Deep Learning Algorithms for Diagnosis of Breast Cancer with Maximum Likelihood Estimation

[1]  Yinan Kong,et al.  Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering , 2018, BioMed research international.

[2]  A. Shamrani,et al.  Breast cancers missed during screening in a tertiary-care hospital mammography facility , 2019, Annals of Saudi medicine.

[3]  Poonam Sonar,et al.  Mammogram Classification in Transform Domain , 2018, 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN).

[4]  Hui Zhang,et al.  Classification of breast density categories based on SE-Attention neural networks , 2020, Comput. Methods Programs Biomed..

[5]  Ayman M. Eldeib,et al.  Breast cancer classification using deep belief networks , 2016, Expert Syst. Appl..

[6]  Thomas J. Fuchs,et al.  Clinical-grade computational pathology using weakly supervised deep learning on whole slide images , 2019, Nature Medicine.

[7]  Tian Liu,et al.  Paired cycle-GAN based image correction for quantitative cone-beam CT. , 2019, Medical physics.

[8]  Amit Sethi,et al.  Classification of Breast Cancer Histology using Deep Learning , 2018, ICIAR.

[9]  Lijun Xie,et al.  A regularized ensemble framework of deep learning for cancer detection from multi-class, imbalanced training data , 2018, Pattern Recognit..

[10]  Xiaowei Xu,et al.  A Deep Learning System to Screen Novel Coronavirus Disease 2019 Pneumonia , 2020, Engineering.

[11]  Yi Wang,et al.  Breast Cancer Classification in Automated Breast Ultrasound Using Multiview Convolutional Neural Network with Transfer Learning. , 2020, Ultrasound in medicine & biology.

[12]  Kevin Smith,et al.  Digital image analysis in breast pathology-from image processing techniques to artificial intelligence. , 2017, Translational research : the journal of laboratory and clinical medicine.

[13]  Yinan Kong,et al.  Involvement of Machine Learning for Breast Cancer Image Classification: A Survey , 2017, Comput. Math. Methods Medicine.

[14]  R. Haug,et al.  Strong quantum memory at resonant Fermi edges revealed by shot noise , 2012, Scientific Reports.

[15]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  V. Nandagopal,et al.  Feasible analysis of gene expression –a computational based classification for breast cancer , 2019, Measurement.

[17]  Yoni Choukroun,et al.  Mammogram Classification and Abnormality Detection from Nonlocal Labels using Deep Multiple Instance Neural Network , 2017, VCBM.

[18]  N. Linder,et al.  Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples , 2016, Journal of pathology informatics.

[19]  Du-Yih Tsai,et al.  Automated Classification of Lung Diseases in Computed Tomography Images Using a Wavelet Based Convolutional Neural Network , 2018 .

[20]  Lakshman Tamil,et al.  RAMS: Remote and automatic mammogram screening , 2019, Comput. Biol. Medicine.

[21]  Zidong Wang,et al.  Machine Learning with Applications in Breast Cancer Diagnosis and Prognosis , 2018 .

[22]  Xionghui Zhou,et al.  Integrating Feature Selection and Feature Extraction Methods With Deep Learning to Predict Clinical Outcome of Breast Cancer , 2018, IEEE Access.

[23]  Chandan Chakraborty,et al.  Efficient deep learning model for mitosis detection using breast histopathology images , 2017, Comput. Medical Imaging Graph..

[24]  Andrew H. Beck,et al.  Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer , 2017, JAMA.

[25]  Jing Li,et al.  SD-CNN: a Shallow-Deep CNN for Improved Breast Cancer Diagnosis , 2018, Comput. Medical Imaging Graph..

[26]  Van-Dung Hoang,et al.  Deep CNN and Data Augmentation for Skin Lesion Classification , 2018, ACIIDS.

[27]  Yongyi Yang,et al.  A context-sensitive deep learning approach for microcalcification detection in mammograms , 2018, Pattern Recognit..

[28]  Hiba Chougrad,et al.  Deep Convolutional Neural Networks for breast cancer screening , 2018, Comput. Methods Programs Biomed..

[29]  Nrusingha Prasad Rath,et al.  Textural Feature Based Classification of Mammogram Images Using ANN , 2018, 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[30]  Maryellen L. Giger,et al.  Evaluating deep learning techniques for dynamic contrast-enhanced MRI in the diagnosis of breast cancer , 2019, Medical Imaging.

[31]  Jianhui Chen,et al.  Automated grading of breast cancer histopathology using cascaded ensemble with combination of multi-level image features , 2017, Neurocomputing.

[32]  A. Boss,et al.  Classification of breast cancer in ultrasound imaging using a generic deep learning analysis software: a pilot study. , 2017, The British journal of radiology.

[33]  James H Thrall,et al.  Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. , 2018, Journal of the American College of Radiology : JACR.

[34]  Lubomir M. Hadjiiski,et al.  Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets , 2019, IEEE Transactions on Medical Imaging.

[35]  Bram van Ginneken,et al.  A survey on deep learning in medical image analysis , 2017, Medical Image Anal..

[36]  Edgar Guevara,et al.  Comparison of Deep Learning Architectures for Pre-Screening of Breast Cancer Thermograms , 2019, 2019 Photonics North (PN).

[37]  Ali Selamat,et al.  Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model , 2018, Sensors.

[38]  Zhang Yi,et al.  Automated diagnosis of breast ultrasonography images using deep neural networks , 2019, Medical Image Anal..

[39]  Dursun Delen,et al.  Predicting breast cancer survivability: a comparison of three data mining methods , 2005, Artif. Intell. Medicine.

[40]  Lei Zhang,et al.  Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategy , 2019, Medical Imaging.

[41]  Mario Coccia,et al.  Artificial Intelligence Technology in Cancer Imaging: Clinical Challenges for Detection of Lung and Breast Cancer , 2019 .

[42]  U. Rajendra Acharya,et al.  Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques , 2019, Cognitive Systems Research.

[43]  Miguel Ángel Guevara-López,et al.  Representation learning for mammography mass lesion classification with convolutional neural networks , 2016, Comput. Methods Programs Biomed..

[44]  Shoji Kawahito,et al.  A Low-Noise X-ray Astronomical Silicon-On-Insulator Pixel Detector Using a Pinned Depleted Diode Structure , 2017, Sensors.

[45]  Ziba Gandomkar,et al.  A cognitive approach to determine the benefits of pairing radiologists in mammogram reading , 2018, Medical Imaging.

[46]  Jing Wang,et al.  Predicting lung nodule malignancies by combining deep convolutional neural network and handcrafted features , 2018, Physics in medicine and biology.