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[DOI]
2Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies
Mousumi Roy,Fusheng Wang,Hoang Vo,Dejun Teng,George Teodoro,Alton B. Farris,Eduardo Castillo-Leon,Miriam B. Vos,Jun Kong
Laboratory Investigation.2020;100(10)1367
[DOI]
3Aufbruch in die digitale Neuropathologie
Konrad Kölble,Ingmar Blümcke
Zeitschrift für Epileptologie.2017;30(3)218
[DOI]
4Aufbruch in die digitale Neuropathologie
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Zeitschrift für Epileptologie.2016;30(3)87
[DOI]
5Integrative Models of Histopathological Image Features and Omics Data Predict Survival in Head and Neck Squamous Cell Carcinoma
Hao Zeng,Linyan Chen,Yeqian Huang,Yuling Luo,Xuelei Ma
Frontiers in Cell and Developmental Biology.2020;8(3)87
[DOI]
6Predicting primary site of secondary liver cancer with a neural estimator of metastatic origin
Geoffrey F. Schau,Erik A. Burlingame,Guillaume Thibault,Tauangtham Anekpuritanang,Ying Wang,Joe W. Gray,Christopher Corless,Young H. Chang
Journal of Medical Imaging.2020;7(01)1
[DOI]
7Artificial Intelligence–Based Screening for Mycobacteria in Whole-Slide Images of Tissue Samples
Liron Pantanowitz,Uno Wu,Lindsey Seigh,Edmund LoPresti,Fang-Cheng Yeh,Payal Salgia,Pamela Michelow,Scott Hazelhurst,Wei-Yu Chen,Douglas Hartman,Chao-Yuan Yeh
American Journal of Clinical Pathology.2021;7(01)1
[DOI]
8Content-based analysis of Ki-67 stained meningioma specimens for automatic hot-spot selection
Zaneta Swiderska-Chadaj,Tomasz Markiewicz,Bartlomiej Grala,Malgorzata Lorent
Diagnostic Pathology.2016;11(1)1
[DOI]
9A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain
Kurt G. Schilling,Yurui Gao,Matthew Christian,Vaibhav Janve,Iwona Stepniewska,Bennett A. Landman,Adam W. Anderson
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[DOI]
10A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain
Zaneta Swiderska-Chadaj,Tomasz Markiewicz,Szczepan Cierniak,Robert Koktysz
Neuroinformatics.2016;17(1)1
[DOI]
111399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
Geert Litjens,Peter Bandi,Babak Ehteshami Bejnordi,Oscar Geessink,Maschenka Balkenhol,Peter Bult,Altuna Halilovic,Meyke Hermsen,Rob van de Loo,Rob Vogels,Quirine F Manson,Nikolas Stathonikos,Alexi Baidoshvili,Paul van Diest,Carla Wauters,Marcory van Dijk,Jeroen van der Laak
GigaScience.2018;7(6)1
[DOI]
121399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
Metin N. Gurcan,John E. Tomaszewski,Naiyun Zhou,Xiaxia Yu,Tianhao Zhao,Si Wen,Fusheng Wang,Wei Zhu,Tahsin Kurc,Allen Tannenbaum,Joel Saltz,Yi Gao
GigaScience.2017;10140(6)101400K
[DOI]
13A Novel MKL Method for GBM Prognosis Prediction by Integrating Histopathological Image and Multi-Omics Data
Ya Zhang,Ao Li,Jie He,Minghui Wang
IEEE Journal of Biomedical and Health Informatics.2020;24(1)171
[DOI]
14Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor-Infiltrating Lymphocytes in Invasive Breast Cancer
Han Le,Rajarsi Gupta,Le Hou,Shahira Abousamra,Danielle Fassler,Luke Torre-Healy,Richard A. Moffitt,Tahsin Kurc,Dimitris Samaras,Rebecca Batiste,Tianhao Zhao,Arvind Rao,Alison L. Van Dyke,Ashish Sharma,Erich Bremer,Jonas S. Almeida,Joel Saltz
The American Journal of Pathology.2020;190(7)1491
[DOI]
15Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology
Gabriele Campanella,Arjun R. Rajanna,Lorraine Corsale,Peter J. Schüffler,Yukako Yagi,Thomas J. Fuchs
