Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent (Q33572428)

28 July 2017

title

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent (English)

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28 July 2017

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Angel Cruz-Roa

1

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Anant Madabhushi

object named as

Anant Madabhushi

9

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author name string

Hannah Gilmore

2

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28 July 2017

Ajay Basavanhally

3

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28 July 2017

Michael Feldman

4

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28 July 2017

Shridar Ganesan

5

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28 July 2017

Natalie N C Shih

6

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28 July 2017

John Tomaszewski

7

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28 July 2017

Fabio A González

8

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28 July 2017

language of work or name

English

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publication date

18 April 2017

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28 July 2017

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28 July 2017

volume

7

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28 July 2017

page(s)

46450

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Creative Commons Attribution 4.0 International

28 July 2017

copyright license

start time

18 April 2017

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April 2022 Public Data File from Crossref

copyright status

copyrighted

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cites work

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21 June 2018

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Assessment of algorithms for mitosis detection in breast cancer histopathology images

21 June 2018

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Inter-observer variability between general pathologists and a specialist in breast pathology in the diagnosis of lobular neoplasia, columnar cell lesions, atypical ductal hyperplasia and ductal carcinoma in situ of the breast.

21 June 2018

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Removing batch effects from histopathological images for enhanced cancer diagnosis

21 June 2018

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Breast cancer histopathology image analysis: a review

21 June 2018

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A quantitative histomorphometric classifier (QuHbIC) identifies aggressive versus indolent p16-positive oropharyngeal squamous cell carcinoma.

21 June 2018

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21 June 2018

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Classification of mitotic figures with convolutional neural networks and seeded blob features

21 June 2018

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21 June 2018

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21 June 2018

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Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides

21 June 2018

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Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX

21 June 2018

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Histology image analysis for carcinoma detection and grading

21 June 2018

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Computational pathology: challenges and promises for tissue analysis

21 June 2018

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Computerized classification of intraductal breast lesions using histopathological images

21 June 2018

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Mucinous carcinoma of the breast is genomically distinct from invasive ductal carcinomas of no special type

21 June 2018

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Histopathological image analysis: a review

21 June 2018

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21 June 2018

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Interobserver agreement and reproducibility in classification of invasive breast carcinoma: an NCI breast cancer family registry study

21 June 2018

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21 June 2018

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Comparison of the prognostic value of Scarff-Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: major importance of the mitotic count as a component of both grading systems

21 June 2018

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21 June 2018

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21 June 2018

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Comparison of Pathologist-Detected and Automated Computer-Assisted Image Analysis Detected Sentinel Lymph Node Micrometastases in Breast Cancer

31 October 2018

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12 December 2020

A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection

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12 December 2020

Digital pathology image analysis: opportunities and challenges

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12 December 2020

Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks

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A boosting cascade for automated detection of prostate cancer from digitized histology

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Image segmentation with implicit color standardization using spatially constrained expectation maximization: detection of nuclei

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12 December 2020

Identifiers

DOI

10.1038/SREP46450

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Dimensions Publication ID

28 July 2017

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28 July 2017

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