Citescorey = Citationsy + Citationsy-1 + Citationsy-2 + Citations y-3 / Published articlesy + Published articlesy-1 + Published articlesy-2 + Published articles y-3
Xiong H, Liu X, Tian X, Pu L, Zhang H, Lu M, Huang W, Zhang YT. A numerical study of the effect of varied blood pressure on the stability of carotid atherosclerotic plaque. Biomedical engineering online. 2014 Dec;13(1):1-3. View at Publisher|View at Google Scholar|View at Indexing
Lim JY, Leech M. Use of auto-segmentation in the delineation of target volumes and organs at risk in head and neck. Acta Oncologica. 55,799-806 (2016). View at Publisher|View at Google Scholar
Cruz-Roa A, Caicedo JC, González FA. Visual pattern mining in histology image collections using bag of features. Artificial intelligence in medicine. 2011 Jun 1;52(2):91-106. View at Publisher|View at Google Scholar|View at Indexing
Ali S, Madabhushi A. An integrated region-, boundary-, shape-based active contour for multiple object overlap resolution in histological imagery. IEEE transactions on medical imaging. 31,1448-1460 (2012). View at Publisher|View at Google Scholar|View at Indexing
Madabhushi A, Agner S, Basavanhally A, et al. Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. Computerized medical imaging and graphics. 35, 506-514 (2011).
Xu Y, Zhu JY, Chang E, Tu Z. Multiple clustered instance learning for histopathology cancer image classification, segmentation and clustering. In2012 IEEE Conference on Computer Vision and Pattern Recognition 2012 Jun 16 (pp. 964-971). IEEE. View at Publisher|View at Google Scholar|View at Indexing
Di Cataldo S, Ficarra E, Macii E. Computer-aided techniques for chromogenic immunohistochemistry: status and directions. Computers in biology and medicine. 42,1012-1025 (2012).
Cruz-Roa A, Basavanhally A, González F, Gilmore H, Feldman M, Ganesan S, Shih N, Tomaszewski J, Madabhushi A. Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks. InSPIE medical imaging 2014 Mar 20 (pp. 904103-904103). International Society for Optics and Photonics. View at Publisher|View at Google Scholar
Di Cataldo S, Bottino A, Islam IU, et al. Subclass discriminant analysis of morphological and textural features for HEp-2 staining pattern classification. Pattern Recognition. 47,2389-2399 (2014). View at Publisher|View at Google Scholar
Hipp JD, Cheng JY, Toner M, Tompkins RG, Balis UJ. Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology. Journal of pathology informatics. 2,13(2011). View at Publisher|View at Google Scholar
Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, Madabhushi A. High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts. IEEE transactions on biomedical engineering. 59,1240-1252 (2012). View at Publisher|View at Google Scholar
Hipp J, Flotte T, Monaco J, Cheng J, Madabhushi A, Yagi Y, Rodriguez-Canales J, Emmert-Buck M, Dugan MC, Hewitt S, Toner M. Computer aided diagnostic tools aim to empower rather than replace pathologists: Lessons learned from computational chess. Journal of pathology informatics. 2,25(2011). View at Publisher|View at Google Scholar
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Xu J, Janowczyk A, Chandran S, Madabhushi A. A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation. InSPIE Medical Imaging. International Society for Optics and Photonics. 76230Y-76230Y (2010). View at Publisher|View at Google Scholar
Cruz-Roa A, DÃÂaz G, Romero E, et al. Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization. Journal of pathology informatics. 2 (2011). View at Publisher|View at Google Scholar
Sparks R, Madabhushi A. Statistical shape model for manifold regularization: Gleason grading of prostate histology. Computer Vision and Image Understanding. 117,1138-1146 (2013). View at Publisher|View at Google Scholar|View at Indexing
Srinivas U, Mousavi H, Jeon C, Monga V, Hattel A, Jayarao B. SHIRC: A simultaneous sparsity model for histopathological image representation and classification. InBiomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on 2013 Apr 7. 1118-1121 View at Publisher|View at Google Scholar
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Xu J, Sparks R, Janowczyk A, et al. High-throughput prostate cancer gland detection, segmentation, and classification from digitized needle core biopsies. InInternational Workshop on Prostate Cancer Imaging.Springer Berlin Heidelberg 77-88 (2010). View at Publisher|View at Google Scholar
Lewis Jr JS, Ali S, Luo J, et al. A quantitative histomorphometric classifier (QuHbIC) identifies aggressive versus indolent p16-positive oropharyngeal squamous cell carcinoma. The American journal of surgical pathology. 38,128 (2014). View at Publisher|View at Google Scholar
Ali S, Veltri R, Epstein JA, Christudass C, Madabhushi A. Cell cluster graph for prediction of biochemical recurrence in prostate cancer patients from tissue microarrays. InSPIE Medical Imaging. International Society for Optics and Photonics. 86760H-86760H (2013). View at Publisher|View at Google Scholar
Ali S, Veltri R, Epstein JI, Christudass C, Madabhushi A. Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays. Computerized medical imaging and graphics. 41,3-13 (2015).
