• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.525-526
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• 2011

복부 MRI 영상에서 간의 인식은 간에 존재하는 질병을 파악하는 것뿐만 아니라 간에 대한 치료 방법이나 수술 방법을 결정하는 중요한 정보를 제공한다. 따라서 본 논문은 복부 MRI 영상에서 이러한 간 영역과 간의 혈관을 자동으로 검출하는 알고리즘을 제안한다. 제안 알고리즘은 1단계로 Region Growing의 개선된 방법으로 초기 설정된 간 영역의 외곽선 정보를 이용하여 씨앗점을 설정해 간 영역을 초기 분할한다. 2단계로 분할된 영역 경계선의 지역적 최소값을 이용하여 경계선의 보정 작업을 수행한다. 이후 3단계로 추출된 간 영역을 기반으로 영상 개선 후, 인페인팅(In-painting) 기법을 활용하여 간 영역 내부의 혈관 부분을 검출하게 된다. 제안 알고리즘의 평가는 전문의의 수작업 결과와 비교하였고, 결과 82.5%의 평균 정확도를 보여 제안 알고리즘의 효과적인 간혈관 검출을 확인하였다. 향후 본 연구의 확장으로 검출된 혈관 영역의 3D Volume Rendering 연구를 수행할 예정이다.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.153-154
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• 2015

현재 의료장비는 진단의 향상을 위해 보다 나은 영상을 획득하기 위하여 개발, 발전되어지고 있다. MRI장비 또한 좋은 영상을 획득하기 위해 소프트웨어 및 하드웨어가 발전되고 있다. 그 중의 하나가 자자의 세기가 점차 강한 장비로 변화되는 것이다. 고자장의 장비는 좋은 영상을 획득할 수 있는 장점이 있는 반면 폐쇄적 공포감, 소음 등의 단점 또한 존재한다. 이에 본 연구에서는 MRI 장비 단점 중 하나인 소음이 환자에게 심리적, 정신적으로 어떠한 영향을 미치는지를 설문조사한다. 그리고 이 장비를 사용하는 방사선사의 소음에 대한 인지정도를 설문조사하여 알아보고자한다. 따라서 이 연구는 MRI 검사 시 환자와 방사선사에게 소음에 대한 인식 향상 및 보호 제도 마련의 기초를 제공하고자 한다.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1341-1345
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• 2021

Spinal ependymomas are generally located in the intramedullary compartment in adults. Intradural extramedullary spinal ependymomas are extremely rare. Spinal ependymomas show various contrast enhancements on MRI. In this study, we report a rare case of a 52-year-old female who had a pathologically confirmed intradural extramedullary ependymoma that showed no enhancement on MRI.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.335-341
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• 2018

With the improvement of medical state, patients' expectations for the most advanced medical equipment are increasing. Particularly, Magnetic Resonance Image (MRI) is used as one of the core image diagnosis methods in all clinical area. However, it has been reported that many of patients who go through the examination suffer from anxiety to the severe noise level during the examination. In this study, both the noise reduction evaluation of headsets with sound-blocking materials added to existing sound-absorbing materials and the existence of sound blocking materials as artifacts on the examination image are tested. An MRI test noise is recorded as a speaker by cross-ordination the sound material (sponge) and the sound material (acrylic plate, copper plate, and 3D copper plate) inside the headset made from 3D pring. A quantitative assessment of headsets showed that the average headset value was 81.8 dB. The average dB value of the most soundproof material combination(Copper, acrylic plate, sponge, sponge) headsets on headsets with added charactering material was measured at 70.4 dB, and MRI showed that the copper was diamagnetic substance and excluded. The second most soundproof headset(Sponge, acrylic plate, 3D copper plate, sponge) was measured at 70.6 dB and MRI showed no artifacts. The same simulation of the material printed with a 3D copper PLA containing approximately 40 % copper powder resulted in no artifacts, therefore, the material output as a 3D printing was better suited for use. For MRI related research, the mutual development of 3D printing is highly anticipated.

• The Journal of the Korean bone and joint tumor society
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• v.20 no.2
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• pp.60-65
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• 2014

Purpose: To diagnose soft tissue tumor, such as lipoma and Schwannoma, magnetic resonance imaging (MRI) is sufficient in most cases. However, various characteristics are found in MRI images of Schwannoma, thus other type of tumors are often misdiagnosed as Schwannoma with MRI images. In this study, we evaluate the diagnostic value of specific MRI findings of Schwannoma. Materials and Methods: From January 2002 to May 2013, 104 patients who are suspected as Schwannoma rith MRI images are included in data, and the final diagnosis is confirmed with biopsy. Patients are divided into group 1 and group 2 who are confirmed as Schwannoma and other disease with biopsy, respectively. Results: 92 patients were diagnosed as Schwannoma (group 1) and 12 patients were diagnosed as other disease (group 2). We investigate the diagnostic value of specific MRI findings of Schwannoma. 41 patients of group 1 (45%) and 0 patients of group 2 (0%) showed target sign, 47 patients of group 1 (51%) and 2 patients of group 2 (17%) showed fascicular sign, 44 patients of group 1 (48%) and 5 patients of group 2 (42%) showed fat split sign, 28 patients of group 1 (30%) and 1 patients of group 2(9%) showed nerve entering and exiting sign, and 8 patients of group 1 (9%) and 6 patients of group 2 (50%) showed none of four specific findings on their MRI images. 52 patients of group 1 (57%) and 5 patients of group 2 (42%) have tumors on the pathway of nerve. Target sign could be considered as the best diagnostic value of the sign we investigate (p<0.05). Conclusion: Although specific MRI findings have powerful diagnostic value, patients are often misdiagnosed as Schwannoma with MRI findings. Therefore, if patients who are suspected as Schwannoma based on MRI findings have no target sign on their MRI images, we should consider the possibility of other disease.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.309-315
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• 2009

