{rfName}

Indexed in

License and use

Citations

1

Altmetrics

Analysis of institutional authors

García MaAuthor

Share

February 27, 2023
Publications
>
Proceedings Paper
No

Breast Ultrasound CAD System Based on Efficient Tumour Segmentation Network and Transfer-Learned Features

Publicated to:2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies, IMPACT 2022. 1-5 - 2022-01-01 (), DOI: 10.1109/IMPACT55510.2022.10029203

Authors: Zaidkilani, Nadeem; Abdel-Nasser, Mohamed; Angel Garcia, Miguel; Puig, Domenec

Affiliations

Aswan Univ, Aswan, Egypt - Author
Aswan University , Universitat Rovira i Virgili - Author
Univ Autonoma Madrid, Dept Elect & Commun Technol, Madrid, Spain - Author
Univ Rovira & Virgili, Dept Comp Engn & Math, Tarragona, Catalonia, Spain - Author
Univ Rovira & Virgili, Tarragona, Spain - Author
Universidad Autónoma de Madrid - Author
Universitat Rovira i Virgili - Author
See more

Abstract

Breast cancer is the second most common type of cancer worldwide after lung cancer and the leading cause of cancer death among women. Over the past few decades, computer-assisted diagnostic (CAD) systems have been implemented to assist physicians. This paper introduces a CAD system to segment tumours in breast ultrasound (BUS) images and classifies them as benign or malignant. The CAD system has two stages: segmentation and classification. In the segmentation stage, we have developed an encoder-decoder network based on different backbones with various loss functions to segment the tumours. We have fine-tuned the MobileNetv2 network in the classification stage to classify the segmented tumours as benign or malignant. Our experiments demonstrate that WideResNet with BCE and Dice loss function outperforms and yields the best tumour segmentation results with a Dice score of 77.32%. The CAD system achieves a classification accuracy of 86%.

Keywords

cad systemdeep learningimage segmentationloss functionsBreast cancerCad systemDeep learningImage segmentationLoss functions

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 1.07, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Aug 2025)

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-02:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 8 (PlumX).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Egypt.