Arevalo J, Cruz-Roa A, Arias V, et al. An unsupervised feature learning framework for basal cell carcinoma image analysis. Artificial intelligence in medicine. 64,131-145 (2015). View at Publisher|View at Google Scholar|View at Indexing
Ramos-Pollán R, González FA, Caicedo JC, et al. Bigs: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources. InE-science (e-science), 2012 IEEE 8th International Conference IEEE. 1-8 (2012) View at Publisher|View at Google Scholar
Gough A, Lezon T, Faeder JR, Chennubhotla C, Murphy RF, Critchley-Thorne R, Taylor DL. High content analysis with cellular and tissue systems biology: a bridge between cancer cell biology and tissue-based diagnostics. The molecular basis of cancer. 4 (2014). View at Publisher|View at Google Scholar
Madabhushi A, Basavanhally A, Doyle S, Agner S, Lee G. Computer-aided prognosis: predicting patient and disease outcome via multi-modal image analysis. InBiomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium IEEE. 1415-1418 (2010). View at Publisher|View at Google Scholar|View at Indexing
Xu Y, Jiao L, Wang S, Wei J, Fan Y, Lai M, Chang EI. Multiââ¬Âlabel classification for colon cancer using histopathological images. Microscopy research and technique. 76,1266-77 (2013). View at Publisher|View at Google Scholar
Sanchez V, AulÃÂ-LlinÃÂ s F, Bartrina-Rapesta J, Serra-SagristÃÂ J. HEVC-based lossless compression of Whole Slide pathology images. InSignal and Information Processing (GlobalSIP) IEEE Global Conference. IEEE 297-301 (2014) View at Publisher|View at Google Scholar
Sparks R, Madabhushi A. Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds. InSPIE Medical Imaging International Society for Optics and Photonics. 83151J-83151J,(2012). View at Publisher|View at Google Scholar
Hipp J, Monaco J, Kunju LP, et al. Integration of architectural and cytologic driven image algorithms for prostate adenocarcinoma identification. Analytical cellular pathology. 35,251-265 (2012). View at Publisher|View at Google Scholar|View at Indexing
Sanchez V, AulÃÂ-LlinÃÂ s F, Vanam R, et al. Rate control for lossless region of interest coding in HEVC intra-coding with applications to digital pathology images. InAcoustics, Speech and Signal Processing (ICASSP), IEEE International Conference. 1250-1254 (2015). View at Publisher|View at Google Scholar
Bhattacharjee S, Mukherjee J, Nag S, et al. Review on histopathological slide analysis using digital microscopy. International Journal of Advanced Science and Technology. 62,65-96 (2014).
Doyle S, Madabhushi A. Consensus of ambiguity: theory and application of active learning for biomedical image analysis. InIAPR International Conference on Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg. 313-324 (2010). View at Publisher|View at Google Scholar
Fatima K, Arooj A, Majeed H. A new texture and shape based technique for improving meningioma classification. Microscopy research and technique. 77,862-873 (2014). View at Publisher|View at Google Scholar|View at Indexing
Held C, Nattkemper T, Palmisano R, et al. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis. Journal of pathology informatics. 4 (2013). View at Publisher|View at Google Scholar
Kumar R, Srivastava R, Srivastava S. Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features. Journal of medical engineering. (2015). View at Publisher|View at Google Scholar
Oztan B, Shubert KR, Bjornsson CS, Plopper GE, Yener B. Biologically-driven cell-graphs for breast tissue grading. InBiomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on 2013 Apr 7 (pp. 137-140). IEEE. View at Publisher|View at Google Scholar
Cruz-Roa A, Arevalo J, Basavanhally A, Madabhushi A, González F. A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation. InTenth International Symposium on Medical Information Processing and Analysis 2015 Jan 28 (pp. 92870G-92870G). International Society for Optics and Photonics. View at Publisher|View at Google Scholar
Bhargava R, Madabhushi A. Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology. Annual Review of Biomedical Engineering. 18,387-412 (2016). View at Publisher|View at Google Scholar|View at Indexing
Hipp JD, Smith SC, Sica J, Lucas D, Hipp JA, Kunju LP, Balis UJ. Tryggo: Old norse for truth-The real truth about ground truth: New insights into the challenges of generating ground truth maps for WSI CAD algorithm evaluation. Journal of pathology informatics. 3,8 (2012). View at Publisher|View at Google Scholar
Ravindran U, Shakila T. Content based image retrieval for histology image collection using visual pattern mining. International Journal of Scientific & Engineering Research. 4 (2013). View at Publisher|View at Google Scholar|View at Indexing