Image reconstruction of Inverse Fourier Transform after Frequency Domain Data is filtered applies to Image signal acquired from MR. There are various kinds of image processing techniques; image preprocessing, image reconstruction, image compression, image restoration image mixture, noise and artifact elimination, and image quality improvement. In this paper, optimum filter applicable to diagnosis in clinic by comparing and analyzing the characteristics of the filter will be explained. Fermi-Dirac filter will improve the image quality better than the previous MR image.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.654-669
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• 2021

Purpose To evaluate the accuracy of MRI in predicting the pathological complete response (pCR) and the residual tumor size of breast cancer after neoadjucant chemotherapy (NAC), and to determine the factors affecting the accuarcy. Materials and Methods Eighty-eight breast cancer patients who underwent surgery after NAC at our center between 2010 and 2017 were included in this study. pCR was defined as the absence of invasive cancer on pathological evaluation. The maximum diameter of the residual tumor on post-NAC MRI was compared with the tumor size of the surgical specimen measured pathologically. Statistical analysis was performed to elucidate the factors affecting pCR and the residual tumor size-discrepancy between the MRI and the pathological measurements. Results The pCR rate was 10%. The diagnostic accuracy of MRI and the area under the curve for predicting pCR were 90.91% and 0.8017, respectively. The residual tumor sizes obtained using MRI and pathological measurements showed a strong correlation (r = 0.9, p < 0.001), especially in patients with a single mass lesion (p = 0.047). The size discrepancy between MRI and the pathological measurements was significantly greater in patients with the luminal type (p = 0.023) and multifocal tumors/non-mass enhancement on pre-NAC MRI (p = 0.047). Conclusion MRI is an accurate tool for evaluating pCR and residual tumor size in breast cancer patients who receive NAC. Tumor subtype and initial MRI features affect the accuracy of MRI.

• Journal of the Korea Computer Graphics Society
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• v.10 no.4
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• pp.1-5
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• 2004

본 논문에서는 인체의 머리 부분을 촬영한 자기 공명 촬영 영상(MRI: Magnetic Resonance Imaging)에서 뇌 영역의 대뇌 피질 만을 분할하는 방법에 대해 제시하고자 한다. 뇌의 해부학적 구조를 파악할 경우에 영상 내에 함께 보여지는 두개골과 뇌척수액 등을 제외한 대뇌피질 영역을 분할하면 보다 효과적인 정보 분석 및 진단이 가능하게 된다. 본 논문에서는 3단계 알고리즘을 제시한다. 첫번째 단계에서는 Speckle reducing anisotropic diffusion (SRAD)를 이용하여 영상 내에 존재하는 잡음을 제거하기 위한 필터링이다. 두번째 단계에서는 필터링된 결과를 이용하여 추출된 임계값과 사용자의 인터렉션인 씨드 포인트를 통해 영상분할을 수행하고, 세 번째 단계에서는 후 처리를 통해 분할 결과를 보완한다. 영상분할 결과의 정확성을 측정하기 위하여 현재 병원의 의료진들이 사용하고 있는 Mayo clinic사의 Analyze를 이용하여 분할된 결과와의 오류를 측정하였다. 또한 최종 결과에 대해 ultravis를 이용한 볼륨 렌더링으로 영상분할의 최종 결과를 제시하였다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.1-5
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• 2003

의료영상의 분할은 의료영상을 컴퓨터 진단 및 가시화에 필요한 같은 성질을 가진 여러 조직으로 나누어주는 방법이다. 즉 입력되어진 영상을 처리하여 유사한 화소들의 집합인 영역들로 화소들을 구분하는 작업이며 영상분할의 결과는 영상인식의 정확성에 큰 영향을 미친다. MRI(Magnetic Resonance Imaging)으로부터 정상적인 세포조직 또는 뇌종양과 같은 비정상적인 세포조직의 가시화와 분석을 위해서는 대상 세포조직의 적절한 분류를 필요로 한다. 하지만 기존의 영역 검출 방법으로는 잡음이 섞여 있는 영상에서 여러 가지의 처리과정(주로 잡음 제거)이 필수적이고 그런 과정으로 인해 정확한 영역 검출이 힘들게 된다. 이에 잡음이 있더라도 이를 제거하기 위한 처리가 필요 없이 영역기반으로 필요한 파라미터의 추정을 통한 MRF(Markov Random Field)를 이용하여 보다 효율적이고 정확하게 MRI에서 질환 영역을 검출할 수 있다.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1366-1372
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• 2022

Myxofibrosarcoma is one of the most common soft tissue sarcomas in elderly patients. It often occurs in the extremities, trunk, and retroperitoneum. However, it is rarely observed in the mediastinum, and only a few cases have been reported in the literature. Herein, we present the imaging findings, with an emphasis on the MRI results, of a surgically confirmed anterior mediastinal myxofibrosarcoma in a 66-year-old male.