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윤웅배,오지은,양희경,황정민,문효원,박종일,김광기 한국멀티미디어학회 2016 멀티미디어학회논문지 Vol.19 No.8
Strabismus is a non-aligned state;the visual axis of each eye is not directed toward the same direction at the same time. Clinically, the degrees of strabismus are measured by prism cover test, corneal reflex test (Hirschberg test), prism reflex test (Krimsky prism test), But corneal reflex test and prism reflex test is a possibility that errors occur. we suggest a computer-aided diagnosis for strabismus. We made a mobile application to measure angles of strabismus. For 34 patients, we tested our application. The result of comparing between two methods, It showed a difference 7 Prism Diopter(PD). Our application gives strabismus angles just using a camera and a smart device. Therefore, it can reduce the cost and make the diagnosis of strabismus accurate.
윤웅배,김현진,김광기,최용두,장희진,손대경 대한의료정보학회 2016 Healthcare Informatics Research Vol.22 No.3
Objectives: We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. Methods: We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. Results: An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. Conclusions: The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.
윤웅배(Woong Bae Yoon),오지은(Ji Eun Oh),문효원(Hyo Won Moon),양희경(Hee Kyung Yang),황정민(Jeong Min Hwang),박종일(Jong Il Park),김광기(Kwang Gi Kim) 한국멀티미디어학회 2016 멀티미디어학회논문지 Vol.19 No.8
Strabismus is a non-aligned state;the visual axis of each eye is not directed toward the same direction at the same time. Clinically, the degrees of strabismus are measured by prism cover test, corneal reflex test (Hirschberg test), prism reflex test (Krimsky prism test), But corneal reflex test and prism reflex test is a possibility that errors occur. we suggest a computer-aided diagnosis for strabismus. We made a mobile application to measure angles of strabismus. For 34 patients, we tested our application. The result of comparing between two methods, It showed a difference 7 Prism Diopter(PD). Our application gives strabismus angles just using a camera and a smart device. Therefore, it can reduce the cost and make the diagnosis of strabismus accurate.
김홍래,이현민,윤웅배,김영재,김석기,유헌,주재영,김광기,이승훈,Kim, Hong Rae,Lee, Hyun Min,Yoon, Woong Bae,Kim, Young Jae,Kim, Seok Ki,Yoo, Heon,Joo, Jae Young,Kim, Kwang Gi,Lee, Seung-Hoon 대한의용생체공학회 2015 의공학회지 Vol.36 No.1
Indocyanine green(ICG) and 5-aminolevulinic acid(5-ALA) have been widely used to mark blood vessels or tumors. However, fluorescent dye detection systems were designed to use one type of dyes only. In this study, we proposed a detection system capable of detecting Indocyanine green and 5-aminolevulinic acid. Multiple filters and light sources are integrated into a single system. In this study, we performed analysis of fluorescent dyes and configured a detection system. During the analysis, it was found that Indocyanine green and 5-aminolevulinic acid have the maximum intensity at $40{\mu}M$. We designed light source for fluorescent dyes and conducted compatibility test using a commercial surgical microscope. The fluorescent dye detection system was configured based on the experimental results. The developed system successfully detects Indocyanine green and 5-aminolevulinic acid. Therefore, more efficient surgical operations can be achieved using both fluorescent dyes at the same time. We expect that the developed system can increase the survival rate of patients.
