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Deep Convolutional Neural Network를 적용한 피하 종괴의 초음파적 진단: 실험적 연구
이우협 ( Woo Hyup Lee ),육화정 ( Hwa Jung Yook ),손준호 ( Joon Ho Son ),이현지 ( Hyun Ji Lee ),김영호 ( Young Ho Kim ),한주희 ( Ju Hee Han ),이지현 ( Ji Hyun Lee ),이준영 ( Jun Young Lee ),박영민 ( Young Min Park ),방철환 ( Chul H 대한피부과학회 2021 대한피부과학회지 Vol.59 No.7
Background: Ultrasonography is an effective noninvasive imaging modality for the diagnosis of subcutaneous masses. To date, few studies have reported skin ultrasonography using deep convolutional neural networks (DCNNs). We investigated the accuracy of DCNNs for the diagnosis of epidermal cysts, lipomas, and other subcutaneous masses. Objective: The purpose of this study was to evaluate whether DCNNs could diagnose subcutaneous masses with ultrasonographic images at level of competence comparable to dermatologists. Methods: We created a dataset of 1,361 skin ultrasonography images obtained from 202 patients diagnosed with epidermal cysts, lipomas, and other subcutaneous masses, to train the DCNNs using ResNet18. Performance was compared with another set of 93 ultrasonographic images (24 epidermal cysts, 25 lipomas, and 44 other subcutaneous masses) from open-access articles. Results: The DCNNs yielded 87.10% classification accuracy and 86.10% F1-scores. The area under the curve, sensitivity, and specificity were 0.92 (95% confidence interval [CI] 0.86∼0.98), 75.00%, and 98.55% for epidermal cysts; 0.93 (95% CI 0.88∼0.98), 80.00%, and 94.12% for lipomas; and 0.97 (95% CI 0.93∼1.00), 97.73%, and 85.71% for other subcutaneous masses, respectively. Analysis using gradient-weighted class activation mapping revealed that the DCNNs could detect specific ultrasonographic findings of epidermal cysts and lipomas. Conclusion: We propose that DCNNs combined with ultrasonography may aid in the diagnosis of subcutaneous masses in outpatient settings. (Korean J Dermatol 2021;59(7):513∼520)
김선희 ( Sun-hee Kim ),최영숙 ( Young-sook Choi ),권산 ( San Gwon ),이우협 ( Woo-hyup Lee ),최수환 ( Su-hwan Choi ),이은서 ( Eun-ser Lee ) 한국정보처리학회 2023 한국정보처리학회 학술대회논문집 Vol.30 No.2
다양한 기후변화로 인한 금전적 피해와 위험한 상황을 예방하는 것은 중요한 과제이다. 기존의 창문은 사용자가 수동으로 제어해야 하므로 사용자 부재 시 피해가 발생할 수 있으며, 이에 대한 신속한 대처가 요구되고 있다. 이를 위해 라즈베리파이와 센서를 활용하여 장소의 구애 없이 날씨에 따라 유동적인 대처가 가능한 자동 창문 개폐 시스템을 설계 및 구현하였다.