Literature DB >> 28347240

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.

Jia-Mei Chen1, Yan Li1,2, Jun Xu3, Lei Gong3, Lin-Wei Wang1, Wen-Lou Liu1, Juan Liu4.   

Abstract

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature-based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

Entities:  

Keywords:  Breast cancer; computer-aided prognosis; hematoxylin and eosin histopathology image; image analysis

Mesh:

Substances:

Year:  2017        PMID: 28347240     DOI: 10.1177/1010428317694550

Source DB:  PubMed          Journal:  Tumour Biol        ISSN: 1010-4283


  8 in total

1.  Digital Microscopy, Image Analysis, and Virtual Slide Repository.

Authors:  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
Journal:  ILAR J       Date:  2018-12-01

2.  Multi-Class Classification of Breast Cancer Using 6B-Net with Deep Feature Fusion and Selection Method.

Authors:  Muhammad Junaid Umer; Muhammad Sharif; Seifedine Kadry; Abdullah Alharbi
Journal:  J Pers Med       Date:  2022-04-26

3.  Stain normalization in digital pathology: Clinical multi-center evaluation of image quality.

Authors:  Nicola Michielli; Alessandro Caputo; Manuela Scotto; Alessandro Mogetta; Orazio Antonino Maria Pennisi; Filippo Molinari; Davide Balmativola; Martino Bosco; Alessandro Gambella; Jasna Metovic; Daniele Tota; Laura Carpenito; Paolo Gasparri; Massimo Salvi
Journal:  J Pathol Inform       Date:  2022-09-24

4.  Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses.

Authors:  Liron Pantanowitz; Douglas Hartman; Yan Qi; Eun Yoon Cho; Beomseok Suh; Kyunghyun Paeng; Rajiv Dhir; Pamela Michelow; Scott Hazelhurst; Sang Yong Song; Soo Youn Cho
Journal:  Diagn Pathol       Date:  2020-07-04       Impact factor: 2.644

Review 5.  Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association.

Authors:  Famke Aeffner; Mark D Zarella; Nathan Buchbinder; Marilyn M Bui; Matthew R Goodman; Douglas J Hartman; Giovanni M Lujan; Mariam A Molani; Anil V Parwani; Kate Lillard; Oliver C Turner; Venkata N P Vemuri; Ana G Yuil-Valdes; Douglas Bowman
Journal:  J Pathol Inform       Date:  2019-03-08

6.  Using parallel pre-trained types of DCNN model to predict breast cancer with color normalization.

Authors:  William Al Noumah; Assef Jafar; Kadan Al Joumaa
Journal:  BMC Res Notes       Date:  2022-01-10

7.  Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade.

Authors:  Andrew Lagree; Audrey Shiner; Marie Angeli Alera; Lauren Fleshner; Ethan Law; Brianna Law; Fang-I Lu; David Dodington; Sonal Gandhi; Elzbieta A Slodkowska; Alex Shenfield; Katarzyna J Jerzak; Ali Sadeghi-Naini; William T Tran
Journal:  Curr Oncol       Date:  2021-10-27       Impact factor: 3.677

8.  Breast Cancer Molecular Subtype Prediction on Pathological Images with Discriminative Patch Selection and Multi-Instance Learning.

Authors:  Hong Liu; Wen-Dong Xu; Zi-Hao Shang; Xiang-Dong Wang; Hai-Yan Zhou; Ke-Wen Ma; Huan Zhou; Jia-Lin Qi; Jia-Rui Jiang; Li-Lan Tan; Hui-Min Zeng; Hui-Juan Cai; Kuan-Song Wang; Yue-Liang Qian
Journal:  Front Oncol       Date:  2022-04-14       Impact factor: 5.738

  8 in total

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