Literature DB >> 31947359

Morphological characterization of breast tumors using conventional B-mode ultrasound images.

Ahmed R M El-Azizy, Mohamed Salaheldien, Muhammad A Rushdi, Hanan Gewefel, Ahmed M Mahmoud.   

Abstract

This work aims to develop and test a vendor-independent computer-aided diagnosis (CAD) system that uses conventional B-mode ultrasound images to distinguish between benign and malignant breast tumors. Three morphological features were extracted from 323 breast tumor lesions including the perimeter, regularity variance, and circularity range ratio. Lesions were segmented using the active contour method via semi- andfully-automated algorithms. Then, the support vector machine classifier was used to identify breast lesions. Results of the CAD system exhibited accuracies of 95.98% and 95.67%using the semi- and fully-automated segmentation, respectively. Based on the preliminary results, this CAD system with such unique combination of geometrical features shall improve the diagnostic decisions and may reduce the need of unnecessary needle biopsies.

Entities:  

Year:  2019        PMID: 31947359     DOI: 10.1109/EMBC.2019.8857438

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  An Optimized Framework for Breast Cancer Classification Using Machine Learning.

Authors:  Epimack Michael; He Ma; Hong Li; Shouliang Qi
Journal:  Biomed Res Int       Date:  2022-02-18       Impact factor: 3.411

2.  Development and External Validation of a Simple-To-Use Dynamic Nomogram for Predicting Breast Malignancy Based on Ultrasound Morphometric Features: A Retrospective Multicenter Study.

Authors:  Qingling Zhang; Qinglu Zhang; Taixia Liu; Tingting Bao; Qingqing Li; You Yang
Journal:  Front Oncol       Date:  2022-04-07       Impact factor: 5.738

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.