• Journal of the Korean Society of Visualization
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• v.12 no.3
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• pp.9-14
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• 2014

Two-photon microscopy (TPM) has been used in plant research as a high-resolution high-depth 3D imaging modality. However, TPM is known to induce photo-damage to the plant in case of long time exposure, and optimal excitation wavelength for plant imaging has not been investigated. Longer excitation wavelength may be appropriate for in vivo two-photon imaging of Arabidopsis thaliana leaves, and effects of longer excitation wavelength were investigated in terms of imaging depth, emission spectrum. Changes of emission spectrum as a function of exposure time at longer excitation wavelength were measured for in vivo longitudinal imaging. Imaging depth was not changed much probably because photon scattering at the cell wall was a limiting factor. Chloroplast emission spectrum showed its intensity peak shift by 20 nm with transition of excitation wavelength from 849 nm or below to 850 nm or higher. Emission spectrum showed different change patterns with excitation wavelengths in longitudinal imaging. Longer excitation wavelengths appeared to interact with chloroplasts differently in comparison with 780 nm excitation wavelength, and may be good for in vivo imaging.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.198-212
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• 2021

Placenta accreta spectrum (PAS) is an abnormal placental adherence or invasion of the myometrium or extrauterine structures. As PAS is primarily staged and managed surgically, imaging can only guide and facilitate diagnosis. But, imaging can aid in preparations for surgical complexity in some cases of PAS. Ultrasound remains the imaging modality of choice; however, magnetic resonance imaging (MRI) is required for evaluation of areas difficult to visualize on ultrasound, and the assessment of the extent of placenta accreta. Numerous MRI features of PAS have been described, including dark intraplacental bands, placental bulge, and placental heterogeneity. Failure to diagnose PAS carries a risk of massive hemorrhage and surgical complications. This article describes a comprehensive, step-by-step approach to diagnostic imaging and its potential pitfalls.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.517-527
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• 1997

Magnetic Resonance Spectroscopic Imaging is a methodology combining the imaging and spectroscopy. It can provide the spectrum of each areas of image so that one can easily compare the spectrum of one position to another position of the image. In this study, we developed pulse sequence or the spectroscopic imaging method, RF wave forms or the saturation of water signal, computer simulations to validate our method, and confirmed the methodology with phantom experiment. Then we applied the spectroscopic method to human subject and identified a few important metabolites in in vivo. To develope a water saturating RF waveform, we used Shinnar-Le-Roux algorithm and obtained maximum phase RF waveform. With this RF pulse, it could suppress the water signal to 1:1000. The magnet is shimmed to under 1.0ppm with auto-shimming technique. The saturation bandwidth is 80Hz(2ppm). The water and fat seperation is 3.3ppm(about 140Hz at 1 Tesla magnet), the bandwidth is enough to resolve the difference. But we are more concerned about the narrow window in between the two peaks, in which the small quantity of metabolites reside. We performed the computer simulation and phantom experiments in 8*8 matrix form and showed good agreement in the image and spectrum. Finally we applied spectroscopic imaging to the brain of human subject. Only the lipid signal was shown in the periphery region which agrees with the at distribution in human head surface area. The spectrum inside the brain shows the important metabolites such as NAA, Cr/PCr, Choline. We here have shown the spectroscopic imaging which is normally done above 1.5 Tesla machine can be performed in the 1 Tesla Magnetic Resonance Imaging Unit.

• Journal of radiological science and technology
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• v.32 no.1
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• pp.17-24
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• 2009

Noise evaluation for an image has been performed by root mean square (RMS) granularity, autocorrelation function (ACF), and Wiener spectrum. RMS granularity stands for standard deviation of photon data and ACF is acquired by integration of 1 D function of distance variation. Fourier transform of ACF results in noise power spectrum which is called Wiener spectrum in image quality evaluation. Wiener spectrum represents noise itself. In addition, along with MTF, it is an important factor to produce detective quantum efficiency (DQE). The proposed evaluation method using Wiener spectrum is expected to contribute to educate the concept of Wiener spectrum in educational organizations, choose the appropriate imaging detectors for clinical applications, and maintain image quality in digital imaging systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.212-218
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• 2013

This paper presents an SVD(Singular Value Decomposition)-Pseudo Spectrum method for SAR (Synthetic Aperture Radar) imaging. The purpose of this work is to improve resolution and target separability of SAR images. This paper proposes SVD-Pseudo Spectrum method whose advantages are noise robustness, reduction of sidelobes and high resolution of spectral estimation. SVD-Pseudo Spectrum method uses Hankel Matrix of signal components and SVD (Singular Value Decomposition) method. In this paper, it is demonstrated that the SVD-Pseudo Spectrum method shows better performance than the matched filtering method and the conventional super-resolution based multiple signal classification (MUSIC) method in SAR image processing. The targets to be separated are modeled, and this modeled data is used to demonstrate the performance of algorithms.

