Literature DB >> 21600733

Multi-resolution graph-based analysis of histopathological whole slide images: application to mitotic cell extraction and visualization.

Vincent Roullier1, Olivier Lézoray, Vinh-Thong Ta, Abderrahim Elmoataz.   

Abstract

In this paper, we present a graph-based multi-resolution approach for mitosis extraction in breast cancer histological whole slide images. The proposed segmentation uses a multi-resolution approach which reproduces the slide examination done by a pathologist. Each resolution level is analyzed with a focus of attention resulting from a coarser resolution level analysis. At each resolution level, a spatial refinement by label regularization is performed to obtain more accurate segmentation around boundaries. The proposed segmentation is fully unsupervised by using domain specific knowledge.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21600733     DOI: 10.1016/j.compmedimag.2011.02.005

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  19 in total

1.  Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images.

Authors:  Ramin Nateghi; Habibollah Danyali; Mohammad Sadegh Helfroush
Journal:  J Med Syst       Date:  2017-08-14       Impact factor: 4.460

2.  Multiview boosting digital pathology analysis of prostate cancer.

Authors:  Jin Tae Kwak; Stephen M Hewitt
Journal:  Comput Methods Programs Biomed       Date:  2017-02-22       Impact factor: 5.428

3.  A Multi-Classifier System for Automatic Mitosis Detection in Breast Histopathology Images Using Deep Belief Networks.

Authors:  K Sabeena Beevi; Madhu S Nair; G R Bindu
Journal:  IEEE J Transl Eng Health Med       Date:  2017-04-25       Impact factor: 3.316

4.  Computer-aided diagnostics in digital pathology: automated evaluation of early-phase pancreatic cancer in mice.

Authors:  Leeor Langer; Yoav Binenbaum; Leonid Gugel; Moran Amit; Ziv Gil; Shai Dekel
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-10-30       Impact factor: 2.924

5.  A gamma-gaussian mixture model for detection of mitotic cells in breast cancer histopathology images.

Authors:  Adnan Mujahid Khan; Hesham Eldaly; Nasir M Rajpoot
Journal:  J Pathol Inform       Date:  2013-05-30

6.  Automated mitosis detection in histopathology using morphological and multi-channel statistics features.

Authors:  Humayun Irshad
Journal:  J Pathol Inform       Date:  2013-05-30

7.  Mitosis detection in breast cancer histological images An ICPR 2012 contest.

Authors:  Ludovic Roux; Daniel Racoceanu; Nicolas Loménie; Maria Kulikova; Humayun Irshad; Jacques Klossa; Frédérique Capron; Catherine Genestie; Gilles Le Naour; Metin N Gurcan
Journal:  J Pathol Inform       Date:  2013-05-30

8.  Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Authors:  Humayun Irshad; Sepehr Jalali; Ludovic Roux; Daniel Racoceanu; Lim Joo Hwee; Gilles Le Naour; Frédérique Capron
Journal:  J Pathol Inform       Date:  2013-03-30

9.  HyMaP: A hybrid magnitude-phase approach to unsupervised segmentation of tumor areas in breast cancer histology images.

Authors:  Adnan M Khan; Hesham El-Daly; Emma Simmons; Nasir M Rajpoot
Journal:  J Pathol Inform       Date:  2013-03-30

10.  Comparison of the manual, semiautomatic, and automatic selection and leveling of hot spots in whole slide images for Ki-67 quantification in meningiomas.

Authors:  Zaneta Swiderska; Anna Korzynska; Tomasz Markiewicz; Malgorzata Lorent; Jakub Zak; Anna Wesolowska; Lukasz Roszkowiak; Janina Slodkowska; Bartlomiej Grala
Journal:  Anal Cell Pathol (Amst)       Date:  2015-07-09       Impact factor: 2.916

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