• Korean Journal of Radiology
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• 제22권6호
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• pp.951-958
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• 2021

Objective: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. Materials and Methods: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. Results: The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). Conclusion: In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.285-286
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• 1998

Virtual Brain-endoscopy is an effective method to detect lesion in brain. Brain is the most part of the human and is not easy part to operate so that reconstructing in 3D may be very helpful to doctors. In this paper, it is suggested that to increase the reliability, method of matching 3D object with the 2D CT slice. 3D Brain-endoscopy is reconstructed with 35 slices of 2D CT images. There is a plate in 3D brain-endoscopy so as to drag upward or downward to match the relevant 2D CT image. Relevant CT image guides the user to recognize the exact part he or she is investigating. VRML Script is used to make the change in images and PlaneSensor node is used to transmit the y coordinate value with the CT image. The result is test on the PC which has the following spec. 400MHz Clock-speed, 512MB ram, and FireGL 3000 3D accelerator is set up. The VRML file size is 3.83MB. There was no delay in controlling the 3D world and no collision in changing the CT images. This brain-endoscopy can be also put to practical use on medical education through internet.

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.317-322
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• 1989

In this paper, brain CT images are automatically segmented to reconstruct the 3-D scene from consecutive CT sections. Contextual segmentation technique was applied to overcome the partial volume artifact and statistical fluctuation phenomenon of soft tissue images. Images are hierarchically analyzed by region growing and graph editing techniques. Segmented regions are discriptively decided to the final organs by using the semantic informations.

• 한국방사선학회논문지
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• 제17권6호
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• pp.809-817
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• 2023

뇌출혈 진단 방법 중 CT는 비침습적으로 피사체의 3차원 영상을 제공할 수 있다. 그래서 응급실에서 급성인 환자 상대로 많이 사용되고 중요한 역할을 담당하고 있다. 뇌혈관 CT는 다른 혈관 CT에 비해 비교적 촬영 빈도가 높으며 뇌혈관 CT 검사 시 적절한 SNR, 합리적인 유효선량으로 검사를 해야한다. 뇌혈관 CT 검사 시 이중에너지와 단일에너지를 이용하였을 때 실질적으로 어느 것이 유효선량이 적으며, SNR이 차이가 없는지 환자영상과 Phantom영상을 같이 비교하였다. SNR과 CNR의 P값이 0.05이상일 때 통계적으로 차이가 없다고 보았고, 유효선량은 0.05미만일 경우 통계적으로 차이가 있다고 보았다. 실험에서는 병원영상의 환자선량을 비교하였을 때 이중에너지의 유효선량이 53.53% 적게, Phantom의 OLSD 이중에너지 유효선량이 57.94% 적게, Phantom의 Dose Report의 이중에너지 유효선량이 56.04% 적었다. 그래서 뇌혈관조영 CT는 이중에너지를 권장한다.

• 한국방사선학회논문지
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• 제9권6호
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• pp.369-374
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• 2015

본 연구에서 제안된 질감특징분석 알고리즘은 뇌출혈환자의 CT영상을 이용하여 정상영상과 질환영상으로 구분하여, 고유영상 및 실험영상을 생성하고 제안된 컴퓨터보조진단 시스템에 적용하여 6개의 파라메타로 정량적 분석을 통해 뇌출혈 CT영상의 인식률을 도출하고 평가하였다. 결과로 뇌출혈 CT영상 40증례 중에서 각각의 질감 특징값에 대한 인식률은 평균밝기의 경우 100%, 평균대조도의 경우 100%, 평탄도의 경우 100%, 왜곡도의 경우 100%로 높게 나타났고, 균일도의 경우 95%, 엔트로피의 경우 87.5%로 다소 낮은 질환 인식률을 보였다. 따라서 본 연구의 결과를 바탕으로 의료영상의 컴퓨터보조진단 시스템으로 발전된 프로그램을 구현한다면 뇌출혈 CT영상의 질환부위 자동검출 및 정량적 진단이 가능해 컴퓨터보조진단 자료로서 활용이 가능할 것으로 판단되며 최종판독에서 정확성과 판독시간 단축에 유용하게 사용 될 것으로 사료된다.

• 한국인공지능학회지
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• 제12권1호
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• pp.1-6
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• 2024

Recently, various techniques are being applied through the development of medical AI, and research has been conducted on the application of super-resolution AI models. In this study, evaluate the results of the application of the super-resolution AI model to brain CT as the basic data for future research. Acquiring CT images of the brain, algorithm for brain and bone windowing setting, and the resolution was downscaled to 5 types resolution image based on the original resolution image, and then upscaled to resolution to create an LR image and used for network input with the original imaging. The SRCNN model was applied to each of these images and analyzed using PSNR, SSIM, Loss. As a result of quantitative index analysis, the results were the best at 256×256, the brain and bone window setting PSNR were the same at 33.72, 35.2, and SSIM at 0.98 respectively, and the loss was 0.0004 and 0.0003, respectively, showing relatively excellent performance in the bone window setting CT image. The possibility of future studies aimed image quality and exposure dose is confirmed, and additional studies that need to be verified are also presented, which can be used as basic data for the above studies.

