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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.1
- 수록면
- 7 - 22 (16page)
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In this review of the most recent applications of deep learning to ultrasound imaging, the architectures of deep learning networks are briefly explained for the medical imaging applications of classification, detection, segmentation, and generation. Ultrasonography applications for image processing and diagnosis are then reviewed and summarized, along with some representative imaging studies of the breast, thyroid, heart, kidney, liver, and fetal head. Efforts towards workflow enhancement are also reviewed, with an emphasis on view recognition, scanning guide, image quality assessment, and quantification and measurement. Finally some future prospects are presented regarding image quality enhancement, diagnostic support, and improvements in workflow efficiency, along with remarks on hurdles, benefits, and necessary collaborations.
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참고문헌 (94)
참고문헌 신청
Carneiro G / 2013 / Combining multiple dynamic models and deep learning architectures for tracking the left ventricle endocardium in ultrasound data / IEEE Trans Pattern Anal Mach Intell 35:2592~2607
Carneiro G / 2012 / The segmentation of the left ventricle of the heart from ultrasound data using deep learning architectures and derivative-based search methods / IEEE Trans Image Process 21:968~982
Solomon O / 2020 / Deep unfolded robust PCA with application to clutter suppression in ultrasound / IEEE Trans Med Imaging 39:1051~1063
Yoon YH / 2019 / Efficient B-mode ultrasound image reconstruction from sub-sampled RF data using deep learning / IEEE Trans Med Imaging 38:325~336
Prevost R / 2018 / 3D freehand ultrasound without external tracking using deep learning / Med Image Anal 48:187~202
Carneiro G / 2012 / The segmentation of the left ventricle of the heart from ultrasound data using deep learning architectures and derivative-based search methods / IEEE Trans Image Process 21:968~982
Solomon O / 2020 / Deep unfolded robust PCA with application to clutter suppression in ultrasound / IEEE Trans Med Imaging 39:1051~1063
Yoon YH / 2019 / Efficient B-mode ultrasound image reconstruction from sub-sampled RF data using deep learning / IEEE Trans Med Imaging 38:325~336
Prevost R / 2018 / 3D freehand ultrasound without external tracking using deep learning / Med Image Anal 48:187~202
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