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Must-read papers
本仓库主要分享AI结合医疗影像（CT/核磁/超声）领域值得一读的文章和资源😊
集中在超声影像和深度学习
Content
| 1. Tool related | ||
| 1.1 Machine Learning | 1.2 Deep Learning | |
| 1.3 Radiomics | ||
| 2. Application related | ||
| 2.1 Machine Learning | 2.2 Deep Learning | |
| 2.3 Radiomics | 2.4 Combination | |
| 3. Related Research Platform | ||
Tool related
Machine Learning Theory
Deep Learning Theory
Radiomics Theory
Application related
Machine Learning
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Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy European Journal of Heart Failure (2018)
Maja Cikes1, Sergio Sanchez-Martinez, Brian Claggett, Nicolas Duchateau, Gemma Piella, Constantine Butakoff, Anne Catherine Pouleur, Dorit Knappe, Tor Biering-Sørensen, Valentina Kutyifa, Arthur Moss, Kenneth Stein, Scott D. Solomon, and Bart Bijnens
Deep Learning
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Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network Nature Medicine 25, 65–69(2019)
Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng
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基于深度学习的医学CT图像中器官的区域检测， 南京师范大学，硕士学位论文 (2018)
嵇伟伟
Radiomics
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非超声影像
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Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer, Clinical Cancer Research (2017)
Zhenyu Liu, Xiao-Yan Zhang,Yan-Jie Shi, Lin Wang, Hai-Tao Zhu, Zhenchao Tang, Shuo Wang, Xiao-Ting Li, Jie Tian, and Ying-Shi Sun
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超声影像
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面向淋巴结病变多分类鉴别的弹性和 B 型 双模态超声影像组学， 生物医学工程学杂志，2019年12月第36卷第6期
石颉1, 2，江建伟3，常婉英3，陈曼3，张麒1, 2
Combination
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Machine Learning & Radiomics
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Deep Learning & Radiomics
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基于影像组学和深度迁移学习的超声图像肝纤维化评估方法研究， 深圳大学，硕士学位论文 (2019)
赵万明