Computerized Medical Imaging and Graphics.2018;65(7)142
[DOI]
16Retrieve similar cell images in OpenSlide file
Jae Gu Lee,Young Woong Ko
Multimedia Tools and Applications.2019;78(5)5269
[DOI]
17Transcriptome Response and Spatial Pattern of Gene Expression in the Primate Subventricular Zone Neurogenic Niche After Cerebral Ischemia
Monika C. Chongtham,Haifang Wang,Christina Thaller,Nai-Hua Hsiao,Ivan H. Vachkov,Stoyan P. Pavlov,Lorenz H. Williamson,Tetsumori Yamashima,Anastassia Stoykova,Jun Yan,Gregor Eichele,Anton B. Tonchev
Frontiers in Cell and Developmental Biology.2020;8(5)5269
[DOI]
18An adaptable navigation strategy for Virtual Microscopy from mobile platforms
Germán Corredor,Eduardo Romero,Marcela Iregui
Journal of Biomedical Informatics.2015;54(5)39
[DOI]
19Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma
Jean Le’Clerc Arrastia,Nick Heilenkötter,Daniel Otero Baguer,Lena Hauberg-Lotte,Tobias Boskamp,Sonja Hetzer,Nicole Duschner,Jörg Schaller,Peter Maass
Journal of Imaging.2021;7(4)71
[DOI]
20Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma
Matthew G. Hanna,Liron Pantanowitz
Journal of Imaging.2019;7(4)524
[DOI]
21A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association
Mark D. Zarella,Douglas Bowman;,Famke Aeffner,Navid Farahani,Albert Xthona;,Syeda Fatima Absar,Anil Parwani,Marilyn Bui,Douglas J. Hartman
Archives of Pathology & Laboratory Medicine.2019;143(2)222
[DOI]
22A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association
Rene Bidart,Alexander Wong
Archives of Pathology & Laboratory Medicine.2019;11663(2)369
[DOI]
23A Practical Guide to Whole Slide Imaging: A White Paper From the Digital Pathology Association
Zaneta Swiderska-Chadaj,Zhaoxuan Ma,Nathan Ing,Tomasz Markiewicz,Malgorzata Lorent,Szczepan Cierniak,Ann E. Walts,Beatrice S. Knudsen,Arkadiusz Gertych
Archives of Pathology & Laboratory Medicine.2019;1011(2)13
[DOI]
24DICOM Format and Protocol Standardization—A Core Requirement for Digital Pathology Success
David A. Clunie
Toxicologic Pathology.2021;49(4)738
[DOI]
25Image-based surrogate biomarkers for molecular subtypes of colorectal cancer
Vlad Popovici,Eva Budinská,Ladislav Dušek,Michal Kozubek,Fred Bosman,Robert Murphy
Bioinformatics.2017;33(13)2002
[DOI]
26Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring
Michelle A. Wood-Trageser,Andrew J. Lesniak,Anthony J. Demetris
Transplantation.2019;103(7)1306
[DOI]
27Digital Microscopy, Image Analysis, and Virtual Slide Repository
Famke Aeffner,Hibret A Adissu,Michael C Boyle,Robert D Cardiff,Erik Hagendorn,Mark J Hoenerhoff,Robert Klopfleisch,Susan Newbigging,Dirk Schaudien,Oliver Turner,Kristin Wilson
ILAR Journal.2018;59(1)66
[DOI]
28A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor
Christof A. Bertram,Marc Aubreville,Christian Marzahl,Andreas Maier,Robert Klopfleisch
Scientific Data.2019;6(1)66
[DOI]
29Convolutional neural networks can accurately distinguish four histologic growth patterns of lung adenocarcinoma in digital slides
Arkadiusz Gertych,Zaneta Swiderska-Chadaj,Zhaoxuan Ma,Nathan Ing,Tomasz Markiewicz,Szczepan Cierniak,Hootan Salemi,Samuel Guzman,Ann E. Walts,Beatrice S. Knudsen
Scientific Reports.2019;9(1)66
[DOI]
30Inviwo — A Visualization System with Usage Abstraction Levels
Daniel Jonsson,Peter Steneteg,Erik Sunden,Rickard Englund,Sathish Kottravel,Martin Falk,Anders Ynnerman,Ingrid Hotz,Timo Ropinski
IEEE Transactions on Visualization and Computer Graphics.2020;26(11)3241
