지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2021.3
- 수록면
- 42 - 43 (2page)
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초록· 키워드
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Introduction and Background
Rotator Cuff Tear (RCT) is the disease that can be followed by surgery due to pain and weakness. USG has manifested comparable performance to MRI. However, conventional vision-based algorithms exhibited inferior performance because of speckle noises and relatively low resolution. In this study, we developed a novel fully convolutional neural network, denoted as Segmentation Model Adopting pRe-Trained Classification Architecture (SMART-CA), with a novel Integrated on Positive Loss Function (IPFL) to diagnose the RCT precisely.
Material and Method
From the total 1,400 US images, the number of RCT is 1,280, whereas that of healthy shoulder was 120. The ratio of training-set, validation-set, and test-set was 8:1:1, respectively. To diagnose RCT, we constructed SMART-CA to solve USG-related problems such as noisy environment and sparse areas of RCT. ^_@span style=color:#999999 ^_# ... ^_@/span^_#^_@a href=javascript:; onclick=onClickReadNode('NODE10566531');fn_statistics('Z354','null','null'); style='color:#999999;font-size:14px;text-decoration:underline;' ^_#전체 초록 보기^_@/a^_#
Rotator Cuff Tear (RCT) is the disease that can be followed by surgery due to pain and weakness. USG has manifested comparable performance to MRI. However, conventional vision-based algorithms exhibited inferior performance because of speckle noises and relatively low resolution. In this study, we developed a novel fully convolutional neural network, denoted as Segmentation Model Adopting pRe-Trained Classification Architecture (SMART-CA), with a novel Integrated on Positive Loss Function (IPFL) to diagnose the RCT precisely.
Material and Method
From the total 1,400 US images, the number of RCT is 1,280, whereas that of healthy shoulder was 120. The ratio of training-set, validation-set, and test-set was 8:1:1, respectively. To diagnose RCT, we constructed SMART-CA to solve USG-related problems such as noisy environment and sparse areas of RCT. ^_@span style=color:#999999 ^_# ... ^_@/span^_#^_@a href=javascript:; onclick=onClickReadNode('NODE10566531');fn_statistics('Z354','null','null'); style='color:#999999;font-size:14px;text-decoration:underline;' ^_#전체 초록 보기^_@/a^_#
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UCI(KEPA) : I410-ECN-0101-2021-514-001736700