96 lines
3.2 KiB
Markdown
96 lines
3.2 KiB
Markdown
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# Must-read papers
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**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**:blush:
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集中在超声影像和深度学习
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## [Content](#content)
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<table>
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<tr><td colspan="2"><a href="#theory">1. Theory</a></td></tr>
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<tr>
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<td> <a href="#machine-learning-theory">1.1 Machine Learning</a></td>
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<td> <a href="#deep-learning-theory">1.2 Deep Learning</a></td>
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</tr>
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<tr>
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<td> <a href="#radiomics-theory">1.3 Radiomics</a></td>
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<td></td>
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</tr>
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<tr><td colspan="2"><a href="#application">2. Application</a></td></tr>
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<tr>
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<td> <a href="#machine-learning">2.1 Machine Learning</a></td>
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<td> <a href="#deep-learning">2.2 Deep Learning</a></td>
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</tr>
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<tr>
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<td> <a href="#radiomics">2.3 Radiomics</a></td>
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<td> <a href="#combination">2.4 Combination</a></td>
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</tr>
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<tr><td colspan="2"><a href="related-research-platform">3. Related Research Platform</a></td></tr>
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</table>
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## [Theory](#content)
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### [Machine Learning Theory](#content)
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### [Deep Learning Theory](#content)
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### [Radiomics Theory](#content)
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## [Application](#content)
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### [Machine Learning](#content)
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1. **Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy** European Journal of Heart Failure (2018)
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*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*
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1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network** Nature Medicine 25, 65–69(2019)
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*Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng*
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### [Deep Learning](#content)
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1. 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)
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*嵇伟伟*
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### [Radiomics](#content)
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* #### 非超声影像
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1. **Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer,** Clinical Cancer Research (2017)
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*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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1. 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
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*石颉1, 2，江建伟3，常婉英3，陈曼3，张麒1, 2*
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### [Combination](#content)
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* ### Machine Learning & Radiomics
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* ### Deep Learning & Radiomics
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1. **Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study,** GUT (2018)
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*Wang K, et al.*
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1. 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)
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*赵万明*
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## [Related Research Platform](#content)
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+ [中国科学院分子影像重点实验室](http://www.radiomics.net.cn/blog/3)
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