• 대한의용생체공학회:의공학회지
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• 제43권4호
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• pp.259-270
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• 2022

Artificial intelligence (AI) has been studied in various fields of medical imaging. Currently, top-notch deep learning (DL) techniques have led to high diagnostic accuracy and fast computation. However, they are rarely used in real clinical practices because of a lack of reliability concerning their results. Most DL models can achieve high performance by extracting features from large volumes of data. However, increasing model complexity and nonlinearity turn such models into black boxes that are seldom accessible, interpretable, and transparent. As a result, scientific interest in the field of explainable artificial intelligence (XAI) is gradually emerging. This study aims to review diverse XAI approaches currently exploited in medical imaging. We identify the concepts of the methods, introduce studies applying them to imaging modalities such as computational tomography (CT), magnetic resonance imaging (MRI), and endoscopy, and lastly discuss limitations and challenges faced by XAI for future studies.

• 전자공학회논문지SC
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• 제40권5호
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• pp.341-349
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• 2003

고속 디지털신호처리기를 사용한 자기공명영상 실시간 대화형 제어기(스펙트로미터)를 개발하였다. 개발린 제어기는 rf 파형과 경사자계 파형을 만들고, 신호 측정을 위한 다중 측정기를 제어한다. TMS320C6701과 간은 높은 계산 능력을 가진 디지털신호처리기를 사용함으로써 복잡한 경사자계파형의 실시간 계산 및 출력이 가능해졌다. 또한 회전 행렬을 실시간으로 계산함으로써 심장과 같이 움직임이 큰 장기의 실시간 영상에서 얻고자하는 평면을 대화식으로 조절이 가능해졌다. 개발된 스펙트로미터를 1.5 테슬라 전신자기공명 영상시스템에 성공적으로 적용하였다. 개발된 스펙트로미터를 고속스핀에코나 echo planar imaging(EPI) 등과 같은 초고속자기공명영상에 적용하여 성능을 검증하였다. 이것은 이들 초고속 자기공명영상기법들이 측정 시간을 단축해주는 대신에 스펙트로미터의 송신부와 수신부 또는 경사자계부간의 동기나 위상에 에러가 있을 경우 문제점을 크게 부각시켜 시스템의 성능 평가에 적합하기 때문이다.

• 한국정보통신학회논문지
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• 제20권1호
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• pp.167-174
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• 2016

본 논문에서는 3D 깊이우선 집적영상(DPII) 디스플레이에서 키넥트(Kinect)를 이용하여 3D 물체에 대한 2D 요소영상들을 생성하는 방법을 제안한다. 먼저, 깊이우선 집적영상에서의 요소영상 생성원리를 기하광학적으로 분석하고 이 분석에 기초하여 키넥트의 RGB영상과 깊이영상으로부터 요소영상들을 생성한다. 3D 영상 복원을 위해서 집적영상에 기반한 컴퓨터적 시점재생 실험을 수행하고, 복원된 3D 영상에 대한 많은 시점영상들을 서로 비교한다. 제안하는 방식의 유용함을 보이기 위해서 기초적인 광학적 실험을 수행하였다. 그 결과, 제안하는 방식은 완전시차를 가지는 올바른 3D 영상을 제공함을 확인하였다.

• 대한의용생체공학회:의공학회지
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• 제28권1호
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• pp.8-16
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• 2007

Finite element analysis (FEA) is an effective means for the analysis of bioelectromagnetism. It has been successfully applied to various problems over conventional methods such as boundary element analysis and finite difference analysis. However, its utilization has been limited due to the overwhelming computational load despite of its analytical power. We have previously developed a novel mesh generation scheme that produces FE meshes that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with far less number of nodes and elements, thus lessen the computational load. In general, the cMesh generation is affected by the quality of feature maps derived from MRI. In this study, we have tested various feature maps created based on the improved differential geometry measures for more effective cMesh head models. As performance indices, correlation coefficient (CC), root mean squared error (RMSE), relative error (RE), and the quality of cMesh triangle elements are used. The results show that there is a significant variation according to the characteristics of specific feature maps on cMesh generation, and offer additional choices of feature maps to yield more effective and efficient generation of cMeshes. We believe that cMeshes with specific and improved feature map generation schemes should be useful in the FEA of bioelectromagnetic problems.

• 한국광학회지
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• 제19권4호
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• pp.270-275
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• 2008

본 논문에서는 집적 영상의 획득과 복원을 통하여 장애물에 가려진 물체를 인식하는 기술은 제안하고 구현하였다. 집적 영상의 복원은 해당되는 화소 세기의1차 확률적 특성인 평균으로 구한다. 복원평면까지의 거리는 2차 확률적 특성인 표준 편차를 이용하여 구하고3차원 물체의 경계(edge)를 검출한다. 표준 편차의 합을 최소로 하는 거리에서 복원된 영상을 표적인식에 이용한다. 표적인식은 주성분 분석(principle component analysis, PCA) 분류기를 복원된 영상에 적용하였다. 표적 분류에 대한 판정은 분류기에 의해서 투영된 클래스의 평균 특징 벡터와 테스트 특징 벡터간의 유클리드 거리(Euclidean distance)를 이용한다. 실험 및 시뮬레이션을 통하여 가려진 표적을 본 논문에서 제안한 방법을 통하여 오차 없이 분류하였다.

• 한국전산유체공학회지
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• 제20권1호
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• pp.99-104
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• 2015

Aero-optic phenomena cause the image position displacement on an imaging plane of the airborne optical/IR systems. Particularly, the aero-optic boresight error(BSE) is important factor for homing, positioning and aiming applications of hypersonic flight interceptor missile. In this paper, an estimating method of aero-optic BSE for a hypersonic flight vehicle is studied. A ray tracing method and a transform method of refractive index fields from flow density fields are combined with computational fluid dynamics(CFD) method.

• Journal of information and communication convergence engineering
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• 제14권1호
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• pp.51-56
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• 2016

In this paper, we present a three-dimensional (3-D) automatic target recognition system based on optical integral imaging reconstruction. In integral imaging, elemental images of the reference and target 3-D objects are obtained through a lenslet array or a camera array. Then, reconstructed 3-D images at various reconstruction depths can be optically generated on the output plane by back-projecting these elemental images onto a display panel. 3-D automatic target recognition can be implemented using computational integral imaging reconstruction and digital nonlinear correlation filters. However, these methods require non-trivial computation time for reconstruction and recognition. Instead, we implement 3-D automatic target recognition using optical cross-correlation between the reconstructed 3-D reference and target images at the same reconstruction depth. Our method depends on an all-optical structure to realize a real-time 3-D automatic target recognition system. In addition, we use a nonlinear correlation filter to improve recognition performance. To prove our proposed method, we carry out the optical experiments and report recognition results.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• Journal of Applied and Pure Mathematics
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• 제5권5_6호
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

• 한국광학회:학술대회논문집
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• 한국광학회 2009년도 동계학술발표회 논문집
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• pp.251-252
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• 2009