수술현미경에서의 다중형광영상을 이용한 뇌종양과 혈관영상 검출 시스템 연구
이현민,김홍래,윤웅배,김영재,김광기,김석기,유헌,이승훈,신민선,권기철,Lee, Hyun Min,Kim, Hong Rae,Yoon, Woong Bae,Kim, Young Jae,Kim, Kwang Gi,Kim, Seok Ki,Yoo, Heon,Lee, Seung Hoon,Shin, Min Sun,Kwon, Ki Chul 한국광학회 2015 한국광학회지 Vol.26 No.1
본 연구에서는 뇌 종양 수술에서 다수의 광원과 빔 스플리터 모듈을 사용해 종양과 혈관의 형광영상을 동시에 검출하고 획득한 형광영상을 동일한 디스플레이 장치에 표시함으로써 시술자에게 종양과 혈관의 정확한 정보를 실시간으로 제공할 수 있는 현미경 시스템을 제안한다. 5-ALA(5-Aminolevulinic acid) 와 ICG(Indocyanine green) 의 형광영상의 동시 검출을 위해 빔 스플리터(beam-splitter : BS)모듈을 사용하였고 5-ALA는 600nm, ICG는 800nm이상의 파장 대역에서 가장 효율이 뛰어나도록 구성하였다. 빔 스플리터 모듈은 파장 대역에 따라 광학기기의 구조를 변경할 수 있고 필터를 탈, 착 가능한 구조로 설계하여 필요에 따라 빔 스플리터와 필터의 종류를 변경할 수 있으며 5-ALA 및 ICG 이외의 형광염료를 사용한 시술에서 사용할 수 있다. 빔 스플리터 모듈을 통한 형광영상은 5-ALA는 가시광역, ICG는 근적외선 영역을 검출 할 수 있는 CCD 카메라를 장착해 동일한 디스플레이에서 확인할 수 있고 획득한 형광영상은 닮음 변환(similarity transform)을 이용해 원영상과 정합하여 실시간으로 시술자에게 제공하는 시스템을 구현하였다. In this paper, we propose a microscope system for detecting both a tumor and blood vessels in brain tumor surgery as fluorescence images by using multiple light sources and a beam-splitter module. The proposed method displays fluorescent images of the tumor and blood vessels on the same display device and also provides accurate information about them to the operator. To acquire a fluorescence image, we utilized 5-ALA (5-aminolevulinic acid) for the tumor and ICG (Indocyanine green) for blood vessels, and we used a beam-splitter module combined with a microscope for simultaneous detection of both. The beam-splitter module showed the best performance at 600 nm for 5-ALA and above 800 nm for ICG. The beam-splitter is flexible to enable diverse objective setups and designed to mount a filter easily, so beam-splitter and filter can be changed as needed, and other fluorescent dyes besides 5-ALA and ICG are available. The fluorescent images of the tumor and the blood vessels can be displayed on the same monitor through the beam-splitter module with a CCD camera. For ICG, a CCD that can detect the near-infrared region is needed. This system provides the acquired fluorescent image to an operator in real time, matching it to the original image through a similarity transform.
유방암 조기발견을 위한 디지털 유방영상에서의 미세석회화 군집의 자동 검출
오지은(Ji Eun Oh),윤웅배(Yoon Woong Bae),김광기(Kwang Gi Kim),채은영(Eun Young Chae),김학희(Hak Hee Kim),이수열(Soo Yeul Lee) 대한전자공학회 2015 대한전자공학회 학술대회 Vol.2015 No.6
Early detection of breast cancer is crucial to improving the breast cancer prognosis and reducing the mortality rates. Microcalcification clusters (MCs) in digital mammography are a major sign of breast cancer in early stage. In this study, we proposed an automatic detection method of MCs in digital mammography. First, we extracted the breast region and then the high intensity artifacts, such as labels or scanning artifacts, were removed. Second, we enhanced the contrast to emphasize small microcalcifications in dense breast regions. Because the candidates of microcalcifications are observed as small bright blobs, we detected by using LoG(Laplacian of Gaussian) and Foveal algorithm. Candidates of MCs and false positives of them are then reduced by using knowledge based rules. The proposed method achieves a sensitivity of 94.3% at 3.3 false positive per image. In the early diagnosis of breast cancer, the proposed algorithm can be useful for the MCs detection.
유방암 조기발견을 위한 치밀 유방 영상에서의 종양 자동 검출 기법 연구
오지은(Ji Eun Oh),윤웅배(Yoon Woong Bae),김광기(Kwang Gi Kim),채은영(Eun Young Chae),김학희(Hak Hee Kim),이수열(Soo Yeul Lee) 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.6
Early detection of breast cancer is crucial to improving the breast cancer prognosis and reducing the mortality rates. Mass in digital mammography are a major sign of breast cancer in early stage. In this study, we proposed an automatic detection method of mass in digital mammography. First, we extracted the breast region and then the high intensity artifacts, such as labels or scanning artifacts, were removed. Second, we enhanced the contrast to emphasize mass with low density in dense breast regions. We detected the mass candidates by using DoG(Difference of Gaussian) and LET(Local Entropy Thresholding) algorithms. Candidates of mass and false positives of them are then reduced by using knowledge based rules. The proposed method achieves a sensitivity of 89.47% at 2.56 false positive per image. In the early diagnosis of breast cancer, the proposed algorithm can be useful for the mass detection.