[DOI]
31Inviwo — A Visualization System with Usage Abstraction Levels
Xueyu Liu,Ming Li,Fang Hao,Guoye Zhang,Chen Wang,Xiaoshuang Zhou
IEEE Transactions on Visualization and Computer Graphics.2020;26(11)229
[DOI]
32Inviwo — A Visualization System with Usage Abstraction Levels
Sadri Salman,Zhaoxuan Ma,Sambit Mohanty,Sanica Bhele,Yung-Tien Chu,Beatrice Knudsen,Arkadiusz Gertych
IEEE Transactions on Visualization and Computer Graphics.2014;283(11)295
[DOI]
33The Emergence of Pathomics
Rajarsi Gupta,Tahsin Kurc,Ashish Sharma,Jonas S. Almeida,Joel Saltz
Current Pathobiology Reports.2019;7(3)73
[DOI]
34A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research
Marc Aubreville,Christof A. Bertram,Taryn A. Donovan,Christian Marzahl,Andreas Maier,Robert Klopfleisch
Scientific Data.2020;7(1)73
[DOI]
35PyHIST: A Histological Image Segmentation Tool
Manuel Muñoz-Aguirre,Vasilis F. Ntasis,Santiago Rojas,Roderic Guigó,Dina Schneidman-Duhovny
PLOS Computational Biology.2020;16(10)e1008349
[DOI]
36PyHIST: A Histological Image Segmentation Tool
Ramakrishnan Mukundan
PLOS Computational Biology.2017;723(10)386
[DOI]
37Fixation and Spread of Somatic Mutations in Adult Human Colonic Epithelium
Anna M. Nicholson,Cora Olpe,Alice Hoyle,Ann-Sofie Thorsen,Teja Rus,Mathilde Colombé,Roxanne Brunton-Sim,Richard Kemp,Kate Marks,Phil Quirke,Shalini Malhotra,Rogier ten Hoopen,Ashraf Ibrahim,Cecilia Lindskog,Meagan B. Myers,Barbara Parsons,Simon Tavaré,Mark Wilkinson,Edward Morrissey,Douglas J. Winton
Cell Stem Cell.2018;22(6)909
[DOI]
38Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study
Huan Yang,Lili Chen,Zhiqiang Cheng,Minglei Yang,Jianbo Wang,Chenghao Lin,Yuefeng Wang,Leilei Huang,Yangshan Chen,Sui Peng,Zunfu Ke,Weizhong Li
BMC Medicine.2021;19(1)909
[DOI]
39Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study
Blair J. Rossetti,Fusheng Wang,Pengyue Zhang,George Teodoro,Daniel J. Brat,Jun Kong
BMC Medicine.2017;19(1)424
[DOI]
40Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic images
Rikiya Yamashita,Jin Long,Atif Saleem,Daniel L. Rubin,Jeanne Shen
Scientific Reports.2021;11(1)424
[DOI]
41Using deep learning to predict anti-PD-1 response in melanoma and lung cancer patients from histopathology images
Jing Hu,Chuanliang Cui,Wenxian Yang,Lihong Huang,Rongshan Yu,Siyang Liu,Yan Kong
Translational Oncology.2021;14(1)100921
[DOI]
42Deep learning-based classification and mutation prediction from histopathological images of hepatocellular carcinoma
Haotian Liao,Yuxi Long,Ruijiang Han,Wei Wang,Lin Xu,Mingheng Liao,Zhen Zhang,Zhenru Wu,Xuequn Shang,Xuefeng Li,Jiajie Peng,Kefei Yuan,Yong Zeng
Clinical and Translational Medicine.2020;10(2)100921
[DOI]
43Retinex model based stain normalization technique for whole slide image analysis
Md. Ziaul Hoque,Anja Keskinarkaus,Pia Nyberg,Tapio Seppänen
Computerized Medical Imaging and Graphics.2021;90(2)101901
[DOI]
44Effects of glycaemic variability on cardiac remodelling after reperfused myocardial infarction: Evaluation of streptozotocin-induced diabetic Wistar rats using cardiac magnetic resonance imaging
M. Joubert,J. Hardouin,D. Legallois,K. Blanchart,N. Elie,M. Nowoczyn,P. Croisille,L. Coulbault,C. Bor-Angelier,S. Allouche,A. Manrique
Diabetes & Metabolism.2016;42(5)342
[DOI]
45Confidence-based dynamic optimization model for biomedical image mosaicking
Romuald Perrot,Pascal Bourdon,David Helbert
