치과용 파노라마방사선사진에서 AlexNet의 골다공증 판정
AlexNet in Determining Osteoporosis on Dental Panoramic Radiograph
배수영, 송인자, 써얌 아디카리, 이재서, 윤숙자, 정호걸,
소속 상세정보
배수영 ( Bae Su-Young ) - Chonnam National University School of Dentistry
송인자 ( Song In-Ja ) - Gwang-Ju Womens University Department of Nursing
써얌 아디카리 ( Shyam Adhikari ) - Jeonbuk National University Electronic Engineering
이재서 ( Lee Jae-Seo ) - Chonnam National University School of Dentistry Department of Oral and Maxillofacial Radiology
윤숙자 ( Yoon Sook-Ja ) - Chonnam National University School of Dentistry Department of Oral and Maxillofacial Radiology
정호걸 ( Jeong Ho-Gul ) - InvisionLab Inc.
Abstract
This study was performed as a part of serial experiments of applying convolutional neural network(CNN) in determining osteoporosis on panoramic radiograph. The purpose of this study was to investigate how sensitively CNN determine osteoporosis on cropped panoramic radiograph. Panoramic radiographs from 1268 female patients(mean age 45.2 ± 21.1 yrs) were selected for this study. For the osteoporosis group, 633(mean age 72.2 ± 8.5 yrs) were selected, while for the normal group 635(mean age 28.3 ± 7.0 yrs). AlexNet was utilized as CNN in this study. A multiple-column CNN was designed with two rectangular regions of interest on the mandible inferior area. An occluding method was used to analyze the sensitive area in determining osteoporosis on AlexNet. Testing of AlexNet showed accuracy of 99% in determining osteoporosis on panoramic radiographs. AlexNet was sensitive at the area of cortical and cancellous bone of the mandible inferior area including adjacent soft tissue.
키워드
Osteoporosis; Panoramic Radiograph; Mandible; Neural network
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