• Proceedings of the Optical Society of Korea Conference
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• 2006.02a
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• pp.359-360
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• 2006

Functional photoacoustic tomography is a new non-invasive imaging modality, and it is emerging as a very practical method for imaging biological tissue structures by means of laser-induced ultrasound. Structures with high optical absorption, such as blood vessels, can be imaged with the spatial resolution of ultrasound, which is not limited by the strong light scattering in biological tissues. By varying wavelengths of the laser light and acquiring photoacoustic images, optical absorption spectrum of each image pixel is found. Since the biochemical constituents of tissues determine the spectrum, useful functional information like oxygen saturation ($SO_2$) and total haemoglobin concentration (HbT) can be extracted. In this study, as a proof-of-principle experiment, hypoxic brain tumor vasculature and traumatic brain injury (TBI) of small animal brain are imaged with functional photoacoustic tomography. High resolution brain vasculature images of oxygen saturation and total hemoglobin concentration are provided to visualize hypoxic tumor vasculature, and hemorrhage on the cortex surface by the TBI.

• Smart Structures and Systems
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• v.22 no.2
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• pp.209-221
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• 2018

Efflorescence is a phenomenon primarily caused by a carbonation process in concrete structures. Efflorescence can cause concrete degradation in the long term; therefore, it must be accurately assessed by proper inspection. Currently, the assessment is performed on the basis of visual inspection or image-based inspection, which may result in the subjective assessment by the inspectors. In this paper, a novel approach is proposed for the objective and quantitative assessment of concrete efflorescence using hyperspectral imaging (HSI). HSI acquires the full electromagnetic spectrum of light reflected from a material, which enables the identification of materials in the image on the basis of spectrum. Spectral angle mapper (SAM) that calculates the similarity of a test spectrum in the hyperspectral image to a reference spectrum is used to assess efflorescence, and the reference spectral profiles of efflorescence are obtained from theUSGS spectral library. Field tests were carried out in a real building and a bridge. For each experiment, efflorescence assessed by the proposed approach was compared with that assessed by image-based approach mimicking conventional visual inspection. Performance measures such as accuracy, precision, and recall were calculated to check the performance of the proposed approach. Performance-related issues are discussed for further enhancement of the proposed approach.

• 대한방사선방어학회:학술대회논문집
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• 2011.04a
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• pp.136-137
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• 2011

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.176-190
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• 2018

This paper presents a novel convolutional neural network based multi-feature fusion learning method for non-rigid 3D model retrieval, which can investigate the useful discriminative information of the heat kernel signature (HKS) descriptor and the wave kernel signature (WKS) descriptor. At first, we compute the 2D shape distributions of the two kinds of descriptors to represent the 3D model and use them as the input to the networks. Then we construct two convolutional neural networks for the HKS distribution and the WKS distribution separately, and use the multi-feature fusion layer to connect them. The fusion layer not only can exploit more discriminative characteristics of the two descriptors, but also can complement the correlated information between the two kinds of descriptors. Furthermore, to further improve the performance of the description ability, the cross-connected layer is built to combine the low-level features with high-level features. Extensive experiments have validated the effectiveness of the designed multi-feature fusion learning method.

• Journal of radiological science and technology
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• v.44 no.1
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• pp.31-37
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• 2021

This study aim of quantitative assessment of Noise Power Spectrum(NPS) and image characteristics of by acquired the optimal image for noise characteristics and quality assurance by using magnetic resonance imaging(MRI). MRI device was (MAGNETOM Vida 3.0T MRI; Siemense healthcare system; Germany) used and the head/neck shim MR receive coil were 20 channels coil and a diameter 200 mm hemisphere phantom. Frequency signal could be acquired the K-space trajectory image and white image for NPS. The T2 image highest quantitatively value for NPS finding of showed the best value of 0.026 based on the T2 frequency of 1.0 mm-1. The NPS acquired of showed that the T1 CE turbo image was 0.077, the T1 CE Conca2 turbo image was 0.056, T1 turbo image was 0.061, and the T1 Conca2 turbo image was 0.066. The assessment of NPS image characteristics of this study were to that could be used efficiently of the MRI and to present the quantitative evaluation methods and image noise characteristics of 3.0T MRI.