Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue
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Tao Xu | Yutao Ma | Baojin Wang | Zhan Zhang | Xiaofang Wang | Xiaolei Huang | Chao Zhou | Xiaoan Zhang | Yihong Wang | Canyu Li | Jason Jerwick | Yuan Ning | Xianxu Zeng | Xiaolei Huang | Tao Xu | Yihong Wang | Jason Jerwick | Chao Zhou | Yutao Ma | Xianxu Zeng | Xiaofang Wang | Zhan Zhang | Canyu Li | Xiaoan Zhang | Baojin Wang | Yuan Ning
[1] J. Fujimoto,et al. Optical biopsy and imaging using optical coherence tomography , 1995, Nature Medicine.
[2] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[3] Eva Lankenau,et al. Detection of cervical intraepithelial neoplasia by using optical coherence tomography in combination with microscopy , 2017, Journal of biomedical optics.
[4] P. Sodhani,et al. Performance of a low cost magnifying device, magnivisualizer, versus colposcope for detection of pre-cancer and cancerous lesions of uterine cervix , 2014, Journal of gynecologic oncology.
[5] M. Schiffman,et al. American Cancer Society, American Society for Colposcopy and Cervical Pathology, and American Society for Clinical Pathology screening guidelines for the prevention and early detection of cervical cancer , 2012, CA: a cancer journal for clinicians.
[6] Clare Gilham,et al. Efficacy of HPV-based screening for prevention of invasive cervical cancer: follow-up of four European randomised controlled trials , 2014, The Lancet.
[7] Alan D. Lopez,et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study , 2017, JAMA oncology.
[8] Karl Pearson F.R.S.. LIII. On lines and planes of closest fit to systems of points in space , 1901 .
[9] Bram van Ginneken,et al. A survey on deep learning in medical image analysis , 2017, Medical Image Anal..
[10] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[11] P. Escobar,et al. Diagnostic efficacy of optical coherence tomography in the management of preinvasive and invasive cancer of uterine cervix and vulva , 2003, International Journal of Gynecologic Cancer.
[12] J. Fujimoto,et al. Optical coherence microscopy in scattering media. , 1994, Optics letters.
[13] K. Friese,et al. Optical coherence tomography as a non‐invasive imaging technique for preinvasive and invasive neoplasia of the uterine cervix , 2010, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.
[14] Nima Tajbakhsh,et al. Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? , 2016, IEEE Transactions on Medical Imaging.
[15] American society for colposcopy and cervical pathology. , 1997, Journal of lower genital tract disease.
[16] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[17] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[18] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[19] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[20] Beop-Min Kim,et al. Optical diagnosis of cervical intraepithelial neoplasm (CIN) using polarization-sensitive optical coherence tomography. , 2008, Optics express.
[21] Jason Jerwick,et al. Ultrahigh-resolution optical coherence microscopy accurately classifies precancerous and cancerous human cervix free of labeling , 2018, Theranostics.
[22] Petra M. Casey,et al. Abnormal cervical appearance: what to do, when to worry? , 2011, Mayo Clinic proceedings.
[23] Brett E. Bouma,et al. In vivo cellular optical coherence tomography imaging , 1998, Nature Medicine.
[24] G. Ripandelli,et al. Optical coherence tomography. , 1998, Seminars in ophthalmology.
[25] Thomas Brox,et al. Striving for Simplicity: The All Convolutional Net , 2014, ICLR.
[26] J. Fujimoto,et al. In vivo endoscopic optical biopsy with optical coherence tomography. , 1997, Science.
[27] Mohammad Hossein Khosravi,et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016 , 2018, JAMA oncology.
[28] Sebastian Thrun,et al. Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.
[29] Mubarak Shah,et al. Visual attention detection in video sequences using spatiotemporal cues , 2006, MM '06.
[30] Subhashini Venugopalan,et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.
[31] Christopher Joseph Pal,et al. Brain tumor segmentation with Deep Neural Networks , 2015, Medical Image Anal..
[32] D. D. de Bruin,et al. Optical biopsy of epithelial cancers by optical coherence tomography (OCT) , 2013, Lasers in Medical Science.
[33] Liming Wang,et al. An artificial intelligence platform for the multihospital collaborative management of congenital cataracts , 2017, Nature Biomedical Engineering.
[34] Stephen V. Stehman,et al. Selecting and interpreting measures of thematic classification accuracy , 1997 .
[35] P. Escobar,et al. Optical coherence tomography as a diagnostic aid to visual inspection and colposcopy for preinvasive and invasive cancer of the uterine cervix , 2006, International Journal of Gynecologic Cancer.
[36] D. Sculley,et al. Google Vizier: A Service for Black-Box Optimization , 2017, KDD.
[37] Daniel S. Kermany,et al. Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning , 2018, Cell.
[38] Xin Qi,et al. Diagnostic efficacy of computer extracted image features in optical coherence tomography of the precancerous cervix. , 2011, Medical physics.
[39] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[40] J. Fleiss. Measuring nominal scale agreement among many raters. , 1971 .
[41] A. Jemal,et al. Cancer statistics, 2017 , 2017, CA: a cancer journal for clinicians.
[42] G. Gelikonov,et al. In vivo endoscopic OCT imaging of precancer and cancer states of human mucosa. , 1997, Optics express.
[43] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[44] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[45] A. Agresti,et al. Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions , 1998 .