• Journal of Electrical Engineering and Technology
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• 제10권5호
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• 대한의용생체공학회:의공학회지
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• 제39권3호
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• pp.116-123
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• 2018

This study is a model experimental study using a phantom to propose an optimized brain CT scan protocol that can reduce the radiation dose of a patient and remain quality of image. We investigate the CT scan parameters of brain CT in clinical medical institutions and to measure the important parameters that determine the quality of CT images. We used 52 multislice spiral CT (SOMATOM Definition AS+, Siemens Healthcare, Germany). The scan parameters were tube voltage (kVp), tube current (mAs), scan time, slice thickness, pitch, and scan field of view (SFOV) directly related to the patient's exposure dose. The CT dose indicators were CTDIvol and DLP. The CT images were obtained while increasing the imaging conditions constantly from the phantom limit value (Q1) to the maximum value (Q4) for AAPM CT performance evaluation. And statistics analyzed with Pearson's correlation coefficients. The result of tube voltage that the increase in tube voltage proportionally increases the variation range of the CT number. And similar results were obtained in the qualitative evaluation of the CT image compared to the tube voltage of 120 kVp, which was applied clinically at 100 kVp. Also, the scan conditions were appropriate in the tube current range of 250 mAs to 350 mAs when the tube voltage was 100 kVp. Therefore, by applying the proposed brain CT scanning parameters can be reduced the radiation dose of the patient while maintaining quality of image.

• 핵의학기술
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• 제19권2호
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• pp.68-73
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• 2015

PET/CT 검사 시 검사 부위에 따라 적절한 액세서리의 사용이 권고되고 있다. 그 중 brain 검사에서 사용되는 액세서리인 brain holder를 사용하지 않는 경우 CT의 small FOV에 의하여 whole pallet이 AC-CT에 cover되지 않으며, 이에 따른 truncated region에 따라 count loss가 발생된다. 본 논문에서는 brain holder를 사용하지 않았을 경우 발생하는 truncated region에 의한 image quality의 변화를 평가하고자 한다. Siemens사의 biograph truepoint40 장비와 $^{68}Ge$-uniform phantom을 사용하여 $^{68}Ge$ phantom을 pallet위에서 스캔하고 brain holder위에 위치하고 스캔 하였다. brain protocol을 적용하여 holder를 사용하지 않은 경우 pallet이 AC-CT의 FOV에 포함되지 않는 것을 알 수 있었다. 획득된 영상을 FBP, OSEM, TrueX recon method를 이용하여 iteration 4, subsets 21, gaussian 2 mm와 5 mm parameter를 적용하여 재구성 후 Window level : -4200, window width : 1000으로 설정하여 영상의 uniformity를 평가하였으며, vertical profile을 생성하여 count uniformity를 평가하였고, 마지막으로 5장과 20장의 slice를 summation하여 integral uniformity를 평가하였다. AC-CT영상을 통하여 holder를 사용하지 않는 경우 FOV내에 pallet이 모두 포함되지 않는 것을 알 수 있으며, 이에 따른 truncation에 의한 부정확한 attenuation factor가 나타났다 PET corrected sinogram 영상에서 holder를 사용하지 않은 경우 truncated region에 의한 defect 부위를 확인할 수 있으며, holder를 사용한 경우 uniform한 영상을 확인할 수 있었다. Window level : 4200, window width : 1000으로 설정 시 FBP, OSEM, TrueX recon 방법 모두에서 holder를 사용한 경우 uniform한 영상이 획득되었지만, holder를 사용하지 않은 경우 하단에 defect가 관찰되었다. Holder를 사용한 경우와 사용하지 않은 경우의 영상을 각 5장, 20장씩 summation하여 NEMA method에 따라 integral uniformity를 구하였으며, 5장 slice의 summation에서 holder를 사용하지 않은 경우 11.7% holder를 사용한 경우 7.2%로 나타났다. 20장 slice의 summation에서 holder를 사용하지 않은 경우 11.1% holder를 사용한 경우 76.7%로 나타났다. brain 검사 시 holder를 사용하지 않는 경우 truncated region에 따른 phantom 하단부의 count defect가 확인되었으며, 이는 환자 검사 시 occipital lobe의 count loss를 발생하게 되며 research 검사 시 검사 결과의 오차를 발생하게 됨으로 brain PET/CT 검사 시 정확한 검사결과를 위하여 검사 액세서리가 반드시 적용되어야 할 것이다.