Literature DB >> 24759275

Breast cancer histopathology image analysis: a review.

Mitko Veta, Josien P W Pluim, Paul J van Diest, Max A Viergever.   

Abstract

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

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Mesh:

Year:  2014        PMID: 24759275     DOI: 10.1109/TBME.2014.2303852

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  84 in total

1.  A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Authors:  David Romo-Bucheli; Andrew Janowczyk; Hannah Gilmore; Eduardo Romero; Anant Madabhushi
Journal:  Cytometry A       Date:  2017-02-13       Impact factor: 4.355

2.  Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images.

Authors:  Jun Xu; Lei Gong; Guanhao Wang; Cheng Lu; Hannah Gilmore; Shaoting Zhang; Anant Madabhushi
Journal:  J Med Imaging (Bellingham)       Date:  2019-02-08

3.  Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships.

Authors:  Nuh Hatipoglu; Gokhan Bilgin
Journal:  Med Biol Eng Comput       Date:  2017-02-28       Impact factor: 2.602

4.  Interactive thyroid whole slide image diagnostic system using deep representation.

Authors:  Pingjun Chen; Xiaoshuang Shi; Yun Liang; Yuan Li; Lin Yang; Paul D Gader
Journal:  Comput Methods Programs Biomed       Date:  2020-06-27       Impact factor: 5.428

5.  Robust Cell Detection and Segmentation for Image Cytometry Reveal Th17 Cell Heterogeneity.

Authors:  Takahiro Tsujikawa; Guillaume Thibault; Vahid Azimi; Sam Sivagnanam; Grace Banik; Casey Means; Rie Kawashima; Daniel R Clayburgh; Joe W Gray; Lisa M Coussens; Young Hwan Chang
Journal:  Cytometry A       Date:  2019-02-04       Impact factor: 4.355

6.  Identification of novel biomarkers associated with poor patient outcomes in invasive breast carcinoma.

Authors:  Renata A Canevari; Fabio A Marchi; Maria A C Domingues; Victor Piana de Andrade; José R F Caldeira; Sergio Verjovski-Almeida; Silvia R Rogatto; Eduardo M Reis
Journal:  Tumour Biol       Date:  2016-08-02

7.  Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy.

Authors:  Minbiao Ji; Spencer Lewis; Sandra Camelo-Piragua; Shakti H Ramkissoon; Matija Snuderl; Sriram Venneti; Amanda Fisher-Hubbard; Mia Garrard; Dan Fu; Anthony C Wang; Jason A Heth; Cormac O Maher; Nader Sanai; Timothy D Johnson; Christian W Freudiger; Oren Sagher; Xiaoliang Sunney Xie; Daniel A Orringer
Journal:  Sci Transl Med       Date:  2015-10-14       Impact factor: 17.956

8.  Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images.

Authors:  Babak Ehteshami Bejnordi; Guido Zuidhof; Maschenka Balkenhol; Meyke Hermsen; Peter Bult; Bram van Ginneken; Nico Karssemeijer; Geert Litjens; Jeroen van der Laak
Journal:  J Med Imaging (Bellingham)       Date:  2017-12-14

Review 9.  Review of quantitative multiscale imaging of breast cancer.

Authors:  Michael A Pinkert; Lonie R Salkowski; Patricia J Keely; Timothy J Hall; Walter F Block; Kevin W Eliceiri
Journal:  J Med Imaging (Bellingham)       Date:  2018-01-22

Review 10.  Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

Authors:  Fuyong Xing; Lin Yang
Journal:  IEEE Rev Biomed Eng       Date:  2016-01-06
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