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컨볼루션 신경망 모델을 이용한 분류에서 입력 영상의 종류가 정확도에 미치는 영향
김민정,김정훈,박지은,정우연,이종민,Kim, Min Jeong,Kim, Jung Hun,Park, Ji Eun,Jeong, Woo Yeon,Lee, Jong Min 대한의용생체공학회 2021 의공학회지 Vol.42 No.4
The purpose of this study is to classify TIFF images, PNG images, and JPEG images using deep learning, and to compare the accuracy by verifying the classification performance. The TIFF, PNG, and JPEG images converted from chest X-ray DICOM images were applied to five deep neural network models performed in image recognition and classification to compare classification performance. The data consisted of a total of 4,000 X-ray images, which were converted from DICOM images into 16-bit TIFF images and 8-bit PNG and JPEG images. The learning models are CNN models - VGG16, ResNet50, InceptionV3, DenseNet121, and EfficientNetB0. The accuracy of the five convolutional neural network models of TIFF images is 99.86%, 99.86%, 99.99%, 100%, and 99.89%. The accuracy of PNG images is 99.88%, 100%, 99.97%, 99.87%, and 100%. The accuracy of JPEG images is 100%, 100%, 99.96%, 99.89%, and 100%. Validation of classification performance using test data showed 100% in accuracy, precision, recall and F1 score. Our classification results show that when DICOM images are converted to TIFF, PNG, and JPEG images and learned through preprocessing, the learning works well in all formats. In medical imaging research using deep learning, the classification performance is not affected by converting DICOM images into any format.
농양을 합병한 거대 자궁근종 수술 후 발생한 하지정맥 혈전증과 폐 색전증
이동혁 ( Dong Hyeok Lee ),원석용 ( Seok Yong Won ),정우연 ( Woo Yeon Jung ),배연경 ( Yeon Kyoung Bae ),고민환 ( Min Whan Koh ),이태형 ( Tae Hyung Lee ) 대한산부인과학회 2002 Obstetrics & Gynecology Science Vol.45 No.11
Pulmonary thromboembolism (PTE) is a serious postoperative complication. Prompt diagnosis of PTE is important but it is difficult because clinical manifestations of PTE are not obvious in most cases. If a patient had tachypnea, cold sweating and hypoxemia
SD-rat에 KIOM-MA128을 경구 투여 한 후 혈장 중 Matrine의 약물 동태
이재연(Jae-yeon Lee),정성미(Seong Mee Jung),채정우(Jung-woo Chae),송병정(Byungjeong Song),백현문(Hyun-moon Back),윤휘열(Hwi-yeol Yun),권광일(Kwang-il Kwon),Sudeep Pradhan 大韓藥學會 2015 약학회지 Vol.59 No.3
KIOM-MA128 is a novel Korean herbal medicine with anti-atopic, anti-inflammatory and anti-asthmatic effects. This article presents the first pharmacokinetic study on KIOM-MA128. The purpose of this study was to characterize a pharmacokinetic characteristic of matrine, a potential marker of KIOM-MA128, in rats using population pharmacokinetic model. 1, 2 and 8 g/kg of KIOM-MA128 were administered to rats orally and plasma concentrations of matrine was determined by HPLC-MS/MS. Non-compartmental analysis (NCA) was performed using Phoenix?? and pharmacokinetic model was built using NONMEM??. This model was validated with internal validation which is visual predictive check (VPC) and bootstrap. The NCA result of matrine showed that Cmax was 294.24, 552.22 and 868.65 ng/ml, AUCinf was 1273.05, 2724.76 and 9743.25 ng · hr/ml and Tmax was 1, 1.3 and 2.3 hr for the doses of 1, 2, and 8 g/kg, respectively. The rat plasma concentrations were described very well with one-compartment model. Pharmacokinetic model for matrine was successfully developed and evaluated. Finally, our model is helpful to understand pharmacokinetic characteristic of KIOM-MA128.