Journal of the Optical Society of America A.2019;36(11)C28
[DOI]
46Customizing Laboratory Information Systems
Peter Gershkovich,John H. Sinard
Advances in Anatomic Pathology.2015;22(5)323
[DOI]
47Pan-cancer analysis of the extent and consequences of intratumor heterogeneity
Noemi Andor,Trevor A Graham,Marnix Jansen,Li C Xia,C Athena Aktipis,Claudia Petritsch,Hanlee P Ji,Carlo C Maley
Nature Medicine.2016;22(1)105
[DOI]
48Machine learning approaches to analyze histological images of tissues from radical prostatectomies
Arkadiusz Gertych,Nathan Ing,Zhaoxuan Ma,Thomas J. Fuchs,Sadri Salman,Sambit Mohanty,Sanica Bhele,Adriana Velásquez-Vacca,Mahul B. Amin,Beatrice S. Knudsen
Computerized Medical Imaging and Graphics.2015;46(1)197
[DOI]
49Personalized Oncology Suite: integrating next-generation sequencing data and whole-slide bioimages
Andreas Dander,Matthias Baldauf,Michael Sperk,Stephan Pabinger,Benjamin Hiltpolt,Zlatko Trajanoski
BMC Bioinformatics.2014;15(1)306
[DOI]
50Examination of Independent Prognostic Power of Gene Expressions and Histopathological Imaging Features in Cancer
Tingyan Zhong,Mengyun Wu,Shuangge Ma
Cancers.2019;11(3)361
[DOI]
51Examination of Independent Prognostic Power of Gene Expressions and Histopathological Imaging Features in Cancer
Athanasios Kallipolitis,Ilias Maglogiannis
Cancers.2019;11(3)7036
[DOI]
52Unmasking the immune microecology of ductal carcinoma in situ with deep learning
Priya Lakshmi Narayanan,Shan E. Ahmed Raza,Allison H. Hall,Jeffrey R. Marks,Lorraine King,Robert B. West,Lucia Hernandez,Naomi Guppy,Mitch Dowsett,Barry Gusterson,Carlo Maley,E. Shelley Hwang,Yinyin Yuan
npj Breast Cancer.2021;7(1)7036
[DOI]
53Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Gabriele Campanella,Matthew G. Hanna,Luke Geneslaw,Allen Miraflor,Vitor Werneck Krauss Silva,Klaus J. Busam,Edi Brogi,Victor E. Reuter,David S. Klimstra,Thomas J. Fuchs
Nature Medicine.2019;25(8)1301
[DOI]
54Cytomine: Toward an Open and Collaborative Software Platform for Digital Pathology Bridged to Molecular Investigations
Ulysse Rubens,Renaud Hoyoux,Laurent Vanosmael,Mehdy Ouras,Maxime Tasset,Christopher Hamilton,Rémi Longuespée,Raphaël Marée
PROTEOMICS – Clinical Applications.2019;13(1)1800057
[DOI]
55Robot-Guided Atomic Force Microscopy for Mechano-Visual Phenotyping of Cancer Specimens
Wenjin Chen,Zachary Brandes,Rajarshi Roy,Marina Chekmareva,Hardik J. Pandya,Jaydev P. Desai,David J. Foran
Microscopy and Microanalysis.2015;21(5)1224
[DOI]
56Robot-Guided Atomic Force Microscopy for Mechano-Visual Phenotyping of Cancer Specimens
Andrew J. Schaumberg,S. Joseph Sirintrapun,Hikmat A. Al-Ahmadie,Peter J. Schüffler,Thomas J. Fuchs
Microscopy and Microanalysis.2017;10477(5)42
[DOI]
57Technical Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper
David A. Clunie,Don K. Dennison,Dawn Cram,Kenneth R. Persons,Mark D. Bronkalla,Henri “Rik” Primo
Journal of Digital Imaging.2016;29(5)583
[DOI]
58Technical Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper
Marc Aubreville,Christof Bertram,Robert Klopfleisch,Andreas Maier
Journal of Digital Imaging.2018;29(5)309
[DOI]
59Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images
Yoshimasa Kawazoe,Kiminori Shimamoto,Ryohei Yamaguchi,Yukako Shintani-Domoto,Hiroshi Uozaki,Masashi Fukayama,Kazuhiko Ohe
Journal of Imaging.2018;4(7)91
[DOI]
60Image Features Based on Characteristic Curves and Local Binary Patterns for Automated HER2 Scoring
