구를 수행 하였다. 실험용 소동물은 Balb/c 마우스를 이용하였으며 기능적 자기공명영상 획득 방법 중 하나인 에코평면영상 기법을 이용하여 뇌 영상을 획득 하였다. 획득한 영상을 바탕으로 뇌 영역의 자극 정도를 확인해보기 위해 영상처리기법인 재편성(realignment), 일치(co-registration), 표준화(normalization), 평활화(smoothing) 방법으로 영상을 전처리 하고, statistical parametric map (SPM12)을 사용하여 분석하였다. 본 연구에서는 광자극이 소동물 뇌 영역 중 하나인 상구(Superior colliculus)영역과 대뇌의 시각피질 (visual cortex, V1) 영역에서 자극을 일으키는 것을 확인할 수 있었다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.144-152
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• 2007

We propose a 3D modeling method for surface inspection of non-linear moving object. The laser lines reflect the surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. ill this paper, we use multi-line laser to make use of robust of single stripe method and high speed of single frame. Binarization and channel edge extraction method were used for robust laser line extraction. A new labeling method was used for laser line labeling. We acquired sink information between each 3D reconstructed frame by feature point matching, and registered each frame to one whole image. We verified the superiority of proposed method by applying it to container damage inspection system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.111-116
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• 2008

The study installed non metric camera which was a 10 Mega Pixel camera in RC Helicopter. And the study controlled images hotographed in air on land, considering their overlap. The study could express DEM by abstracting TIN from the acquired images through image registration. Also, the study compared and examined accuracy between reference point and check point observed by Total Station which was a conventional type of survey. As the results, the study could get errors of $-0.194{\sim}0.224\;m$ on X axis, $-0.088{\sim}0.180\;m$ on Y axis and $-0.286{\sim}0.285\;m$ on Z axis. Expressing an error's RMSE in the checkpoint, the study could get of 0.021388 m on X axis, 0.015285 m on Y axis and 0.041872 m on Z axis. It is judged that the above photographing and analyzing technique are better than the existing Total Station to acquire more terrain elevation data.

• Journal of KIISE
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• v.42 no.10
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• pp.1222-1230
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• 2015

Segmentation of the anterior cruciate ligament (ACL) in knee MRI remains a challenging task due to its inhomogeneous signal intensity and low contrast with surrounding soft tissues. In this paper, we propose a multi-atlas-based segmentation of the ACL in knee MRI with locally-aligned probabilistic atlas (PA) in an iterative graph cuts framework. First, a novel PA generation method is proposed with global and local multi-atlas alignment by means of rigid registration. Second, with the generated PA, segmentation of the ACL is performed by maximum-aposteriori (MAP) estimation and then by graph cuts. Third, refinement of ACL segmentation is performed by improving shape prior through mask-based PA generation and iterative graph cuts. Experiments were performed with a Dice similarity coefficients of 75.0%, an average surface distance of 1.7 pixels, and a root mean squared distance of 2.7 pixels, which increased accuracy by 12.8%, 22.7%, and 22.9%, respectively, from the graph cuts with patient-specific shape constraints.