Literature DB >> 9214818

Morphological feature extraction for the classification of digital images of cancerous tissues.

J P Thiran1, B Macq.   

Abstract

This paper presents a new method for automatic recognition of cancerous tissues from an image of a microscopic section. Based on the shape and the size analysis of the observed cells, this method provides the physician with nonsubjective numerical values for four criteria of malignancy. This automatic approach is based on mathematical morphology, and more specifically on the use of Geodesy. This technique is used first to remove the background noise from the image and then to operate a segmentation of the nuclei of the cells and an analysis of their shape, their size, and their texture. From the values of the extracted criteria, an automatic classification of the image (cancerous or not) is finally operated.

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Mesh:

Year:  1996        PMID: 9214818     DOI: 10.1109/10.536902

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


  14 in total

1.  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

2.  Automated image processing method for the diagnosis and classification of malaria on thin blood smears.

Authors:  Nicholas E Ross; Charles J Pritchard; David M Rubin; Adriano G Dusé
Journal:  Med Biol Eng Comput       Date:  2006-04-08       Impact factor: 2.602

3.  Classifying tissue samples from measurements on cells with within-class tissue sample heterogeneity.

Authors:  Jose-Miguel Yamal; Michele Follen; Martial Guillaud; Dennis D Cox
Journal:  Biostatistics       Date:  2011-06-03       Impact factor: 5.899

4.  Automated Renal Cell Carcinoma Subtype Classification Using Morphological, Textural and Wavelets Based Features.

Authors:  Qaiser Chaudry; Syed Hussain Raza; Andrew N Young; May D Wang
Journal:  J Signal Process Syst       Date:  2008-06-21

5.  Imaging system for visualization and numerical analysis of cancer at stomach and skin tissues.

Authors:  Sadik Kara; Mustafa Okandan; Fulya Sener; Mustafa Yildirim
Journal:  J Med Syst       Date:  2005-04       Impact factor: 4.460

6.  Three-dimensional texture analysis of renal cell carcinoma cell nuclei for computerized automatic grading.

Authors:  T Y Kim; H J Choi; H G Hwang; H K Choi
Journal:  J Med Syst       Date:  2009-04-08       Impact factor: 4.460

7.  Improving Renal Cell Carcinoma Classification by Automatic Region of Interest Selection.

Authors:  Qaiser Chaudry; S Hussain Raza; Yachna Sharma; Andrew N Young; May D Wang
Journal:  Proc IEEE Int Symp Bioinformatics Bioeng       Date:  2008-12-08

8.  Texture analysis of fluorescence microscopic images of colonic tissue sections.

Authors:  V Atlamazoglou; D Yova; N Kavantzas; S Loukas
Journal:  Med Biol Eng Comput       Date:  2001-03       Impact factor: 3.079

9.  Coupled analysis of in vitro and histology tissue samples to quantify structure-function relationship.

Authors:  Evrim Acar; George E Plopper; Bülent Yener
Journal:  PLoS One       Date:  2012-03-30       Impact factor: 3.240

10.  Chagas parasite detection in blood images using AdaBoost.

Authors:  Víctor Uc-Cetina; Carlos Brito-Loeza; Hugo Ruiz-Piña
Journal:  Comput Math Methods Med       Date:  2015-03-11       Impact factor: 2.238

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