Literature DB >> 16900681

High-throughput analysis of multispectral images of breast cancer tissue.

Umesh Adiga1, Ravikanth Malladi, Rodrigo Fernandez-Gonzalez, Carlos Ortiz de Solorzano.   

Abstract

Statistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast.

Entities:  

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Year:  2006        PMID: 16900681     DOI: 10.1109/tip.2006.875205

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  11 in total

1.  Cell segmentation using front vector flow guided active contours.

Authors:  Fuhai Li; Xiaobo Zhou; Hong Zhao; Stephen T C Wong
Journal:  Med Image Comput Comput Assist Interv       Date:  2009

2.  Histology image analysis for carcinoma detection and grading.

Authors:  Lei He; L Rodney Long; Sameer Antani; George R Thoma
Journal:  Comput Methods Programs Biomed       Date:  2012-03-20       Impact factor: 5.428

3.  Feature-Based Representation Improves Color Decomposition and Nuclear Detection Using a Convolutional Neural Network.

Authors:  Mina Khoshdeli; Bahram Parvin
Journal:  IEEE Trans Biomed Eng       Date:  2018-03       Impact factor: 4.538

4.  Automated noninvasive classification of renal cancer on multiphase CT.

Authors:  Marius George Linguraru; Shijun Wang; Furhawn Shah; Rabindra Gautam; James Peterson; W Marston Linehan; Ronald M Summers
Journal:  Med Phys       Date:  2011-10       Impact factor: 4.071

Review 5.  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

6.  Detection and classification of thyroid follicular lesions based on nuclear structure from histopathology images.

Authors:  Wei Wang; John A Ozolek; Gustavo K Rohde
Journal:  Cytometry A       Date:  2010-05       Impact factor: 4.355

7.  Multiple nuclei tracking using integer programming for quantitative cancer cell cycle analysis.

Authors:  Fuhai Li; Xiaobo Zhou; Jinwen Ma; Stephen T C Wong
Journal:  IEEE Trans Med Imaging       Date:  2009-07-28       Impact factor: 10.048

8.  Workflow and methods of high-content time-lapse analysis for quantifying intracellular calcium signals.

Authors:  Fuhai Li; Xiaobo Zhou; Jinmin Zhu; Weiming Xia; Jinwen Ma; Stephen T C Wong
Journal:  Neuroinformatics       Date:  2008-05-28

9.  A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching.

Authors:  Cheng Chen; Wei Wang; John A Ozolek; Gustavo K Rohde
Journal:  Cytometry A       Date:  2013-04-08       Impact factor: 4.355

10.  High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

Authors:  Fuhai Li; Xiaobo Zhou; Jinmin Zhu; Jinwen Ma; Xudong Huang; Stephen T C Wong
Journal:  BMC Biotechnol       Date:  2007-10-09       Impact factor: 2.563

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