Feature extraction from histopathological images based on nucleus-guided convolutional neural network for breast lesion classification

Siegel, 2017, Cancer statistics, 2017, CA, 67, online Zhang, 2016, Large-scale medical image analytics: recent methodologies, applications and future directions, Med. Image Anal., 33, 98, 10.1016/j.media.2016.06.010 Wu, 2017, Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: model discovery and external validation, J. Magn. Reson. Imaging, 10.1002/jmri.25661 Wu, 2017, Unsupervised clustering of quantitative image phenotypes reveals breast cancer subtypes with distinct prognoses and molecular pathways, Clin. Cancer Res., 10.1158/1078-0432.CCR-16-2415 Robbins, 2010 Mosquera-Lopez, 2014, Computer-aided prostate cancer diagnosis from digitized histopathology: a review on texture-based systems, IEEE Rev. Biomed. Eng., 8, 98, 10.1109/RBME.2014.2340401 Duncan, 2000, Medical image analysis: progress over two decades and the challenges ahead, IEEE Trans. Pattern Anal. Mach. Intell., 22, 85, 10.1109/34.824822 Gurcan, 2009, Histopathological image analysis: a review, IEEE Rev. Biomed. Eng., 2, 147, 10.1109/RBME.2009.2034865 Bejnordi, 2016, Automated detection of dcis in whole-slide h&e stained breast histopathology images, IEEE Trans. Med. Imaging, 35, 2141, 10.1109/TMI.2016.2550620 Lakhani, 2012 Caicedo, 2009, Histopathology image classification using bag of features and kernel functions, 126 Sertel, 2009, Computer-aided prognosis of neuroblastoma on whole-slide images: classification of stromal development, Pattern Recognit., 42, 1093, 10.1016/j.patcog.2008.08.027 Mercan, 2014, Localization of diagnostically relevant regions of interest in whole slide images, 1179 Xu, 2014, Weakly supervised histopathology cancer image segmentation and classification, Med. Image Anal., 18, 591, 10.1016/j.media.2014.01.010 Lowe, 2004, Distinctive image features from scale-invariant keypoints, Int. J. Comput. Vision, 60, 91, 10.1023/B:VISI.0000029664.99615.94 Dalal, 2005, Histograms of oriented gradients for human detection, 886 Ojala, 1996, A comparative study of texture measures with classification based on feature distributions, Pattern Recognit., 29, 51, 10.1016/0031-3203(95)00067-4 Dundar, 2011, Computerized classification of intraductal breast lesions using histopathological images, IEEE Trans. Biomed. Eng., 58, 1977, 10.1109/TBME.2011.2110648 Kowal, 2013, Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images, Comput. Biol. Med., 43, 1563, 10.1016/j.compbiomed.2013.08.003 Cheng, 2015, Automated analysis and diagnosis of skin melanoma on whole slide histopathological images, Pattern Recognit., 48, 2738, 10.1016/j.patcog.2015.02.023 Doyle, 2008, Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features, 496 Basavanhally, 2010, Computerized image-based detection and grading of lymphocytic infiltration in her2+ breast cancer histopathology, IEEE Trans. Biomed. Eng., 57, 642, 10.1109/TBME.2009.2035305 Tabesh, 2007, Multifeature prostate cancer diagnosis and gleason grading of histological images, IEEE Trans. Med. Imaging, 26, 1366, 10.1109/TMI.2007.898536 Al-Kadi, 2010, Texture measures combination for improved meningioma classification of histopathological images, Pattern Recognit., 43, 2043, 10.1016/j.patcog.2010.01.005 Ozdemir, 2013, A hybrid classification model for digital pathology using structural and statistical pattern recognition, IEEE Trans. Med. Imaging, 32, 474, 10.1109/TMI.2012.2230186 Zheng, 2014, Retrieval of pathology image for breast cancer using plsa model based on texture and pathological features, 2304 Kandemir, 2015, Computer-aided diagnosis from weak supervision: a benchmarking study, Comput. Med. Imaging Graph., 42, 44, 10.1016/j.compmedimag.2014.11.010 Zhang, 2015, Fusing heterogeneous features from stacked sparse autoencoder for histopathological image analysis, IEEE J. Biomed. Health Inform., 20, 1377, 10.1109/JBHI.2015.2461671 Ma, 2016, Breast histopathological image retrieval based on latent Dirichlet allocation, IEEE J. Biomed. Health Inform. Cruz-Roa, 2013, A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection, 403 Arevalo, 2015, An unsupervised feature learning framework for basal cell carcinoma image analysis, Artif. Intell. Med., 64, 131, 10.1016/j.artmed.2015.04.004 Xu, 2016, Stacked sparse autoencoder (ssae) for nuclei detection on breast cancer histopathology images, IEEE Trans. Med. Imaging, 35, 119, 10.1109/TMI.2015.2458702 Nayak, 2013, Classification of tumor histopathology via sparse feature learning, 410 Chang, 2013, Characterization of tissue histopathology via predictive sparse decomposition and spatial pyramid matching, 91 Zhou, 2014, Classification of histology sections via multispectral convolutional sparse coding, 3081 Srinivas, 2014, Simultaneous sparsity model for histopathological image representation and classification, Med. Imaging IEEE Trans., 33, 1163, 10.1109/TMI.2014.2306173 Vu, 2016, Histopathological image classification using discriminative feature-oriented dictionary learning, Med. Imaging IEEE Trans., 35, 738, 10.1109/TMI.2015.2493530 Malon, 2008, Identifying histological elements with convolutional neural networks, 450 Xu, 2016, A deep convolutional neural network for segmenting and classifying epithelial and stromal regions in histopathological images, Neurocomputing, 191, 214, 10.1016/j.neucom.2016.01.034 Hou, 2015, Patch-based convolutional neural network for whole slide tissue image classification, 2424 Zhang, 2015, Fine-grained histopathological image analysis via robust segmentation and large-scale retrieval, 5361 Zhang, 2015, High-throughput histopathological image analysis via robust cell segmentation and hashing, Med. Image Anal., 26, 306, 10.1016/j.media.2015.10.005 Zink, 2004, Nuclear structure in cancer cells, Nat. Rev. Cancer, 4, 677, 10.1038/nrc1430 Ruifrok, 2001, Quantification of histochemical staining by color deconvolution, Anal. Quant. Cytol. Histol., 23, 291 Coates, 2011, An analysis of single-layer networks in unsupervised feature learning, 215 Masci, 2011, Stacked convolutional auto-encoders for hierarchical feature extraction, 52 Ng, 2011, Sparse autoencoder, CS294A Lect. notes, 72, 1 Byrd, 1995, A limited memory algorithm for bound constrained optimization, SIAM J. Sci. Comput., 16, 1190, 10.1137/0916069 Kohavi, 1995, A study of cross-validation and bootstrap for accuracy estimation and model selection, 1137 Krizhevsky, 2012, Imagenet classification with deep convolutional neural networks, 1097