• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.87-97
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• 2018

Maximum intensity projection (MIP) is a common visualization technique in medical imaging system. A typical method to improve the performance of MIP is empty space leaping, which skips unnecessary area. This research proposes a new method to improve the existing empty space leaping. In order to skip more regions, we introduce a variety of acceleration strategies that use some tolerance given by the user to take part in image quality loss. Each proposed method shows various image quality and speed, and this study compares them to select the best one. Experimental results show that it is most efficient to add a constant tolerance function when the image quality required by the user is low. Conversely, when the user required image quality is high, a function with a low tolerance of volume center is most effective. Applying the proposed method to general MIP visualization can generate a relatively high quality image in a short time.

• Journal of Korea Multimedia Society
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• v.10 no.3
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• pp.316-324
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• 2007

Maximum Intensity Projection (MIP) identifies patients' anatomical structures from MR or CT data sets. Recently, it becomes possible to generate MIP images with interactive speed by exploiting Graphics Processing Unit (GPU) even in large volume data sets. Generally, volume boundary plane is obliquely crossed with view-aligned texture plane in hardware-texture based volume rendering. Since the ray sampling distance is not increased at volume boundary in volume rendering, the aliasing problem occurs due to data loss. In this paper, we propose an efficient method to overcome this problem by Re-rendering volume boundary planes. Our method improves image quality to make dense distances between samples near volume boundary which is a high frequency area. Since it is only 6 clipping planes are additionally needed for Re-rendering, high quality rendering can be performed without sacrificing computational efficiency. Furthermore, our method couldbe applied to Minimum Intensity Projection (MinIP) volume rendering.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.484-488
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• 1997

In this Paper, We use Maximum-Intensity Projection(MIP) algorithms. Maximum-Intensity Projection algorithms currently used for construction of magnetic resonance angiograms. The blood flow in a volume of interest is represented by bright intensities in the MR data volume. The flow within the vasculature shows up in the projections plane. By relating the intensities of the pixel to their location in the slice, the total number of pixels considered for the projection plane was reduced, thus saving calculation time. The algorithm was written in visual C++.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.512-520
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• 2009

Maximum intensity projection (MIP) is a volume rendering method which extracts maximum values along the viewing direction through volume data. It visualizes high-density structures, such as angio-graphic datasets so that it is frequently used in medical imaging systems. We have proposed an efficient two-step MIP acceleration method that uses the recent CPUs. First, we exploited SIMD instructions to reduce conditional branch instructions which take up a considerable part of whole rendering process, so that we improved rendering speed. Second, we proposed a new method, which accesses volume and image data successively by modifying the shear-warp rendering. This method improves memory access patterns so that cache misses are reduced. Using the current CPUs, our method improved the rendering speed by a factor of 7 than that of the shear-warp rendering.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.2
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• pp.123-130
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• 2016

Purpose : The aim of this study was to compare the differences between the volumes acquired with four-dimensional computed tomography (4DCT)images with a reconstruction image-filtering algorithm and cone-beam computed tomography (CBCT) images with dynamic phantom. Materials and Methods : The 4DCT images were obtained from the computerized imaging reference systems (CIRS) phantom using a computed tomography (CT) simulator. We analyzed the volumes for maximum intensity projection (MIP), minimum intensity projection (MinIP) and average intensity projection (AVG) of the images obtained with the 4DCT scanner against those acquired from CBCT images with CT ranger tools. Results : Difference in volume for node of 1, 2 and 3 cm between CBCT and 4DCT was 0.54~2.33, 5.16~8.06, 9.03~20.11 ml in MIP, respectively, 0.00~1.48, 0.00~8.47, 1.42~24.85 ml in MinIP, respectively and 0.00~1.17, 0.00~2.19, 0.04~3.35 ml in AVG, respectively. Conclusion : After a comparative analysis of the volumes for each nodal size, it was apparent that the CBCT images were similar to the AVG images acquired using 4DCT.

• Investigative Magnetic Resonance Imaging
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• v.15 no.1
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• pp.77-81
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• 2011

It is a well-known clinical fact that contrast-enhanced magnetic resonance angiography exaggerates vertebral arterial ostial stenosis and sometimes shows pseudostenosis. Considering the clinical significance of a lesion in the posterior circulation ischemia, the importance of an accurate imaging diagnosis of ostial stenosis should not be underestimated. We were able to differentiate pseudo stenosis of the ostium from true stenosis using thin-slab maximum-intensity-projection(MIP) images which are thought to be helpful for minimizing standard full thickness MIP images.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.286-289
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• 2002

뇌 혈관 영상은 2D로 되어있어 임상에서 뇌의 이상 유무와 질병의 진행 정도를 판별하는데 어려움이 있다. Volume Rendering은 2차원 데이터를 3차원 영상으로 재구성하여 오브젝트의 내부 모습을 3차원으로 볼 수 있게 해주는 장점이 있어 진단에 도움을 줄 수가 있다. MRA(Magnetic Resonance Angiography) 는 MRI(Magnetic Resonance Imaging)을 이용하여 Vascular Imaging 하는 기법이다. MRA 혈관 영상을 가시화하는 방법으로 MIP(Maximum Intensity Projection)를 이용하였다. 본 논문에서는 256×256 크기의 MRA영상 48장을 MIP 로 볼륨 랜더링하여 뇌 혈관 영상을 3차원으로 가시화 하였다.

• Radiation Oncology Journal
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• v.35 no.3
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• pp.274-280
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• 2017

Purpose: To see the gross tumor volume (GTV) dependency according to the phase selection and reconstruction methods, we measured and analyzed the changes of tumor volume and motion at each phase in 20 cases with lung cancer patients who underwent image-guided radiotherapy. Materials and Methods: We retrospectively analyzed four-dimensional computed tomography (4D-CT) images in 20 cases of 19 patients who underwent image-guided radiotherapy. The 4D-CT images were reconstructed by the maximum intensity projection (MIP) and the minimum intensity projection (Min-IP) method after sorting phase as 40%-60%, 30%-70%, and 0%-90%. We analyzed the relationship between the range of motion and the change of GTV according to the reconstruction method. Results: The motion ranges of GTVs are statistically significant only for the tumor motion in craniocaudal direction. The discrepancies of GTV volume and motion between MIP and Min-IP increased rapidly as the wider ranges of duty cycles are selected. Conclusion: As narrow as possible duty cycle such as 40%-60% and MIP reconstruction was suitable for lung cancer if the respiration was stable. Selecting the reconstruction methods and duty cycle is important for small size and for large motion range tumors.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.623-632
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• 2009

In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.981-991
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• 2011

MIP(Maximum Intensity Projection) is a volume rendering technique which is essential for the medical imaging system. MIP rendering based on the ray casting method produces high quality images but takes a long time. Our aim is improvement of the rendering speed using GPGPU(General-purpose computing on Graphic Process Unit) technique. In this paper, we present the ray casting algorithm based on CUDA(an acronym for Compute Unified Device Architecture) which is a programming language for GPGPU and we suggest new acceleration methods for CUDA. In detail, we propose the block based space leaping which skips unnecessary regions of volume data for CUDA, the bisection method which is a fast method to find a block edge, and the initial value estimation method which improves the probability of space leaping. Due to the proposed methods, we noticeably improve the rendering speed without image quality degradation.