Literature DB >> 25475487

Heterogeneity assessment of histological tissue sections in whole slide images.

Philippe Belhomme1, Simon Toralba2, Benoît Plancoulaine3, Myriam Oger4, Metin N Gurcan5, Catherine Bor-Angelier4.   

Abstract

Computerized image analysis (IA) can provide quantitative and repeatable object measurements by means of methods such as segmentation, indexation, classification, etc. Embedded in reliable automated systems, IA could help pathologists in their daily work and thus contribute to more accurate determination of prognostic histological factors on whole slide images. One of the key concept pathologists want to dispose of now is a numerical estimation of heterogeneity. In this study, the objective is to propose a general framework based on the diffusion maps technique for measuring tissue heterogeneity in whole slide images and to apply this methodology on breast cancer histopathology digital images.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; Dimensionality reduction; Heterogeneity; Spectral graph theory; Whole slide image

Mesh:

Year:  2014        PMID: 25475487     DOI: 10.1016/j.compmedimag.2014.11.006

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


  7 in total

1.  Histopathological imaging-based cancer heterogeneity analysis via penalized fusion with model averaging.

Authors:  Baihua He; Tingyan Zhong; Jian Huang; Yanyan Liu; Qingzhao Zhang; Shuangge Ma
Journal:  Biometrics       Date:  2020-08-29       Impact factor: 1.701

2.  Classification of follicular lymphoma: the effect of computer aid on pathologists grading.

Authors:  Mohammad Faizal Ahmad Fauzi; Michael Pennell; Berkman Sahiner; Weijie Chen; Arwa Shana'ah; Jessica Hemminger; Alejandro Gru; Habibe Kurt; Michael Losos; Amy Joehlin-Price; Christina Kavran; Stephen M Smith; Nicholas Nowacki; Sharmeen Mansor; Gerard Lozanski; Metin N Gurcan
Journal:  BMC Med Inform Decis Mak       Date:  2015-12-30       Impact factor: 2.796

3.  Evaluation of intratumoral heterogeneity by using diffusion kurtosis imaging and stretched exponential diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model.

Authors:  Ran Guo; Shuo-Hui Yang; Fang Lu; Zhi-Hong Han; Xu Yan; Cai-Xia Fu; Meng-Long Zhao; Jiang Lin
Journal:  Quant Imaging Med Surg       Date:  2019-09

4.  Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning.

Authors:  Muhammad Khalid Khan Niazi; Thomas Erol Tavolara; Vidya Arole; Douglas J Hartman; Liron Pantanowitz; Metin N Gurcan
Journal:  PLoS One       Date:  2018-04-12       Impact factor: 3.240

5.  Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology.

Authors:  Muhammad Khalid Khan Niazi; Fazly Salleh Abas; Caglar Senaras; Michael Pennell; Berkman Sahiner; Weijie Chen; John Opfer; Robert Hasserjian; Abner Louissaint; Arwa Shana'ah; Gerard Lozanski; Metin N Gurcan
Journal:  PLoS One       Date:  2018-05-10       Impact factor: 3.240

6.  Bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumor cells in Hodgkin lymphoma.

Authors:  Jennifer Hannig; Hendrik Schäfer; Jörg Ackermann; Marie Hebel; Tim Schäfer; Claudia Döring; Sylvia Hartmann; Martin-Leo Hansmann; Ina Koch
Journal:  PLoS Comput Biol       Date:  2020-01-21       Impact factor: 4.475

7.  A modular cGAN classification framework: Application to colorectal tumor detection.

Authors:  Thomas E Tavolara; M Khalid Khan Niazi; Vidya Arole; Wei Chen; Wendy Frankel; Metin N Gurcan
Journal:  Sci Rep       Date:  2019-12-12       Impact factor: 4.379

  7 in total

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