Paper references

Whole slide imaging informatics - Digital Pathology in support of big data and omics datasets - Non-human applications of digital pathology - Beyond two dimensions

Whole Slide Imaging Informatics

Collaborative analysis of multi-gigapixel imaging data using Cytomine, Marée et al, Bioinformatics, 2016 http://bioinformatics.oxfordjournals.org/content/early/2016/02/26/bioinformatics.btw013

Method of detecting and quantifying blur in a digital image, Bertheau and Ameisen, US Patent 9,076,192, 2015

Assessment of algorithms for mitosis detection in breast cancer histopathology images, Veta et al, Medical Image Analysis, 2015 http://www.sciencedirect.com/science/article/pii/S1361841514001807

Towards better digital pathology workflows: programming libraries for high-speed sharpness assessment of Whole Slide Images, Ameisen et al, Diagnostic Pathology, 2014 https://www.ncbi.nlm.nih.gov/pubmed/25565494

Automatic Image Quality Assessment in Digital Pathology: From Idea to Implementation, Ameisen et al, 2nd International Work-Conference on Bioinformatics and Biomedical Engineering, 2014 http://iwbbio.ugr.es/2014/papers/IWBBIO_2014_paper_18.pdf

Breast cancer histopathology image analysis: a review, Veta et al, IEEE Trans Biomed Eng, 2014 http://www.ncbi.nlm.nih.gov/pubmed/24759275

Stack or trash? Quality assessment of virtual slides, Ameisen et al, Diagnostic Pathology, 2013 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3849546/

Analyzing huge pathology images with open source software, Deroulers et al, Diagnostic Pathology, 2013 https://www.ncbi.nlm.nih.gov/pubmed/23829479

Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks, Cireşan et al, Book Chapter: Medical Image Computing and Computer-Assisted Intervention, 2013 http://link.springer.com/chapter/10.1007/978-3-642-40763-5_51

Automatic nuclei segmentation in H&E stained breast cancer histopathology images, Veta et al, PLoS One, 2013 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3726421/

Mitosis detection using generic features and an ensemble of cascade adaboosts, Tek, J Pathol Inform, 2013 http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=12;epage=12;aulast=Tek;type=0

Automated mitosis detection in histopathology using morphological and multi-channel statistics features, Irshad, J Pathol Inform, 2013 http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=10;epage=10;aulast=Irshad;type=0

2-SiMDoM: A 2-Sieve Model for Detection of Mitosis in Multispectral Breast Cancer Imagery, Tripathi et al, Proceedings of IEEE ICIP, 2013 http://f4k.dieei.unict.it/proceedings/ICIP2013/pdfs/0000611.pdf

Classification of mitotic figures with convolutional neural networks and seeded blob features, Malon and Cosatto, J Pathol Inform, 2013 http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=9;epage=9;aulast=Malon;type=0

A gamma-gaussian mixture model for detection of mitotic cells in breast cancer histopathology images, Khan et al, J Pathol Inform, 2013 http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2013;volume=4;issue=1;spage=11;epage=11;aulast=Khan;type=0

Mitosis detection in breast cancer histological images An ICPR 2012 contest, Roux et al, J Pathol Inform, 2013 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709417/

Automated Image Analysis of Hodgkin lymphoma, Schmitz et al, 2012 http://arxiv.org/abs/1209.3189

Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling, Yuan et al, Sci Transl Med, 2012 http://www.ncbi.nlm.nih.gov/pubmed/23100629

A boosting cascade for automated detection of prostate cancer from digitized histology, Doyle et al, Med Image Comput Comput Assist Interv, 2006 http://www.ncbi.nlm.nih.gov/pubmed/17354810

Digital Pathology in support of big data and omics datasets

Next-Generation Pathology—Surveillance of Tumor Microecology, Koos et al, J Mol Biol, 2015 http://www.ncbi.nlm.nih.gov/pubmed/25725260

Image fusion of mass spectrometry and microscopy: a multimodality paradigm for molecular tissue mapping, Van de Plas et al, Nature Methods, 2015 http://www.nature.com/nmeth/journal/v12/n4/abs/nmeth.3296.html

Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry, Giesen et al, Nature Methods, 2014 http://www.nature.com/nmeth/journal/v11/n4/full/nmeth.2869.html

Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy, Kong et al, PNAS, 2013 http://www.pnas.org/content/110/38/15189.full.pdf

RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues, Wang et al, J Mol Diagn, 2012 http://www.ncbi.nlm.nih.gov/pubmed/22166544

Systems pathology—taking molecular pathology into a new dimension, Faratian et al, Nat Rev Clin Oncol, 2009 http://www.ncbi.nlm.nih.gov/pubmed/19581910

Non-human applications of digital pathology

FuncISH: learning a functional representation of neural ISH images, Liscovitch et al, Bioinformatics, 2013 http://bioinformatics.oxfordjournals.org/content/29/13/i36.abstract?sid=cb662af7-7667-4451-af06-d323eaaa3779

Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans, Aerni et al, Bioinformatics, 2013 http://bioinformatics.oxfordjournals.org/content/29/13/i18.full

Simultaneous recognition and segmentation of cells: application in C.elegans, Qu et al, Bioinformatics, 2011 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3187651/

A principal skeleton algorithm for standardizing confocal images of fruit fly nervous systems, Qu and Peng, Bioinformatics, 2010 http://www.ncbi.nlm.nih.gov/pubmed/20172944

Automatic reconstruction of 3D neuron structures using a graph-augmented deformable model, Peng et al, Bioinformatics, 2010 http://bioinformatics.oxfordjournals.org/cgi/pmidlookup?view=long&pmid=20529931

Histopathological Image Analysis: A Review, Gurcan et al, IEEE Rev Biomed Eng, 2009 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2910932/

Beyond two dimensions

High-resolution three-dimensional digital imaging of the human renal microcirculation: An aid to evaluating microvascular alterations in chronic kidney disease in humans, Uesugi et al, Pathology Int, 2015 http://www.ncbi.nlm.nih.gov/pubmed/?term=26289029

Books

Digital Pathology: Historical Perspectives, Current Concepts & Future Applications, 2015, Kaplan and Rao, view on Amazon

Digital pathology (SpringerBriefs in Computer Science), 2014, Sucaet and Waelput, view on Amazon

Pathology Informatics: Theory and Practice, 2012, Pantanowitz, view on Amazon

Virtual Microscopy and Virtual Slides in Teaching, Diagnosis, and Research (Advances in Pathology, Microscopy, & Molecular Morphology), 2005, Gu and Ogilvie, view on Amazon

Past and present community challenges and other initiatives

ISBI challenge on cancer metastasis detection in lymph node - camelyon16, http://camelyon16.grand-challenge.org/

MITOS-ATYPIA-14 (detection of mitosis; evaluation of nuclear atypia score), http://mitos-atypia-14.grand-challenge.org/

Assessment of Mitosis Detection Algorithms 2013 - AMIDA13, http://amida13.isi.uu.nl/

Mitosis Detection in Breast Cancer Histological Images http://ludo17.free.fr/mitos_2012/