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Augmenting the Pathology Lab: An Intelligent Whole Slide Image
  Classification System for the Real World

Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World

24 September 2019
Julianna D. Ianni
R. Soans
Sivaramakrishnan Sankarapandian
R. V. Chamarthi
Devi Ayyagari
Thomas G. Olsen
Michael J. Bonham
Coleman C. Stavish
K. Motaparthi
C. Cockerell
T. A. Feeser
Jason B. Lee
ArXivPDFHTML

Papers citing "Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World"

10 / 10 papers shown
Title
Automated Gleason Grading of Prostate Biopsies using Deep Learning
Automated Gleason Grading of Prostate Biopsies using Deep Learning
W. Bulten
H. Pinckaers
H. V. van Boven
R. Vink
Thomas de Bel
Bram van Ginneken
J. A. van der Laak
C. Hulsbergen–van de Kaa
G. Litjens
78
449
0
18 Jul 2019
An attention-based multi-resolution model for prostate whole slide
  imageclassification and localization
An attention-based multi-resolution model for prostate whole slide imageclassification and localization
Jiayun Li
Wenyuan Li
Arkadiusz Gertych
Beatrice Knudsen
W. Speier
C. Arnold
79
36
0
30 May 2019
Ink removal from histopathology whole slide images by combining
  classification, detection and image generation models
Ink removal from histopathology whole slide images by combining classification, detection and image generation models
Sharib Ali
N. K. Alham
C. Verrill
J. Rittscher
MedIm
16
22
0
10 May 2019
Quantifying the effects of data augmentation and stain color
  normalization in convolutional neural networks for computational pathology
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
David Tellez
G. Litjens
Péter Bándi
W. Bulten
J. Bokhorst
F. Ciompi
Jeroen van der Laak
MedIm
OOD
15
478
0
18 Feb 2019
Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI
  Cancer Detection
Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection
Timo Kohlberger
Yun-Hui Liu
M. Moran
Po-Hsuan Cameron Chen
Chen
Trissia Brown
C. Mermel
J. Hipp
Martin C. Stumpe
41
78
0
15 Jan 2019
Context-Aware Learning using Transferable Features for Classification of
  Breast Cancer Histology Images
Context-Aware Learning using Transferable Features for Classification of Breast Cancer Histology Images
Ruqayya Awan
Navid Alemi Koohbanani
Muhammad Shaban
A. Lisowska
Nasir M. Rajpoot
23
62
0
12 Feb 2018
Learning to diagnose from scratch by exploiting dependencies among
  labels
Learning to diagnose from scratch by exploiting dependencies among labels
L. Yao
Eric Poblenz
Dmitry Dagunts
Ben Covington
D. Bernard
Kevin Lyman
36
333
0
28 Oct 2017
Deep-Learning for Classification of Colorectal Polyps on Whole-Slide
  Images
Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images
Bruno Korbar
Andrea M. Olofson
Allen P. Miraflor
Katherine M. Nicka
M. Suriawinata
Lorenzo Torresani
A. Suriawinata
Saeed Hassanpour
MedIm
36
277
0
05 Mar 2017
The importance of stain normalization in colorectal tissue
  classification with convolutional networks
The importance of stain normalization in colorectal tissue classification with convolutional networks
F. Ciompi
Oscar G. F. Geessink
B. Bejnordi
Gabriel Silva de Souza
A. Baidoshvili
G. Litjens
Bram van Ginneken
Iris Nagtegaal
Jeroen van der Laak
MedIm
19
201
0
20 Feb 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
383
9,233
0
06 Jun 2015
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