Literature DB >> 11370371

Classification of ultrasonic B-mode images of breast masses using Nakagami distribution.

P M Shankar1, V A Dumane, J M Reid, V Genis, F Forsberg, C W Piccoli, B B Goldberg.   

Abstract

The Nakagami distribution was proposed recently for modeling the echo from tissue. In vivo breast data collected from patients with lesions were studied using this Nakagami model. Chi-square tests showed that the Nakagami distribution is a better fit to the envelope than the Rayleigh distribution. Two parameters, m (effective number) and alpha (effective cross section), associated with the Nakagami distribution were used for the classification of breast masses. Data from 52 patients with breast masses/lesions were used in the studies. Receiver operating characteristics (ROC) were calculated for the classification methods based on these two parameters. The results indicate that these parameters of the Nakagami distribution may be useful in classification of the breast abnormalities. The Nakagami distribution may be a reasonable means to characterize the backscattered echo from breast tissues toward a goal of an automated scheme for separating benign and malignant breast masses.

Entities:  

Mesh:

Year:  2001        PMID: 11370371     DOI: 10.1109/58.911740

Source DB:  PubMed          Journal:  IEEE Trans Ultrason Ferroelectr Freq Control        ISSN: 0885-3010            Impact factor:   2.725


  16 in total

1.  Role of ultrasound in the detection of apoptosis.

Authors:  Gregory J Czarnota
Journal:  Eur J Nucl Med Mol Imaging       Date:  2005-05       Impact factor: 9.236

2.  Ultrasonic Nakagami-parameter characterization of parotid-gland injury following head-and-neck radiotherapy: a feasibility study of late toxicity.

Authors:  Xiaofeng Yang; Srini Tridandapani; Jonathan J Beitler; David S Yu; Ning Wu; Yuefeng Wang; Deborah W Bruner; Walter J Curran; Tian Liu
Journal:  Med Phys       Date:  2014-02       Impact factor: 4.071

3.  Modeling the envelope statistics of three-dimensional high-frequency ultrasound echo signals from dissected human lymph nodes.

Authors:  Thanh Minh Bui; Alain Coron; Jonathan Mamou; Emi Saegusa-Beecroft; Tadashi Yamaguchi; Eugene Yanagihara; Junji Machi; S Lori Bridal; Ernest J Feleppa
Journal:  Jpn J Appl Phys (2008)       Date:  2014       Impact factor: 1.480

4.  A Quantitative Ultrasound-Based Multi-Parameter Classifier for Breast Masses.

Authors:  Haidy G Nasief; Ivan M Rosado-Mendez; James A Zagzebski; Timothy J Hall
Journal:  Ultrasound Med Biol       Date:  2019-04-26       Impact factor: 2.998

5.  Three-dimensional high-frequency backscatter and envelope quantification of cancerous human lymph nodes.

Authors:  Jonathan Mamou; Alain Coron; Michael L Oelze; Emi Saegusa-Beecroft; Masaki Hata; Paul Lee; Junji Machi; Eugene Yanagihara; Pascal Laugier; Ernest J Feleppa
Journal:  Ultrasound Med Biol       Date:  2011-03       Impact factor: 2.998

6.  Noninvasive evaluation of vaginal fibrosis following radiotherapy for gynecologic malignancies: a feasibility study with ultrasound B-mode and Nakagami parameter imaging.

Authors:  Xiaofeng Yang; Peter Rossi; Deborah Watkins Bruner; Srini Tridandapani; Joseph Shelton; Tian Liu
Journal:  Med Phys       Date:  2013-02       Impact factor: 4.071

Review 7.  Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound.

Authors:  Michael L Oelze; Jonathan Mamou
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2016-01-08       Impact factor: 2.725

8.  Evaluation of thrombolysis by using ultrasonic imaging: an in vitro study.

Authors:  Jui Fang; Po-Hsiang Tsui
Journal:  Sci Rep       Date:  2015-07-01       Impact factor: 4.379

9.  Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization.

Authors:  Omar S Al-Kadi; Daniel Y F Chung; Robert C Carlisle; Constantin C Coussios; J Alison Noble
Journal:  Med Image Anal       Date:  2014-12-27       Impact factor: 8.545

10.  A nonlinear approach to identify pathological change of thyroid nodules based on statistical analysis of ultrasound RF signals.

Authors:  Huan Xu; Chunrui Liu; Ping Yang; Juan Tu; Bin Yang; Dong Zhang
Journal:  Sci Rep       Date:  2017-12-05       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.