Ramakrishnan Mukundan
Journal of Imaging.2018;4(2)35
[DOI]
61Image Features Based on Characteristic Curves and Local Binary Patterns for Automated HER2 Scoring
Rui Lebre,Rui Jesus,Pedro Nunes,Carlos Costa
Journal of Imaging.2021;1400(2)407
[DOI]
62Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma
Hao Zeng,Jianrui Ji,Xindi Song,Yeqian Huang,Hui Li,Juan Huang,Xuelei Ma
Frontiers in Genetics.2020;11(2)407
[DOI]
63Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma
Sébastien Besson,Roger Leigh,Melissa Linkert,Chris Allan,Jean-Marie Burel,Mark Carroll,David Gault,Riad Gozim,Simon Li,Dominik Lindner,Josh Moore,Will Moore,Petr Walczysko,Frances Wong,Jason R. Swedlow
Frontiers in Genetics.2019;11435(2)3
[DOI]
64Rocky road to digital diagnostics: implementation issues and exhilarating experiences
Nikolaos Stathonikos,Tri Q Nguyen,Paul J van Diest
Journal of Clinical Pathology.2020;11435(2)jclinpath-2020-206715
[DOI]
65EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
Christian Marzahl,Marc Aubreville,Christof A. Bertram,Jennifer Maier,Christian Bergler,Christine Kröger,Jörn Voigt,Katharina Breininger,Robert Klopfleisch,Andreas Maier
Scientific Reports.2021;11(1)jclinpath-2020-206715
[DOI]
66EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
A. Kallipolitis,I. Maglogiannis
Scientific Reports.2018;519(1)374
[DOI]
67Automated detection and quantification of breast cancer brain metastases in an animal model using democratized machine learning tools
Dina Sikpa,Jérémie P. Fouquet,Réjean Lebel,Phedias Diamandis,Maxime Richer,Martin Lepage
Scientific Reports.2019;9(1)374
[DOI]
68ImageBox 2 – Efficient and rapid access of image tiles from whole-slide images using serverless HTTP range requests
Erich Bremer,Joel Saltz,JonasS Almeida
Journal of Pathology Informatics.2020;11(1)29
[DOI]
69Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer
Renan Valieris,Lucas Amaro,Cynthia Aparecida Bueno de Toledo Osório,Adriana Passos Bueno,Rafael Andres Rosales Mitrowsky,Dirce Maria Carraro,Diana Noronha Nunes,Emmanuel Dias-Neto,Israel Tojal da Silva
Cancers.2020;12(12)3687
[DOI]
70Deep Learning Predicts Underlying Features on Pathology Images with Therapeutic Relevance for Breast and Gastric Cancer
Michael Nalisnik,David A Gutman,Jun Kong,Lee A D Cooper
Cancers.2015;12(12)928
[DOI]
71Characterization of tumor-associated T-lymphocyte subsets and immune checkpoint molecules in head and neck squamous cell carcinoma
Axel Lechner,Hans Schlößer,Sacha I. Rothschild,Martin Thelen,Sabrina Reuter,Peter Zentis,Alexander Shimabukuro-Vornhagen,Sebastian Theurich,Kerstin Wennhold,Maria Garcia-Marquez,Lars Tharun,Alexander Quaas,Astrid Schauss,Jörg Isensee,Tim Hucho,Christian Huebbers,Michael von Bergwelt-Baildon,Dirk Beutner
Oncotarget.2017;8(27)44418
[DOI]
72QuPath: Open source software for digital pathology image analysis
Peter Bankhead,Maurice B. Loughrey,José A. Fernández,Yvonne Dombrowski,Darragh G. McArt,Philip D. Dunne,Stephen McQuaid,Ronan T. Gray,Liam J. Murray,Helen G. Coleman,Jacqueline A. James,Manuel Salto-Tellez,Peter W. Hamilton
Scientific Reports.2017;7(1)44418
[DOI]
73An integrated iterative annotation technique for easing neural network training in medical image analysis
Brendon Lutnick,Brandon Ginley,Darshana Govind,Sean D. McGarry,Peter S. LaViolette,Rabi Yacoub,Sanjay Jain,John E. Tomaszewski,Kuang-Yu Jen,Pinaki Sarder
Nature Machine Intelligence.2019;1(2)112
