Digital Watermarking of Medical Images

이상복(Sangbock Lee),이삼열(Samyol Lee),이준행(Jun-Haeng Lee) 대한방사선과학회(구 대한방사선기술학회) 2004 방사선기술과학 Vol.27 No.2

본 논문은 의료영상에 강력한 워터마크를 삽입하는 방법을 제안한다. 기존의 푸리에 형태의 변환은 영상의 전체적 주파수 성분에 대한 정보를 구할 수 있는 반면, 웨이블릿 변환법은 국부적으로 에지와 텍스처 영역을 찾을 수 있다. 그러므로 웨이블릿 변환을 통해 해당 영역을 선택하여 저작권 형태의 워터마크를 삽입한다. 이러한 제안 알고리즘을 단순히 웨이블릿 변환을 이용한 Xia의 워터마킹 기법과 비교하여 실험하였다. 기존 논문에서 사용된 공격법으로 충실도(Fidelity)와 견고성(Robustness)에 대해 실험하였고, 그 결과 HVS 특성을 이용한 제안 알고리즘이 Xia의 기법보다 우수함을 확인하였다. This study proposes how to insert a strong watermark creating a big change in the areas of edge and texture. While conversion by existing Fourier transformation can acquire information for all ranges of frequency domain from the image, Wavelet transformation can manipulate edge and texture area selectively. Therefore, through wavelet transformation concerned area may be selected and watermarks in copyright formation are inserted, Our proposed algorithm was compared to Xia's watermarking technique using wavelet transformation, Its fidelity and robustness were tested with attack methods used in existing papers and it turns out that the proposed algorithm using HVS properties is more superior to Xia's techniques.

Region Extraction & Disease Recognition in MRI

이상복(Sangbock Lee),이삼열(Samyol Lee),이준행(Jun-Haeng Lee) 대한방사선과학회(구 대한방사선기술학회) 2004 방사선기술과학 Vol.27 No.3

인체의 해부학적 구조에 관해 다른 영상들보다 정확한 정보를 제공하는 MRI에 대해 많은 연구가 진행중이다. 본 논문에서는 대퇴골두 무혈성 괴사의 자동 진단에 필요한 대퇴골두 영역의 추출에 관한 효과적인 방법을 제안한다. 대퇴골두의 해부학적 특성과 Hough transform을 이용하여 대퇴골두 영역을 설정하였고, 대퇴골두 영역을 분할하는 방법으로서 영역 확장법과 히스토그램 기반 영역 분할 방법의 장점을 결합한 방법을 고안하였다. 본 논문에서 제시한 방법은 정상적인 대퇴골두와 무혈성 괴사의 초기 단계의 대퇴골두 뿐만 아니라 괴사가 심한 대퇴골두에 대해서도 좋은 결과를 얻을 수 있었다. MRI imaging is one of the imaging techniques, showing anatomical structures of human body for medical diagnosis, and has been researched in order to provide better quality of anatomical information. In this study, we propose a very useful method to extract an interest areas and how to diagnose necrolysis of femoral neck disease automatically. Regions of femoral neck is set using anatomical features and Hough transform and advantages of both region extension and histogram-based region segmentation method are combined for better region segmentation. As a result of the proposed method, good imaging quality was obtained for femoral neck with both normal and severe necrosis as well as for femoral neck in early stage of necrolysis.

Measurement of Neutron Capture Gamma-ray Spectrum of Natural Gold in the keV Energy Region

Jae Hong Lee,Samyol Lee,Sangbock Lee,Junhaeng Lee,Gyehwan Jin 한국방사선학회 2007 한국방사선학회 논문지 Vol.1 No.1

keV-neutron capture gamma-ray spectrum of 197Au(natural gold) sample have been measured in neutron energy range from 10 to 90 keV using the 3-MV pelletron accelerator of the Research Laboratory for Nuclear Reactors at the Tokyo Institute of Technology. Pulsed keV neutrons were produced from the 7Li(p,n)7Be reaction by bombarding on the 7Li target with the 1.5-ns bunched proton beam. The incident neutron spectrum on the Au sample was measured by a 6Li-glass scintillation detector and TOF method. Capture gamma-rays from Au sample were measured by anti-Compton NaI(TI) spectrometer. Five average neutron energy regions were selected to obtain the neutron capture spectrum. Several gamma-ray peaks in the spectrum were found in the present experiment. 동경공업대학교의 3MV 펠레트론가속기를 사용하여 10에서 90keV 영역에 대하여 197 Au의 중성자포획 스펙트럼을 측정하였다. 중성자 펄스빔은 7Li(p,n)7 Be반응을 통하여 발생되었다. 사용되어진 양성자 빔 의 폭은 1.5-ns였다. 금 시료에 입사된 중성자의 에너지 스펙트럼은 6 Li-glass 섬광검출기의 중성자 비행 시간법을 사용하여 측정하였다. 금 시료의 중성자포획에 의해서 발생된 감마선은 anti-Compton NaI(TI) 검출장비를 사용하여 측정되었다. 본 연구에서는 5개의 중성자 에너지 역영을 선택했고, 각각의 에너지 영역에서 얻어진 감마선파고스펙트럼을 표시하였다. 본 연구에서 얻어진 스펙트럼은 처음으로 얻어진 결과이며, 중성자 결합에너지부근에 몇 개의 천이 피크가 보인다.

