Literature DB >> 20033596

Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience.

Yuji Ikedo1, Takako Morita, Daisuke Fukuoka, Takeshi Hara, Gobert Lee, Hiroshi Fujita, Etsuo Takada, Tokiko Endo.   

Abstract

PURPOSE: A computerized classification scheme to recognize breast parenchymal patterns in whole breast ultrasound (US) images was developed. A preliminary evaluation of the system performance was performed.
METHODS: Breast parenchymal patterns were classified into three categories: mottled pattern (MP), intermediate pattern (IP), and atrophic pattern (AP). Each classification was defined as proposed by an experienced physician. A total of 281 image features were extracted from a volume of interest which was automatically segmented. Canonical discriminant analysis with stepwise feature selection was employed for the classification of the parenchymal patterns.
RESULTS: The classification scheme accuracy was computed to be 83.3% (10/12 cases) in MP cases, 91.7% (22/24 cases) in IP cases, 92.9% (13/14 cases) in AP cases, and 90.0% (45/50 cases) in all the cases.
CONCLUSIONS: The feasibility of an automated ultrasonography classifier for parenchymal patterns was demonstrated with promising results in whole breast US images.

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Year:  2009        PMID: 20033596     DOI: 10.1007/s11548-009-0295-0

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  20 in total

1.  Diagnosis of breast cancer: contribution of US as an adjunct to mammography.

Authors:  H M Zonderland; E G Coerkamp; J Hermans; M J van de Vijver; A E van Voorthuisen
Journal:  Radiology       Date:  1999-11       Impact factor: 11.105

2.  Development of ultrasound tomography for breast imaging: technical assessment.

Authors:  Nebojsa Duric; Peter Littrup; Alex Babkin; David Chambers; Stephen Azevedo; Roman Pevzner; Mikhail Tokarev; Earle Holsapple; Olsi Rama; Robert Duncan
Journal:  Med Phys       Date:  2005-05       Impact factor: 4.071

3.  Breast density analysis in 3-D whole breast ultrasound images.

Authors:  Ruey-Feng Chang; Kuang-Che Chang-Chien; Etsuo Takada; Jasjit S Suri; Woo Kyung Moon; Jeffery H K Wu; Nariya Cho; Yi-Fa Wang; Dar-Ren Chen
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

4.  Development of a fully automatic scheme for detection of masses in whole breast ultrasound images.

Authors:  Yuji Ikedo; Daisuke Fukuoka; Takeshi Hara; Hiroshi Fujita; Etsuo Takada; Tokiko Endo; Takako Morita
Journal:  Med Phys       Date:  2007-11       Impact factor: 4.071

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Authors:  K Kerlikowske; D Grady; S M Rubin; C Sandrock; V L Ernster
Journal:  JAMA       Date:  1995-01-11       Impact factor: 56.272

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Authors:  N F Boyd; B O'Sullivan; E Fishell; I Simor; G Cooke
Journal:  J Natl Cancer Inst       Date:  1984-06       Impact factor: 13.506

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Journal:  AJR Am J Roentgenol       Date:  1976-06       Impact factor: 3.959

8.  Effects of age, breast density, ethnicity, and estrogen replacement therapy on screening mammographic sensitivity and cancer stage at diagnosis: review of 183,134 screening mammograms in Albuquerque, New Mexico.

Authors:  R D Rosenberg; W C Hunt; M R Williamson; F D Gilliland; P W Wiest; C A Kelsey; C R Key; M N Linver
Journal:  Radiology       Date:  1998-11       Impact factor: 11.105

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Authors:  J Brisson; A S Morrison; N Khalid
Journal:  J Natl Cancer Inst       Date:  1988-12-07       Impact factor: 13.506

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Authors:  S W Fletcher; W Black; R Harris; B K Rimer; S Shapiro
Journal:  J Natl Cancer Inst       Date:  1993-10-20       Impact factor: 13.506

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  1 in total

Review 1.  Breast ultrasound image segmentation: a survey.

Authors:  Qinghua Huang; Yaozhong Luo; Qiangzhi Zhang
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-01-09       Impact factor: 2.924

  1 in total

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