Breast cancer cell nuclei classification in histopathology images using deep neural networks

Purpose Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of cell nuclei, and heavy noise in histopathology image...

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Veröffentlicht in:	International journal for computer assisted radiology and surgery Jg. 13; H. 2; S. 179 - 191
Hauptverfasser:	Feng, Yangqin, Zhang, Lei, Yi, Zhang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.02.2018 Springer Nature B.V
Schlagworte:	Algorithms Artificial neural networks Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - pathology Cancer Cell Nucleus - classification Cell Nucleus - pathology Classification Classifiers Computer Imaging Computer Science Diagnosis, Computer-Assisted Feature extraction Feature recognition Female Health Informatics Histopathology Humans Image classification Image Processing, Computer-Assisted Imaging Machine Learning Medical imaging Medicine Medicine & Public Health Methods Neural networks Neural Networks, Computer Noise reduction Nuclei (cytology) Object recognition Pattern Recognition and Graphics Radiology Reproducibility of Results Review Article Software Surgery Vision Medical image processing Representation learning Denoising autoencoder Deep neural network Cell nuclei classification
ISSN:	1861-6410, 1861-6429, 1861-6429
Online-Zugang:	Volltext
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