Image Processing Algorithms for Non-destructive Testing

SangBock Lee(이상복) 한국컴퓨터정보학회 2016 韓國컴퓨터情報學會論文誌 Vol.21 No.9

In this study, an image processing algorithm was developed to increase readability of the images of specific parts of a KTX train acquired by using a mobile digital radiographic testing device in a situation where a running train is stopped. The image processing algorithm was realized by using a Visual C++ development tool. The algorithm developed in this study allows to select an interested region in the acquired images when the interested region is suspected to cause a problem, and applies a thinning process based Sobel operators to the selected region. The experimental results show that the readability of defect parts that are not visible to naked eyes was increased through edge detector. Application of the algorithm developed in this study may help to accurately read non-destructive inspection images.

SPECT 이미지의 부분 볼륨 효과 제거를 위한 필터 설계

이상복(SangBock Lee) 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.6

분자 MR영상에서 UTE 신호의 효용성 평가

이상복(Sangbock Lee),최규락(Guirack Choi) 한국방사선학회 2012 한국방사선학회 논문지 Vol.6 No.4

본 연구에서는 MR영상의 신호획득 기법 중 TE(Time of Echo)신호와 움직임에 의한 인공물을 줄이기 위하여 신호수신 시간을 짧게 하는 UTE(Ultra Time of Echo)기법으로 신호를 획득하여 TE신호와 UTE신호의 차이를 공학적 도구인 MatLab의 DWT(Discrete Wavelet Transform) ToolBox를 이용하여 프로그램밍을 하여 특징을 추출한 후 UTE 기법의 유용성을 평가하고자 하였다. 추출된 특징값을 이용하여 TE신호(T2) 특징값과 UTE신호 특징값을 비교한 결과 거의 일치함을 알 수 있었다. This study compares the TE and UTE is to evaluate. We was programming by DWT of Matlab Tool-box for evaluation. M-program used feature value extract between TE Images and UTE Images. Two images using the extracted feature values were compared. Comparison of similar features two images phase was found to have value.

MR Molecular Imaging for Find Biological Processes of Occur in Breast Cancer

Hwunjae Lee,Minju Park,Jungmin Son,Byungchea Lee,Jisun Kim,Guyrack Choi,ByeoungJu Ahn,Sangbock Lee 한국방사선학회 2014 한국방사선학회 학술대회 논문집 Vol.2014 No.춘계

Novel diagnostic technique has been developed in many research area using targetable contrast agents with magnetic resonance imaging (MRI) for cancer diagnosis. It is efficient for cancer diagnosis to use MRI with biocompatible targeting moiety and magnetic nanoparticles (MNPs).Thus, we synthesized MNPs using thermal decomposition method which enable sensitive T2- or T2 Turbo spin echo (TSE) weighted magnetic resonance imaging. And it was coated with Hyaluronic acid (HA). Also we carried out that breast cancer cell line (MDA-MB-231) which has cancer stem cell property was injected in heterotopic mouse model. And then magnetic resonance sequence (T2) for imaging effects and targeting ability were analyzed into MNPs conjugated HA. We noted that MDA-MB-231cellwhich high-expressed CD44 ligand was showed contrast enhance efficiency through magnetic nanoparticles because of combining a lot of HA. As a result of these studies, we conclude that HA coated magnetic nanoparticles can be effectively used as a novel probe for visualizing of Breast cancer stem cell.

MR Molecular Imaging for Find Biological Processes of Occur in Breast Cancer

Hwunjae Lee,Minju Park,Jungmin Son,Byungchea Lee,Jisun Kim,Guyrack Choi,ByeoungJu Ahn,Sangbock Lee 한국방사선학회 2014 한국방사선학회 학술대회 논문집 Vol.8 No.1

Novel diagnostic technique has been developed in many research area using targetable contrast agents with magnetic resonance imaging (MRI) for cancer diagnosis. It is efficient for cancer diagnosis to use MRI with biocompatible targeting moiety and magnetic nanoparticles (MNPs).Thus, we synthesized MNPs using thermal decomposition method which enable sensitive T2- or T2 Turbo spin echo (TSE) weighted magnetic resonance imaging. And it was coated with Hyaluronic acid (HA). Also we carried out that breast cancer cell line (MDA-MB-231) which has cancer stem cell property was injected in heterotopic mouse model. And then magnetic resonance sequence (T2) for imaging effects and targeting ability were analyzed into MNPs conjugated HA. We noted that MDA-MB-231cellwhich high-expressed CD44 ligand was showed contrast enhance efficiency through magnetic nanoparticles because of combining a lot of HA. As a result of these studies, we conclude that HA coated magnetic nanoparticles can be effectively used as a novel probe for visualizing of Breast cancer stem cell.