[DOI]
74Identification of “BRAF-Positive” Cases Based on Whole-Slide Image Analysis
Vlad Popovici,Aleš Krenek,Eva Budinská
BioMed Research International.2017;2017(2)1
[DOI]
75QuArray: an application for tissue array whole slide image export and signal analysis
Callum Arthurs,Aamir Ahmed,Jonathan Wren
Bioinformatics.2021;2017(2)1
[DOI]
76Pathadin – The essential set of tools to start with whole slide analysis
Georgi Dzaparidze,Dmitri Kazachonok,Kristi Laht,Heleri Taelma,Ave Minajeva
Acta Histochemica.2020;122(7)151619
[DOI]
77Pathadin – The essential set of tools to start with whole slide analysis
Inderpreet Kaur,Kamaljit Singh Saini,Jaiteg Singh Khaira
Acta Histochemica.2020;122(7)263
[DOI]
78Pathadin – The essential set of tools to start with whole slide analysis
Donglin Di,Shengrui Li,Jun Zhang,Yue Gao
Acta Histochemica.2020;12265(7)428
[DOI]
79Open access image repositories: high-quality data to enable machine learning research
F. Prior,J. Almeida,P. Kathiravelu,T. Kurc,K. Smith,T.J. Fitzgerald,J. Saltz
Clinical Radiology.2020;75(1)7
[DOI]
80Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned
Gerald Li,Peter Bankhead,Philip D Dunne,Paul G O’Reilly,Jacqueline A James,Manuel Salto-Tellez,Peter W Hamilton,Darragh G McArt
Briefings in Bioinformatics.2016;75(1)bbw044
[DOI]
81SlideJ: An ImageJ plugin for automated processing of whole slide images
Vincenzo Della Mea,Giulia L. Baroni,David Pilutti,Carla Di Loreto,Helmut Ahammer
PLOS ONE.2017;12(7)e0180540
[DOI]
82SlideJ: An ImageJ plugin for automated processing of whole slide images
Yves Sucaet,Wim Waelput
PLOS ONE.2014;12(7)43
[DOI]
83A Tunable Diffusion-Consumption Mechanism of Cytokine Propagation Enables Plasticity in Cell-to-Cell Communication in the Immune System
Alon Oyler-Yaniv,Jennifer Oyler-Yaniv,Benjamin M. Whitlock,Zhiduo Liu,Ronald N. Germain,Morgan Huse,Grégoire Altan-Bonnet,Oleg Krichevsky
Immunity.2017;46(4)609
[DOI]
84A Tunable Diffusion-Consumption Mechanism of Cytokine Propagation Enables Plasticity in Cell-to-Cell Communication in the Immune System
Zhaoxuan Ma,Jiayun Li,Hootan Salemi,Corey Arnold,Beatrice S. Knudsen,Arkadiusz Gertych,Nathan Ing,Metin N. Gurcan,John E. Tomaszewski
Immunity.2018;46(4)46
[DOI]
85A Tunable Diffusion-Consumption Mechanism of Cytokine Propagation Enables Plasticity in Cell-to-Cell Communication in the Immune System
Rashika Mishra,Ovidiu Daescu,Patrick Leavey,Dinesh Rakheja,Anita Sengupta
Immunity.2017;10330(4)12
[DOI]
86Sparse coding of pathology slides compared to transfer learning with deep neural networks
Will Fischer,Sanketh S. Moudgalya,Judith D. Cohn,Nga T. T. Nguyen,Garrett T. Kenyon
BMC Bioinformatics.2018;19(S18)12
[DOI]
87Sparse coding of pathology slides compared to transfer learning with deep neural networks
Xiao Ma,Fucang Jia
BMC Bioinformatics.2020;11993(S18)343
[DOI]
88A computational method for three-dimensional reconstruction of the microarchitecture of myometrial smooth muscle from histological sections
E. Josiah Lutton,Wim J. E. P. Lammers,Sean James,Hugo A. van den Berg,Andrew M. Blanks,Roger C. Young
PLOS ONE.2017;12(3)e0173404
[DOI]
89Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks
Kun-Hsing Yu,Feiran Wang,Gerald J Berry,Christopher Ré,Russ B Altman,Michael Snyder,Isaac S Kohane
Journal of the American Medical Informatics Association.2020;27(5)757
[DOI]
90AI in Medical Imaging Informatics: Current Challenges and Future Directions
