• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2375-2378
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• 2014

Cancer, like any disease, is a pathologic biological process. Drugs are designed to interfere with the pathologic process and should therefore also be validated using a functional screening method directed at these processes. Screening for cancers at an appropriate time and also evaluating results is also very important. Volumetric measurement helps in better screening and evaluation of tumors. Volumetry is a process of quantification of the tumors by identification (pre-cancerous or target lesion) and measurement. Volumetric image analysis allows an accurate, precise, sensitive, and medically valuable assessment of tumor response. It also helps in identifying possible outcomes such disease progression (PD) or complete response as per Response Evaluation Criteria in Solid Tumors (RECIST).

• Current Optics and Photonics
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• v.6 no.6
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• pp.550-564
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• 2022

Optical microscopy is a useful tool for study in the biological sciences. With an optical microscope, we can observe the micro world of life such as tissues, cells, and proteins. A fluorescent dye or a fluorescent protein provides an opportunity to mark a specific target in the crowd of biological samples, so that an image of a specific target can be observed by an optical microscope. The optical microscope, however, is constrained in resolution due to diffraction limit. Super-resolution microscopy made a breakthrough with this diffraction limit. Using a super-resolution microscope, many biomolecules are observed beyond the diffraction limit in cells. In the case of volumetric imaging, the super-resolution techniques are only applied to a limited area due to long imaging time, multiple scattering of photons, and sample-induced aberration in deep tissue. In this article, we review recent advances in super-resolution microscopy for volumetric imaging. The super-resolution techniques have been integrated with various modalities, such as a line-scan confocal microscope, a spinning disk confocal microscope, a light sheet microscope, and point spread function engineering. Super-resolution microscopy combined with adaptive optics by compensating for wave distortions is a promising method for deep tissue imaging and biomedical applications.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.180-187
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• 2021

In this paper, we present a computational volumetric reconstruction method for three-dimensional (3D) photon counting imaging with enhanced visual quality when low-resolution elemental images are used under photon-starved conditions. In conventional photon counting imaging with low-resolution elemental images, it may be difficult to estimate the 3D scene correctly because of a lack of scene information. In addition, the reconstructed 3D images may be blurred because volumetric computational reconstruction has an averaging effect. In contrast, with our method, the pixels of the elemental image rearrangement technique and a Bayesian approach are used as the reconstruction and estimation methods, respectively. Therefore, our method can enhance the visual quality and estimation accuracy of the reconstructed 3D images because it does not have an averaging effect and uses prior information about the 3D scene. To validate our technique, we performed optical experiments and demonstrated the reconstruction results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.557-561
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• 2009

This paper presents a prototype of high resolution 3D display with a new principle. We have proposed a new 3D display which has the features of both Integral Imaging (II) and volumetric display. The proposed display consists of two lens arrays and a thin volumetric display. When the viewer watches a thin volumetric display through two lens array, he can perceive a thick 3D image. In other words the two lens arrays can play a role of a convex lens which has a large diameter as a amplification of a depth. The advantage of the proposed display is that it has higher resolution than II and it is smaller than volumetric display with a large convex lens. In this paper, we show a detail of a prototype 3D display. We took various errors into consideration when we simulated 3D display and we found suitable lenses parameter from the simulation result. Then we confirm that the prototype will be able to reconstruct 3D images.

• Journal of Biomedical Engineering Research
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• v.27 no.3
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• pp.110-116
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• 2006

Finite element method (FEM) provides several advantages over other numerical methods such as boundary element method, since it allows truly volumetric analysis and incorporation of realistic electrical conductivity values. Finite element mesh generation is the first requirement in such in FEM to represent the volumetric domain of interest with numerous finite elements accurately. However, conventional mesh generators and approaches offered by commercial packages do not generate meshes that are content-adaptive to the contents of given images. In this paper, we present software that has been implemented to generate content-adaptive finite element meshes (cMESHes) based on the contents of MR images. The software offers various computational tools for cMESH generation from multi-slice MR images. The software named as the Content-adaptive FE Mesh Generation Toolbox runs under the commercially available technical computation software called Matlab. The major routines in the toolbox include anisotropic filtering of MR images, feature map generation, content-adaptive node generation, Delaunay tessellation, and MRI segmentation for the head conductivity modeling. The presented tools should be useful to researchers who wish to generate efficient mesh models from a set of MR images. The toolbox is available upon request made to the Functional and Metabolic Imaging Center or Bio-imaging Laboratory at Kyung Hee University in Korea.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3E
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• pp.107-110
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• 2010

