• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1264-1272
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• 2012

Three-dimensional volume rendering method which shows the inside of human body is widely used in medical imaging area. Existing medical imaging system using a volume rendering method already has provided a variety of three-dimensional results. Recently existing results in the medical imaging among physicians and patients to facilitate communication have been studied since smart device which has advantage of portability applied in the medical imaging. In this paper, we propose 3D volume visualization system for a relatively low spec portable smart devices by using 2D textures and we also implements 2D diagnostic images of portable medical imaging visualization system.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.158-162
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• 1999

This thesis presents applications of three dimensional visualization technique based on shear-warp volume rendering to medical information. Volume rendering is compared to surface rendering and acceleration technique is also presented. The presented rendering techniques by using three-dimensional arrays of data are a widely used representation for computational fluid dynamics and geological structures as well as medical information.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.145-146
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• 2006

Recently, the next-generation advanced flow visualization techniques such as holographic PIV, dynamic PIV, echo-PIV, micro/nano-PIV, and X-ray PIV have been introduced. These advanced measurement techniques have a big potential as the core technology for analyzing outmost thermo-fluid flows in future. These would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT (Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is impossible for conventional measurement methods to observe most complicated nano- and bio-fluidic phenomena. In this presentation, the basic principle of these high-tech flow visualization techniques and their practical applications which cannot be resolved by conventional methods, such as blood flows in a micro-tube, in vivo analysis of micro-circulation, and flow around a living body will be introduced as a blue ocean strategy.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.14-17
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• 2008

Recently, several advanced flow visualization techniques such as Particle Image Velocimetry (PIV) including stereo PIV, holographic PIV, and dynamic PIV have been developed. These advanced techniques have strong potential as the experimental technology which can be used for verifying numerical simulation. In addition, there would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the basic research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is difficult for conventional methods to observe most complicated nano- and bio-fluidic phenomena. In this paper, the basic principle of these advanced visualization techniques and their practical applications which cannot be resolved by conventional methods, such as flow in automotive HVAC system, ship and propeller wake, three-dimensional flow measurement in micro-conduits, and flow around a circulating cylinder will be introduced.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.14-17
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• 2008

Recently, several advanced flow visualization techniques such as Particle Image Velocimetry (PIV) including stereo PIV, holographic PIV, and dynamic PIV have been developed. These advanced techniques have strong potential as the experimental technology which can be used for verifying numerical simulation. In addition, there would be indispensable in solving complicated thermo-fluid flow problems not only in the industrial fields such as automotive, space, electronics, aero- and hydro-dynamics, steel, and information engineering, but also in the basic research fields of medical science, bio-medical engineering, environmental and energy engineering etc. Especially, NT (Nano Technology) and BT (Bio Technology) strongly demand these advanced measurement techniques, because it is difficult for conventional methods to observe most complicated nano- and bio-fluidic phenomena. In this paper, the basic principle of these advanced visualization techniques and their practical applications which cannot be resolved by conventional methods, such as flow in automotive HVAC system, ship and propeller wake, three-dimensional flow measurement in micro-conduits, and flow around a circulating cylinder will be introduced.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.35-42
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• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.87-94
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• 2017

Due to improvements in the capabilities of commercial game engines, there are increasing instances of applying game engines to scientific visualization applications. This study describes a case of creating a virtual reality application that visualizes medical volume data based on the Unity3D game engine. When using a game engine, there is an advantage that various functions required for an application are basically provided, such as depth sorting of translucent objects or virtual reality hardware support. On the other hand, there is a restriction that the structure of the application program should be modified to suit the characteristics of the game engine. This paper describes a method for visualizing medical volume data using the structure of a game engine. As a result, we were able to create a virtual reality scene that consisted of surface data and medical volume data fragments together. And we confirmed the possibility of game engine as a future medical simulation production tool.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.207-214
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• 2015

In this paper, we proposed new software for 3D rendering of MR images in the medical domain using C# wrapper of Visualization Toolkit (VTK) and Microsoft .NET framework. Our objective in developing this software was to provide medical image segmentation, 3D rendering and visualization of hippocampus for diagnosis of Alzheimer disease patients using DICOM Images. Such three dimensional visualization can play an important role in the diagnosis of Alzheimer disease. Segmented images can be used to reconstruct the 3D volume of the hippocampus, and it can be used for the feature extraction, measure the surface area and volume of hippocampus to assist the diagnosis process. This software has been designed with interactive user interfaces and graphic kernels based on Microsoft.NET framework to get benefited from C# programming techniques, in particular to design pattern and rapid application development nature, a preliminary interactive window is functioning by invoking C#, and the kernel of VTK is simultaneously embedded in to the window, where the graphics resources are then allocated. Representation of visualization is through an interactive window so that the data could be rendered according to user's preference.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.109-116
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• 2003

In this paper, a CORBA-based collaborative medical image analysis and visualization system, which provides high accessibility and usability of the system for the users on distributed environment is introduced. The system allows us to manage datasets and manipulates medical images such as segmentation and volume visualization of computed geometry from biomedical images in distributed environments. Using Bayesian classification technique and an active contour model the system provides classification results of medical images or boundary information of specific tissue. Based on such information, the system can create real time 3D volume model from medical imagery. Moreover, the developed system supports collaborative work among multiple users using broadcasting and synchronization mechanisms. Since the system is developed using Java and CORBA, which provide distributed programming, the remote clients can access server objects via method invocation, without knowing where the distributed objects reside or what operating system it executes on.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.