Andreas S. Panayides,Amir Amini,Nenad D. Filipovic,Ashish Sharma,Sotirios A. Tsaftaris,Alistair Young,David Foran,Nhan Do,Spyretta Golemati,Tahsin Kurc,Kun Huang,Konstantina S. Nikita,Ben P. Veasey,Michalis Zervakis,Joel H. Saltz,Constantinos S. Pattichis
IEEE Journal of Biomedical and Health Informatics.2020;24(7)1837
[DOI]
91OpenTein: a database of digital whole-slide images of stem cell-derived teratomas
Sung-Joon Park,Yusuke Komiyama,Hirofumi Suemori,Akihiro Umezawa,Kenta Nakai
Nucleic Acids Research.2016;44(D1)D1000
[DOI]
92OpenTein: a database of digital whole-slide images of stem cell-derived teratomas
Nabila Shawki,M. Golam Shadin,Tarek Elseify,Luke Jakielaszek,Tunde Farkas,Yuri Persidsky,Nirag Jhala,Iyad Obeid,Joseph Picone
Nucleic Acids Research.2020;44(D1)69
[DOI]
93A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk
Sergey Klimov,Islam M. Miligy,Arkadiusz Gertych,Yi Jiang,Michael S. Toss,Padmashree Rida,Ian O. Ellis,Andrew Green,Uma Krishnamurti,Emad A. Rakha,Ritu Aneja
Breast Cancer Research.2019;21(1)69
[DOI]
94A 2021 update on cancer image analytics with deep learning
Nikhil Cherian Kurian,Amit Sethi,Anil Reddy Konduru,Abhishek Mahajan,Swapnil Ulhas Rane
WIREs Data Mining and Knowledge Discovery.2021;21(1)69
[DOI]
95Automated Histology Analysis: Opportunities for signal processing
Michael T McCann,John A. Ozolek,Carlos A. Castro,Bahram Parvin,Jelena Kovacevic
IEEE Signal Processing Magazine.2015;32(1)78
[DOI]
96Automated Histology Analysis: Opportunities for signal processing
Klaus Strohmenger,Christian Herta,Oliver Fischer,Jonas Annuscheit,Peter Hufnagl
IEEE Signal Processing Magazine.2020;12090(1)155
[DOI]
97DomainBuilder: the knowledge authoring system for SlideTutor Intelligent Tutoring system
Eugene Tseytlin,Faina Linkov,Melissa Castine,Elizabeth Legowski,Rebecca S. Jacobson
F1000Research.2018;7(1)1721
[DOI]
98A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images
Fahdi Kanavati,Gouji Toyokawa,Seiya Momosaki,Hiroaki Takeoka,Masaki Okamoto,Koji Yamazaki,Sadanori Takeo,Osamu Iizuka,Masayuki Tsuneki
Scientific Reports.2021;11(1)1721
[DOI]
99Enhanced image similarity analysis system in digital pathology
Jae-Gu Lee,Kyung-Chan Choi,Seung-Ho Yeon,Jeong Won Kim,Young-Woong Ko
Multimedia Tools and Applications.2017;76(23)25477
[DOI]
100Enhanced image similarity analysis system in digital pathology
Aparna Kanakatte,Rakshith Subramanya,Ashik Delampady,Rajarama Nayak,Balamuralidhar Purushothaman,Jayavardhana Gubbi
Multimedia Tools and Applications.2017;76(23)1202
[DOI]
101Enhanced image similarity analysis system in digital pathology
Zaneta Swiderska-Chadaj,Tomasz Markiewicz,Bartlomiej Grala,Malgorzata Lorent,Arkadiusz Gertych
Multimedia Tools and Applications.2017;723(23)448
[DOI]
102Enhanced image similarity analysis system in digital pathology
Mousumi Roy,Fusheng Wang,George Teodoro,Miriam B Vos,Alton Brad Farris,Jun Kong
Multimedia Tools and Applications.2018;723(23)810
[DOI]
103Enhanced image similarity analysis system in digital pathology
Pargorn Puttapirat,Chen Li,Haichuan Zhang,Jingyi Deng,Yuxin Dong,Jiangbo Shi,Hongyu He,Zeyu Gao,Chunbao Wang,Xiangrong Zhang
Multimedia Tools and Applications.2019;723(23)2696
[DOI]
104Whole Slide Imaging: Technology and Applications
Matthew G. Hanna,Anil Parwani,Sahussapont Joseph Sirintrapun
Advances in Anatomic Pathology.2020;27(4)251
[DOI]
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