신경회로망에 의한 의료영상 질환인식

이상복(Sangbock Lee),이준행(Junhaeng Lee),김태식(Taesik Kim) 한국방사선학회 2009 한국방사선학회 논문지 Vol.3 No.1

본 논문에서는 신경회로망을 이용한 의료영상의 질환부위 인식방법을 제안하였다. 질환부위 인식을 위한 신경회로망은 입력층, 은닉층, 출력층으로 구성하여 적응 오차 역전파 알고리즘으로 학습하였다. 신경회로망에 입력된 의료영상의 특징 파라미터는 웨이브릿 변환에 의하여 분해된 저주파 영역을 행렬식으로 표현하여 특성다항식의 계수값 (n+1)개로 하였다. 추출된 특징 파라미터는 탄젠트시그모이드 전달함수의 범위로 정규화하여 신경회로망의 입력 벡터로 이용하였다. 제안된 방법의 타당성을 입증하기 위해서 실험에 사용된 입력 의료영상을 가지고 모사실험을 통해 질환부위의 인식률을 평가하였다. 실험 결과 4레벨 DWT로 변환된 저주파영역 행렬의 특성 다항식 계수를 탄젠트시그모이드 전달함수의 범위로 정규화하여 신경회로망의 입력 벡터로 이용했을 때 최적의 학습 횟수를 보였다. 신경회로망의 학습은 적응오차 역전파 알고리즘을 사용하였고, 학습계수를 0.01, 모우멘텀을 0.95로 하였을 때, 위영상에 대해서는 55회, 가슴영상은 55회, CT영상은 46회, 초음파영상은 55회 그리고 혈관영상에 대해서는 157회 등의 최적의 학습 횟수를 보이며 100%의 인식률을 보였다. In this paper has proposed to the recognition of the disease on medical images using neural network. The neural network is constructed as three-layers of the input-layer, the hidden-layer and the output-layer. The training method applied for the recognition of disease region is adaptive error back-propagation. The low-frequency region analyzed by DWT are expressed by matrix. The coefficient-values of the characteristic polynomial applied are n+1. The normalized maximum value +1 and minimum value -1 in the range of tangent-sigmoid transfer function are applied to be use as the input vector of the neural network. To prove the validity of the proposed methods used in the experiment with a simulation experiment, the input medical image recognition rate the evaluation of areas of disease. As a result of the experiment, the characteristic polynomial coefficient of low-frequency area matrix, conversed to 4 level DWT, was proved to be optimum to be applied to the feature parameter. As for the number of training, it was marked fewest in 0.01 of learning coefficient and 0.95 of momentum, when the adaptive error back-propagation was learned by inputting standardized feature parameter into organized neural network. As to the training result when the learning coefficient was 0.01, and momentum was 0.95, it was 100% recognized in fifty-five times of the stomach image, fifty-five times of the chest image, forty-six times of the CT image, fifty-five times of ultrasonogram, and one hundred fifty-seven times of angiogram.

디지털 유방영상의 CAD 알고리즘 구현

이병채(Byungchea Lee),최규락(Guirack Choi),정재은(Jaeeun Jung),이상복(Sangbock Lee) 한국방사선학회 2014 한국방사선학회 논문지 Vol.8 No.1

건강에 대한 관심의 증대로 의료영상이 빠르게 증가하고 있으며, 컴퓨터 기술의 발전으로 의료영상의 디지털화가 빠르게 진전되어 PACS가 의료현장에 도입되었다. 이러한 현상에 의한 의료영상 생산의 증가는 의료영상을 판독하여야 하는 영상의학과 전문의의 업무량을 증가하게 하였다. 이러한 추세에 따라 컴퓨터를 이용한 보조 진단의 필요성이 대두되어 의료영상 판독 분야에 CAD라는 용어가 생겨나게 되었다. 본 연구에서는 디지털 X-선 유방촬영장치에 의하여 획득된 영상의 판독을 위한 CAD 알고리즘을 제안하였다. 제안된 알고리즘을 Visual C++로 프로그램하여 실험하였다. 본 연구에 사용한 일곱 샘플영상을 CAD 알고리즘으로 실행한 결과 다섯 샘플의 결과는 양성종양 및 유방암으로 확인되었고 두 샘플 영상은 error처리 되었다. 본 연구에서 제시한 알고리즘과 이를 구현한 프로그램을 이용한다면 판독업무에 많은 도움이 될 것이며, 유방암의 조기발견에 크게 기여할 것으로 사료된다. Medical imaging has increased rapidly in the increase of interest in health, with the development of computer technology, digitization of medical imaging is rapidly advancing, PACS has been introduced to the medical field. Increase in the production of medical images by these phenomena made increased the workload of radiologist who must read a medical image. in response to the need for secondary diagnosis using a computer, The term of CAD in medical radiology field was introduced. In this study, we have proposed a CAD algorithm for the interpretation of the image obtained by the digital X-ray mammography equipment. The experiments were performed by programmed in Visual C++ for the proposed algorithm. A result of the execution of the CAD algorithm seven sample images, the results of five samples was confirmed in breast cancer and benign tumors, both the images sample was error processing. If you use a program that implements this with the algorithm proposed in this study it is helpful to reading breast images, and it is considered to contribute significantly to the early detection of breast cancer.