• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1623-1626
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• 2005

초음파 영상 기법은 장기, 연조직, 혈류를 검사하는데 쓰이는 영상 진단법이다. 초음파 장비를 통해 얻어진 초음파 볼륨 데이터는 장비 특성상 많은 잡음(speckle noise)을 포함하기 때문에, 깨끗한 영상을 얻기 위해서는 잡음 필터링(noise filtering)이 필요하다. 그런데, 볼륨 데이터 모든 영역에 대해 잡음 필터링을 적용할 경우 전처리 시간이 길어져 실시간으로 초음파 볼륨 데이터를 렌더링하기 어렵다. 본 논문에서는 실시간으로 입력되는 초음파 볼륨 데이터를 가시화 하기위하여 전처리 시간 없이 잡음을 제거하는 방법을 제안한다. 전처리 시간에 전체 볼륨 데이터에 대해 잡음 필터링을 적용하지 않고, 영상을 생성하는 동안 참조되는 복셀(voxel)에 대해서만 잡음 필터를 적용하여 얻은 값을 사용한다. 이때 필터링에 소요되는 시간을 최소화하기 위해 가장 단순한 평균화 필터를 사용한다. 그리고 복셀에 적용되는 3차원 필터를 3단계의 1차원 필터 연산 단계로 분할 한 후, 각 단계별 연산을 거친 복셀들에 대해서는 다시 연산을 하지 않도록 하여 중복을 피한다. 이를 통해 전처리 시간 없이 기존 방법과 동일한 화질을 유지하는 최종 영상을 만들어 낸다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.117-126
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• 2008

Recent advances in medical imaging technologies have enabled the high-resolution data acquisition. Therefore visualization of such large data set on standard graphics hardware became a popular research theme. Among many visualization techniques, we focused on bricking method which divided the entire volume into smaller bricks and rendered them in order. Since it switches bet\W8n bricks on main memory and bricks on GPU memory on the fly, to achieve better performance, the number of these memory swapping conditions has to be minimized. And, because the original bricking algorithm was designed for regular volume data such as CT and MR, when applying the algorithm to ultrasound volume data which is based on the toroidal coordinate space, it revealed some performance degradation. In some areas near bricks' boundaries, an orthogonal viewing ray intersects the single brick twice, and it consequently makes a single brick memory to be uploaded onto GPU twice in a single frame. To avoid this redundancy, we divided the volume into bricks allowing overlapping between the bricks. In this paper, we suggest the formula to determine an appropriate size of these shared area between the bricks. Using our formula, we could minimize the memory bandwidth. and, at the same time, we could achieve better rendering performance.

• Journal of Korea Game Society
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• v.15 no.2
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• pp.159-168
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• 2015

This paper introduces effective noise removal method for medical ultrasound volume data. Ultrasound volume data need to be filtered because it has a lot of noise. Conventional 2d filtering methods ignore information of adjacent layers and conventional 3d filtering methods are slow or have simple filter that are not efficient for removing noise and also don't equally operate filtering because that don't take into account ultrasound' sampling character. To solve this problem, we introduce method that fast perform in parallel bilateral filtering that is known as good for noise removal and adjust proportionally window size depending on that's position. Experiments compare noise removal and loss of original data among average filtered or biliteral filtered or adaptive biliteral filtered ultrasound volume rendering images. In this way, we can more efficiently and correctly remove noise of ultrasound volume data.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.519-526
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• 2000

볼륨 렌더링은 3D 의료영상 데이터를 가시화하는 중용한 기법 중 하나이다. 그러나 볼륨 렌더링을 실시간으로 이룰 때, 많은 계산량을 필요로하는 것이 볼률 렌더링을 사용하는데 걸림돌이 되고 있다. 이 논문에서는 Superscalar와 VLIM(Very Long Instruction Word)의 구조를 가지고 있어 동시에 8개의 명령어 수행이 가능한 TI사의 TMS320C6201 DSP를 이용하여 3D 초음파 영상의 쉬어-웝 볼륨 렌더링을 구현하였다. 쉬어-웝 방법을 DSP 상에서 최적으로 구현하기 위하여 ray map 방법, one-to-four ray casting, ？디 skipping 방법을 제안하였다. 제안한 방법들을 이용한 볼륨 렌더링과 적용하지 않은 기존의 알고리즘을 DSP에 구현하여 PSNR과 렌더링 시간의 비교·평가를 통해 만족할 만한 영상 화질에 빠른 렌더링 성능을 얻을 수 있음을 보여주었다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.51-58
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• 2005

This paper proposes an efficient algorithm for extracting a tumor region from an breast ultrasound volume image by using rate-distortion (R-D) based seeded region growing. In the proposed algorithm the rate and the distortion represent the roughness of the contour and the dissimilarity of pixels in a region, respectively. Staring from an initial seed region set in each cutting plane of a volume, a pair of the seed region and one of adjacent regions whose R-D cost is minimal is searched and then they are merged into a new updated seed region. This procedure is recursively performed until the averaged R-D cost values per the number of contour pixels in the seed region becomes maxim. As a result, the final seed region has good pixel homogeneity and a much smooth contour. Finally, the tumor volume is extracted using the contours of the final seed regions in all the cutting planes. Experimental results show that the averaged error rate of the proposed method is shown to be below 4%.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.59-68
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• 2003

3-D data modeling of a volumetric scattered data is highly demanded for geological structure inspection, environment visualization and supersonic testing. The data used in these area are generally irregularly scattered in a volume data space, which are much different from the structured points data (cuberille data) used in Marching cube algorithm. In this paper, first we explore a volume modeling method for the scattered data based on tetrahedral domain. Next we propose a method for solving the ambiguity of tetrahedral domain decision using asymptotic decider criterion. Last we implement a simple visualization system based on the proposed asymptotic decider criterion and compare it with a system based on sphere criterion. In deciding tetrahedral domain, sphere criterion considers only positional values but asymptotic decider criterion considers not only positional values but also functional values, so asymptotic decider criterion is more accurate on deciding tetrahedral domain than sphere criterion.