Literature DB >> 26513796

Breast Cancer Ultrasound Images' Sequence Exploration Using BI-RADS Features' Extraction: Towards an Advanced Clinical Aided Tool for Precise Lesion Characterization.

Lamia Sellami, O Ben Sassi, Khalil Chtourou, A Ben Hamida.   

Abstract

This research concerned a clinical need for precise breast cancer lesion characterization imaged by ultrasound sequences. Using therefore BI-RADS features that would be carefully extracted, the purpose of this study could be mainly to prove and to demonstrate the possibility of surveying precisely the changing characteristics of a breast cancer lesion within a considered ultrasound images' sequence. This was in fact a clinical need of a computer aided diagnosis (CAD) system permitting flexible and convivial clinical analysis of multi-slices' ultrasound breast cancer lesion with greater precision. The obtained results of our images' sequence breast cancer ultrasound analysis had shown the lesion form changing depending on the treated slice, as well as the values' differences for the morphological and the textural features. This would allow extracting more information about breast cancer lesions helping then radiologist to converge more rapidly and with a certain reinforced precision to the accurate clinical action to conduct. Such results would be reassembled and rearranged for constituting one computer aided diagnosis (CAD) system that could be provided for clinical explorations permitting on the other hand to avoid possible confusion between benign and malignant masses.

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Year:  2015        PMID: 26513796     DOI: 10.1109/TNB.2015.2486621

Source DB:  PubMed          Journal:  IEEE Trans Nanobioscience        ISSN: 1536-1241            Impact factor:   2.935


  3 in total

1.  Emerging Feature Extraction Techniques for Machine Learning-Based Classification of Carotid Artery Ultrasound Images.

Authors:  S Latha; P Muthu; Samiappan Dhanalakshmi; R Kumar; Khin Wee Lai; Xiang Wu
Journal:  Comput Intell Neurosci       Date:  2022-05-12

2.  Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules.

Authors:  Shu-Yi Lyu; Yan Zhang; Mei-Wu Zhang; Bai-Song Zhang; Li-Bo Gao; Lang-Tao Bai; Jue Wang
Journal:  World J Clin Cases       Date:  2022-01-14       Impact factor: 1.337

3.  Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience.

Authors:  Ji-Hye Choi; Bong Joo Kang; Ji Eun Baek; Hyun Sil Lee; Sung Hun Kim
Journal:  Ultrasonography       Date:  2017-08-14
  3 in total

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