Literature DB >> 11442099

Comparative analysis of texture characteristics of malignant and benign tumors in breast ultrasonograms.

K G Kim1, J H Kim, B G Min.   

Abstract

We evaluated various texture features and region of interest (ROI) types of breast ultrasonograms in order to determine the best-performing combinations for differentiating between benign and malignant solid breast nodules. A total of 21 breast ultrasonograms (12 benign, nine malignant) containing solid breast nodules were evaluated. Eight ROI types were defined around the nodules. The texture feature of each ROI was measured and the ratios of texture features were calculated for each pair of ROIs. This procedure was repeated for five different feature types, thus yielding texture feature ratios for 140 different combinations of ROIs and texture features. We evaluated the performance of the texture feature ratio in differentiating between benign and malignant nodules using t test analysis. Evaluating the top ranked texture and ROI combinations, we found edge density and mutual information were the best two texture features, and that the ROI types of outside lesion and lesion margin had good performance.

Entities:  

Mesh:

Year:  2001        PMID: 11442099      PMCID: PMC3452665          DOI: 10.1007/BF03190341

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  5 in total

1.  Computerized analysis of lesions in US images of the breast.

Authors:  M L Giger; H Al-Hallaq; Z Huo; C Moran; D E Wolverton; C W Chan; W Zhong
Journal:  Acad Radiol       Date:  1999-11       Impact factor: 3.173

2.  Improvement in specificity of ultrasonography for diagnosis of breast tumors by means of artificial intelligence.

Authors:  V Goldberg; A Manduca; D L Ewert; J J Gisvold; J F Greenleaf
Journal:  Med Phys       Date:  1992 Nov-Dec       Impact factor: 4.071

3.  Multimodality image registration by maximization of mutual information.

Authors:  F Maes; A Collignon; D Vandermeulen; G Marchal; P Suetens
Journal:  IEEE Trans Med Imaging       Date:  1997-04       Impact factor: 10.048

4.  Breast cancer diagnosis using self-organizing map for sonography.

Authors:  D Chen; R F Chang; Y L Huang
Journal:  Ultrasound Med Biol       Date:  2000-03       Impact factor: 2.998

5.  Improving the distinction between benign and malignant breast lesions: the value of sonographic texture analysis.

Authors:  B S Garra; B H Krasner; S C Horii; S Ascher; S K Mun; R K Zeman
Journal:  Ultrason Imaging       Date:  1993-10       Impact factor: 1.578

  5 in total
  1 in total

Review 1.  Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review.

Authors:  Lejla Alic; Wiro J Niessen; Jifke F Veenland
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

  1 in total

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