Parameter Transfer Deep Neural Network for Single-Modal B-Mode Ultrasound-Based Computer-Aided Diagnosis
暂无分享,去创建一个
Shihui Ying | Wentao Kong | Jun Shi | Xiaoyan Fei | Lu Shen | Yehua Cai | Qi Zhang | Weijun Zhou
[1] Xuelong Li,et al. Segmentation of breast ultrasound image with semantic classification of superpixels , 2020, Medical Image Anal..
[2] Jie Zhu,et al. Shearlet-based texture feature extraction for classification of breast tumor in ultrasound image , 2013, Biomed. Signal Process. Control..
[3] Michael I. Jordan,et al. Learning Transferable Features with Deep Adaptation Networks , 2015, ICML.
[4] Jeff A. Bilmes,et al. Deep Canonical Correlation Analysis , 2013, ICML.
[5] Yongli Guo,et al. Erratum to “The Feasibility of Xpert MTB/RIF Testing to Detect Rifampicin Resistance among Childhood Tuberculosis for Prevalence Surveys in Northern China” , 2017, BioMed research international.
[6] Qi Zhang,et al. Sonoelastomics for Breast Tumor Classification: A Radiomics Approach with Clustering-Based Feature Selection on Sonoelastography. , 2017, Ultrasound in medicine & biology.
[7] Hamid R. Rabiee,et al. MDL-CW: A Multimodal Deep Learning Framework with CrossWeights , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Shuang Song,et al. Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks. , 2019, Medical engineering & physics.
[9] Wenzhong Guo,et al. Deep Multimodal Representation Learning: A Survey , 2019, IEEE Access.
[10] Chee Kheong Siew,et al. Extreme learning machine: Theory and applications , 2006, Neurocomputing.
[11] Guang-Bin Huang,et al. Trends in extreme learning machines: A review , 2015, Neural Networks.
[12] F. Alam,et al. Bimodal Multiparameter-Based Approach for Benign-Malignant Classification of Breast Tumors. , 2015, Ultrasound in medicine & biology.
[13] Graham W. Taylor,et al. Deep Multimodal Learning: A Survey on Recent Advances and Trends , 2017, IEEE Signal Processing Magazine.
[14] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[15] Bo Peng,et al. Cascaded Multi-Column RVFL+ Classifier for Single-Modal Neuroimaging-Based Diagnosis of Parkinson's Disease , 2019, IEEE Transactions on Biomedical Engineering.
[16] Dacheng Tao,et al. On Combining Biclustering Mining and AdaBoost for Breast Tumor Classification , 2020, IEEE Transactions on Knowledge and Data Engineering.
[17] NahavandiSaeid,et al. Extreme learning machine based transfer learning algorithms , 2017 .
[18] Chao Chen,et al. Parameter Transfer Extreme Learning Machine based on Projective Model , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).
[19] Qi Zhang,et al. Deep learning based classification of breast tumors with shear-wave elastography. , 2016, Ultrasonics.
[20] M. Chammas,et al. Ultrasound Elastography: Review of Techniques and Clinical Applications , 2017, Theranostics.
[21] Andre Esteva,et al. A guide to deep learning in healthcare , 2019, Nature Medicine.
[22] David Zhang,et al. Robust Visual Knowledge Transfer via Extreme Learning Machine-Based Domain Adaptation , 2016, IEEE Transactions on Image Processing.
[23] Jun Shi,et al. Learning using privileged information improves neuroimaging-based CAD of Alzheimer’s disease: a comparative study , 2019, Medical & Biological Engineering & Computing.
[24] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[25] Jürgen Schmidhuber,et al. Deep learning in neural networks: An overview , 2014, Neural Networks.
[26] Chao Yang,et al. A Survey on Deep Transfer Learning , 2018, ICANN.
[27] Peng-Bo Zhang,et al. A New Learning Paradigm for Random Vector Functional-Link Network: RVFL+ , 2017, Neural Networks.
[28] Barbara Caputo,et al. Learning Categories From Few Examples With Multi Model Knowledge Transfer , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] Honglak Lee,et al. Improved Multimodal Deep Learning with Variation of Information , 2014, NIPS.
[30] Taghi M. Khoshgoftaar,et al. A survey of transfer learning , 2016, Journal of Big Data.
[31] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Ilias Gatos,et al. A new computer aided diagnosis system for evaluation of chronic liver disease with ultrasound shear wave elastography imaging. , 2016, Medical physics.
[33] SchmidhuberJürgen. Deep learning in neural networks , 2015 .
[34] Qinghua Huang,et al. Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey , 2018, BioMed research international.
[35] Chris H. Q. Ding,et al. R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization , 2006, ICML.
[36] Ivor W. Tsang,et al. Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Hong Zhou,et al. Ultrasound-based differentiation of malignant and benign thyroid Nodules: An extreme learning machine approach , 2017, Comput. Methods Programs Biomed..
[38] Dong Ni,et al. Deep Learning in Medical Ultrasound Analysis: A Review , 2019, Engineering.
[39] Josien P. W. Pluim,et al. Not‐so‐supervised: A survey of semi‐supervised, multi‐instance, and transfer learning in medical image analysis , 2018, Medical Image Anal..
[40] Guang-Bin Huang,et al. Extreme Learning Machine for Multilayer Perceptron , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[41] Alejandro F. Frangi,et al. Classification of breast lesions in ultrasonography using sparse logistic regression and morphology‐based texture features , 2018, Medical physics.
[42] Shihui Ying,et al. Quaternion Grassmann average network for learning representation of histopathological image , 2019, Pattern Recognit..
[43] Roi Livni,et al. An Algorithm for Training Polynomial Networks , 2013, 1304.7045.
[44] Eliseo Guallar,et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: A meta‐analysis , 2011, Hepatology.
[45] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[46] Fan Zhang,et al. Evolutionary optimized fuzzy reasoning with mined diagnostic patterns for classification of breast tumors in ultrasound , 2019, Inf. Sci..
[47] Ferdinand Frauscher,et al. Ultrasound of the prostate , 2010, Cancer imaging : the official publication of the International Cancer Imaging Society.
[48] Saeid Nahavandi,et al. Extreme learning machine based transfer learning algorithms: A survey , 2017, Neurocomputing.