ArticlePloS one2022
Automated breast lesion localisation in microwave imaging employing simplified pulse coupled neural network.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Microwave Breast Sensing via Deep Learning for Tumor Spatial Localization by Probability Maps.Bioengineering (Basel, Switzerland) · 2023Article
- Review and Analysis of Tumour Detection and Image Quality Analysis in Experimental Breast Microwave Sensing.Sensors (Basel, Switzerland) · 2023Review
- Radar-Based Microwave Breast Imaging Using Neurocomputational Models.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
10 authors.
Funding
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Abstract
MammoWave is a microwave imaging device for breast lesion detection, employing two antennas which rotate azimuthally (horizontally) around the breast. The antennas operate in the 1-9 GHz band and are set in free space, i.e., pivotally, no matching liquid is required. Microwave images, subsequently obtained through the application of Huygens Principle, are intensity maps, representing the homogeneity of the dielectric properties of the breast tissues under test. In this paper, MammoWave is used to realise tissues dielectric differences and localise lesions by segmenting microwave images adaptively employing pulse coupled neural network (PCNN). Subsequently, a non-parametric thresholding technique is modelled to differentiate between breasts having no radiological finding (NF) or benign (BF) and breasts with malignant finding (MF). Resultant findings verify that automated breast lesion localization with microwave imaging matches the gold standard achieving 81.82% sensitivity in MF detection. The proposed method is tested on microwave images acquired from a feasibility study performed in Foligno Hospital, Italy. This study is based on 61 breasts from 35 patients; performance may vary with larger number of datasets and will be subsequently investigated.
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