Deep learning accelerates whole slide imaging for next-generation digital pathology applications
摘要
Deep learning demonstrates the ability to significantly increase the scanning speed of whole slide imaging in histology.This transformative solution can be used to further accelerate the adoption of digital pathology.
二级参考文献2
-
1Yair Rivenson,Tairan Liu,Zhensong Wei,Yibo Zhang,Kevin de Haan,Aydogan Ozcan.PhaseStain:the digital staining of label-free quantitative phase microscopy images using deep learning[J].Light(Science & Applications),2019,8(1):983-993. 被引量：26
-
2Neha Goswami,Yuchen R.He,Yu-Heng Deng,Chamteut Oh,Nahil Sobh,Enrique Valera,Rashid Bashir,Nahed Ismail,Hyunjoon Kong,Thanh H.Nguyen,Catherine Best-Popescu,Gabriel Popescu.Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity[J].Light(Science & Applications),2021,10(9):1797-1808. 被引量：4
共引文献2
-
1Jiaxiang Wang,Zhengyi Li,Peng Shi,Hongying Yu,Dongbai Sun.MIDNet:Deblurring Network for Material Microstructure Images[J].Computers, Materials & Continua,2024,79(4):1187-1204.
-
2Yi Zheng,Xin Wang,Zhao Jiang,Jinbo Xu,Rongying Yuan,Youran Zhao,Haoran Zhang,Chao Liu,Qionghua Wang.Adaptive multiscale microscope with fast zooming,extended working distance,and large field of view[J].Light(Advanced Manufacturing),2024,5(1):60-72.
-
1黄丹,王奕,游庆华,王鑫,张敬谊,丁偕,张伯强,崔浩阳,赵嘉旭,盛伟琪.基于注意力机制网络的多实例学习框架实现慢性胃炎多项病理指标的自动识别[J].中华病理学杂志,2021,50(10):1116-1121. 被引量：1
-
2Cheng Lu,Rakesh Shiradkar,Zaiyi Liu.Integrating pathomics with radiomics and genomics for cancer prognosis:A brief review[J].Chinese Journal of Cancer Research,2021,33(5):563-573. 被引量：6
-
3Yuting Gao,Jiurun Chen,Aiye Wang,An Pan,Caiwen Ma,Baoli Yao.Erratum to:High-throughput fast full-color digital pathology based on Fourier ptychographic microscopy via color transfer [Sci. China-Phys. Mech. Astron. 64(11), 114211 (2021)][J].Science China(Physics,Mechanics & Astronomy),2021,64(12):153-153. 被引量：6
-
4Ke Zhao,Lin Wu,Yanqi Huang,Su Yao,Zeyan Xu,Huan Lin,Huihui Wang,Yanting Liang,Yao Xu,Xin Chen,Minning Zhao,Jiaming Peng,Yuli Huang,Changhong Liang,Zhenhui Li,Yong Li,Zaiyi Liu.Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images[J].Precision Clinical Medicine,2021,4(1):17-24.
-
5李强,刘贤明,韩凯歌,江俊君,季向阳.基于深度学习的数字病理扫描系统单次曝光自动对焦方法[J].中国科学：信息科学,2021,51(10):1675-1689. 被引量：1
-
6Hyun-Jong Jang,Ahwon Lee,Jun Kang,In Hye Song,Sung Hak Lee.Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach[J].World Journal of Gastroenterology,2021,27(44):7687-7704. 被引量：1
-
7张艳辉,吴江华,孙保存.人工智能在肿瘤组织病理标志物分析中的应用进展[J].中国肿瘤临床,2022,49(14):743-747. 被引量：1
-
8DAOXIN DAI,DI LIANG,PAVEL CHEBEN.Next-generation siliconphotonics:introduction[J].Photonics Research,2022,10(10). 被引量：1
-
9Afzan Adam,Abdul Hadi Abd Rahman,Nor Samsiah Sani,Zaid Abdi Alkareem Alyessari,Nur Jumaadzan Zaleha Mamat,Basela Hasan.Epithelial Layer Estimation Using Curvatures and Textural Features for Dysplastic Tissue Detection[J].Computers, Materials & Continua,2021(4):761-777.
-
10Anil Alpsoy,Aysen Yavuz,Gulsum Ozlem Elpek.Artificial intelligence in pathological evaluation of gastrointestinal cancers[J].Artificial Intelligence in Gastroenterology,2021,2(6):141-156.
