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신윤주,장원,예종철,강은희,오동열,이윤진,박지훈,김영훈 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.3
Objective: To compare the image quality of low-dose (LD) computed tomography (CT) obtained using a deep learning-based denoising algorithm (DLA) with LD CT images reconstructed with a filtered back projection (FBP) and advanced modeled iterative reconstruction (ADMIRE). Materials and Methods: One hundred routine-dose (RD) abdominal CT studies reconstructed using FBP were used to train the DLA. Simulated CT images were made at dose levels of 13%, 25%, and 50% of the RD (DLA-1, -2, and -3) and reconstructed using FBP. We trained DLAs using the simulated CT images as input data and the RD CT images as ground truth. To test the DLA, the American College of Radiology CT phantom was used together with 18 patients who underwent abdominal LD CT. LD CT images of the phantom and patients were processed using FBP, ADMIRE, and DLAs (LD-FBP, LD-ADMIRE, and LD-DLA images, respectively). To compare the image quality, we measured the noise power spectrum and modulation transfer function (MTF) of phantom images. For patient data, we measured the mean image noise and performed qualitative image analysis. We evaluated the presence of additional artifacts in the LD-DLA images. Results: LD-DLAs achieved lower noise levels than LD-FBP and LD-ADMIRE for both phantom and patient data (all p < 0.001). LD-DLAs trained with a lower radiation dose showed less image noise. However, the MTFs of the LD-DLAs were lower than those of LD-ADMIRE and LD-FBP (all p < 0.001) and decreased with decreasing training image dose. In the qualitative image analysis, the overall image quality of LD-DLAs was best for DLA-3 (50% simulated radiation dose) and not significantly different from LD-ADMIRE. There were no additional artifacts in LD-DLA images. Conclusion: DLAs achieved less noise than FBP and ADMIRE in LD CT images, but did not maintain spatial resolution. The DLA trained with 50% simulated radiation dose showed the best overall image quality.
Wavelet Power Spectrum Estimation for High-resolution Terahertz Time-domain Spectroscopy
김영찬,진경환,예종철,안재욱,이대수 한국광학회 2011 Current Optics and Photonics Vol.15 No.1
Recently reported asynchronous-optical-sampling terahertz (THz) time-domain spectroscopy enables high-resolution spectroscopy due to a long time-delay window. However, a long-lasting tail signal following the main pulse is often measured in a time-domain waveform, resulting in spectral fluctuation above a background noise level on a high-resolution THz amplitude spectrum. Here, we adopt the wavelet power spectrum estimation technique (WPSET) to effectively remove the spectral fluctuation without sacrificing spectral features. Effectiveness of the WPSET is verified by investigating a transmission spectrum of water vapor.
High Resolution Time Resolved Contrast Enhanced MR Angiography Using k-t FOCUSS
정홍,김응엽,예종철 대한자기공명의과학회 2010 Investigative Magnetic Resonance Imaging Vol.14 No.1
Purpose : Recently, the Recon Challenge at the 2009 ISMRM workshop on Data Sampling and Image Reconstruction at Sedona, Arizona was held to evaluate feasibility of highly accelerated acquisition of time resolved contrast enhanced MR angiography. This paper provides the step-by-step description of the winning results of k-t FOCUSS in this competition. Materials and Methods : In previous works, we proved that k-t FOCUSS algorithm successfully solves the compressed sensing problem even for less sparse cardiac cine applications. Therefore, using k-t FOCUSS, very accurate time resolved contrast enhanced MR angiography can be reconstructed. Accelerated radial trajectory data were synthetized from X-ray cerebral angiography images and provided by the organizing committee, and radiologists double blindly evaluated each reconstruction result with respect to the ground-truth data. Results : The reconstructed results at various acceleration factors demonstrate that each components of compressed sensing, such as sparsifying transform and incoherent sampling patterns, etc can have profound effects on the final reconstruction results. Conclusion : From reconstructed results, we see that the compressed sensing dynamic MR imaging algorithm, k-t FOCUSS enables high resolution time resolved contrast enhanced MR angiography.
박세희,정형진,예종철,이가영 대한안과학회 2024 대한안과학회지 Vol.65 No.1
목적: 낮은 명도 정보 기반 모델(dark channel prior)과 높은 명도 정보 기반 모델(bright channel prior)을 활용한 새로운 사전 정보복원 모델을 통해 흐림개선(dehazing)을 하여 일반 안저 사진의 품질을 개선함으로써 망막 질환의 진단을 더 정확하고 쉽게 하고자하였다. 대상과 방법: 2000년부터 2022년 9월까지 본원 환자들의 일반 안저 사진에 기존의 낮은 명도 정보 기반 모델과 제시된 보정 방식을적용해 보았다. 원본 사진, 낮은 명도 정보 기반 모델을 적용한 사진, 제시된 보정 방식을 적용한 사진, 백내장수술 후 흐림(haze)이개선된 사진을 비교하였고, 각 방법에서 유의미한 품질 개선이 이루어졌는지 보기 위해 피셔의 정확한 검정법을 사용하였다. 결과: 백내장 환자에서 낮은 명도 정보 기반 모델을 적용한 사진과 제시된 방법을 적용한 사진이 더 좋은 사진 품질을 보였으며, 제시된 방법을 적용한 경우의 품질이 더 좋았다. 동공이 작은 환자의 경우, 제시된 방법을 적용할 때 어둡게 보이던 망막과 혈관 부분이가시화되었으며, 백내장수술 후 얻은 사진에 더 가까운 모습을 보였다. 백내장 환자와 작은 동공 환자의 사진 모두에서 제시된 방법의품질 개선 비율이 각각 62.3%, 96.0%로 유의미하게 높았다(p-value<0.05). 결론: 본 연구에서 제안된 사전 정보 복원 모델 기반의 방법은 백내장이 있거나 동공이 작은 환자에게서 얻은 안저 사진의 대조도를높이고, 넓은 범위의 혈관과 병변을 가시화하여 임상에서 더 나은 진단과 치료를 할 수 있도록 도울 수 있을 것이다. Purpose: We present a dehazing algorithm using dark channel prior (DCP) and bright channel prior (BCP) to enhance the quality of retinal images obtained through conventional fundus photography. Methods: A retrospective analysis was conducted on retinal images from patients who visited Gangnam Sacred Heart Hospital between January 2000 and September 2022. These images were captured using a digital fundus camera (KOWA Nonmyd 8S Fundus Camera, KOWA Company, Nagoya, Japan) without pupil dilation. We used two mathematical algorithms: DCP only and DCP and BCP combined. The original, DCP-processed, and DCP & BCP-processed images were compared. Fisher's exact test was used to identify significant quality improvements. Results: The DCP and the newly proposed DCP plus BCP algorithm effectively eliminated haze and enhanced the contrast of cataract images. Notably, DCP demonstrated limited improvements in fundus photographs from patients with small pupils, whereas the proposed DCP plus BCP method effectively revealed previously obscured retinal details and vessels. However, these methods exhibited limited performance in severe cataracts compared to the clear images obtained after surgery. The quality enhancement with the proposed method was significant in photographs of patients with cataracts (p = 0.032) and small pupils (p < 0.01). Conclusions: Our algorithm produced clearer images of blood vessels and optic disc structures, while significantly reducing artifacts in fundus images from patients with small pupils or cataracts. The proposed algorithm can provide visually enhanced images, potentially aiding physicians in the diagnosis of retinal diseases in patients with cataracts.