In this paper, the rationale and contents of the special issue of the Journal of the Acoustical Society of Korea regarding comprehensive reviews on past, present and future of biomedical ultrasound are described. Brief descriptions of invited articles are given, and efforts by all contributing authors are gratefully acknowledged.

• Proceedings of the Optical Society of Korea Conference
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• 2005.07a
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• pp.150-151
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• 2005

Integral imaging is one of the three-dimensional(3D) display methods, which is an autostereoscopic method. The integral imaging system can provide volumetric 3D image which has both vertical and horizontal parallaxes. The elemental image which is obtained in the pickup process by lens array has the 3D information of the object and can be used for the depth perception and the 3D correlation. Moreover, the elemental image which represents a cyber-space can be generated by computer process.

• Proceedings of the Optical Society of Korea Conference
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• 2008.02a
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• pp.181-182
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• 2008

In this paper, we propose a volumetric computational reconstruction method by use of smart pixel mapping technique in the computational integral imaging in order to overcome the problem of resolution degradation. The experimental results are presented to show the usefulness of our proposed technique.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.227-234
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• 2002

This study was conducted to nondestructively estimate the volumetric information of peach and pit and to visualize the 3D information of internal structure from magnetic resonance imaging(MRI) data. Bruker Biospec 7T spectrometer operating at a proton reosonant frequency of 300 MHz was used for acquisition of MRI data of peach. Image processing algorithms and visualization techniques were implemented by using MATLAB (Mathworks) and Visualization Toolkit(Kitware), respectively. Thresholding algorithm and Kohonen's self organizing map(SOM) were applied to MRI data fur region segmentation. Volumetric information were estimated from segemented images and compared to the actual measurements. The average prediction errors of peach and pit volumes were 4.5%, 26.1%, respectively for the thresholding algorithm. and were 2.1%, 19.9%. respectively for the SOM. Although we couldn't get the statistically meaningful results with the limited number of samples, the average prediction errors were lower when the region segmentation was done by SOM rather than thresholding. The 3D visualization techniques such as isosurface construction and volume rendering were successfully implemented, by which we could nondestructively obtain the useful information of internal structures of peach.

• Investigative Magnetic Resonance Imaging
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• v.14 no.1
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• pp.56-63
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• 2010

Purpose : DIR image is relatively free from susceptibility artifacts therefore, DIR image can make it possible to reliably measure cortical thickness/volume. One drawback of the DIR acquisition is the long scan time to acquire the fully sampled 3D data set. To solve this problem, we applied a parallel imaging method (GRAPPA) and verify the reliability of using the volumetric study. Materials and methods : Six healthy volunteers (3 males and 3 females; age $25.33{\pm}2.25$ years) underwent MRI using the 3D DIR sequence at a 3.0T Siemens Tim Trio MRI scanner. GRAPPA simulation was performed from the fully sampled data set for reduction factor 2. Data reconstruction was performed using MATLAB R2009b. Freesurfer v.4.3.0 was used to evaluate the cortical thickness of the entire brain, and to extract white matter information from the DIR image, Analyze 9.0 was used. The global cortical thickness estimated from the reconstructed image was compared with reference image by using a T-test in SPSS. Results : Although reduced SNR and blurring are observed from the reconstructed image, in terms of segmentation the effect was not so significant. The volumetric result was validated that there were no significant differences in many cortical regions. Conclusion : This study was performed with DIR image for a volumetric MRI study. To solve the long scan time of 3D DIR imaging, we applied GRAPPA algorithm. According to the results, fast imaging can be done with reduction factor 2 with little loss of image quality at 3.0T.