• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.2
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• pp.78-84
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• 2007

Quantitative analysis of dynamic brain PET data using a tracer kinetic modeling has played important roles in the investigation of functional and molecular basis of various brain diseases. Parametric imaging of the kinetic parameters (voxel-wise representation of the estimated parameters) has several advantages over the conventional approaches using region of interest (ROI). Therefore, several strategies have been suggested to generate the parametric images with a minimal bias and variability in the parameter estimation. In this paper, we will review the several approaches for parametric imaging with linearized methods which include graphical analysis and mulilinear regression analysis.

• Investigative Magnetic Resonance Imaging
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• v.23 no.2
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• pp.148-156
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• 2019

Hyperglycemia-induced hemichorea (HGHC) is a rare but characteristic hyperkinetic movement disorder involving limbs on one side of the body. In a 75-year-old woman with a left-sided HGHC, conventional brain MR imaging showed very subtle T1-hyperintensity and unique gadolinium enhancement in the basal ganglia contralateral to movements. Multi-parametric MRI was acquired using pulse sequence with quantification of relaxation times and proton density by multi-echo acquisition. Myelin map was reconstructed based on new tissue classification modeling. In this case report of multi-parametric MRI, quantitative measurement of myelin change related to HGHC in brain structures and its possible explanations are presented. This is the first study to demonstrate myelin loss related to hyperglycemic insult in multi-parametric quantitative MR imaging.

• Current Optics and Photonics
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• v.7 no.4
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• pp.419-427
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• 2023

The structural design of an optical-telescope assembly (OTA) for satellite laser ranging (SLR) is conducted in two steps. First, the results of a parametric study of the major design variables (e.g. dimension and shape) of the OTA part are explained, and the detailed structural design of the OTA is derived, considering the design requirements. Among the structural-shape concepts of various OTAs, the Serrurier truss concept is selected in this study, and the collimation of the telescope according to the design variables is extensively discussed. After generating finite-element models for different structural shapes, self-gravity analyses are performed. To minimize the deflection and tilt of the mirror and frame for the OTA under the limited design requirements, a parametric study is conducted according to design variables such as the shapes of the upper and lower struts and the spider vane. The structural features found in the parametric study are described. Finally, the OTA structure is designed in detail to maintain the optical alignment by balancing the gravity deflections of the upper and lower trusses using the optimal combination of the parameters. Additionally, thermal analysis of the optical telescope design is evaluated.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.61.1-61.1
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• 2021

Squeezed light는 중력파 검출기의 양자 잡음을 줄여 측정의 민감도를 향상시키기 위해 사용하는 양자 광원이다. Squeezed light는 광학적 손실에 민감하기 때문에 중력파를 측정하기 위해서는 정밀한 mode matching이 필요하다. 하지만 mode mismatching은 실제 실험 상황에서 동적으로, 그리고 무작위로 나타나므로 정밀하게 조정하기 어렵다. Mode mismatching에 견고한 squeezed light를 만들기 위해서는 multimode squeezed light가 필요하다. Multimode squeezed light를 만드는 방법으로 는 self-imaging cavity를 이용하여 생성하는 방법이 대표적으로 알려져 있다. 이 발표에서는 self-imaging cavity 기반으로 만든 optical parametric oscillator(OPO) 에서 생성된 squeezed light가 기존 OPO로 생성한 squeezed light 보다 여러 spatial mode mismatching (위치, 방향, 크기 빗맞음)에 대해 견고함을 소개한다.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.736-746
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• 2016

In this paper, we propose an automatic prostate cancer detection method using position, signal intensity and texture feature based on SVM in multi-parametric MR images. First, to align the prostate on DWI and ADC map to T2wMR, the transformation parameters of DWI are estimated by normalized mutual information-based rigid registration. Then, to normalize the signal intensity range among inter-patient images, histogram stretching is performed. Second, to detect prostate cancer areas in T2wMR, SVM classification with position, signal intensity and texture features was performed on T2wMR, DWI and ADC map. Our feature classification using multi-parametric MR imaging can improve the prostate cancer detection rate on T2wMR.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2006.08a
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• pp.147-147
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• 2006

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.69-76
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• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.197-198
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• 2009