Evidence map›Paper›PMID 35862368›Full record

ArticlePloS one2022

Automated breast lesion localisation in microwave imaging employing simplified pulse coupled neural network.

Maitreyee Dey, Soumya Prakash Rana, Riccardo Loretoni, Michele Duranti, Lorenzo Sani, Alessandro Vispa, Giovanni Raspa, Mohammad Ghavami, Sandra Dudley, Gianluigi Tiberi

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Maitreyee DeySchool of Engineering, London South Bank University, London, United Kingdom.ORCID 0000-0002-6862-7032
Soumya Prakash RanaSchool of Engineering, London South Bank University, London, United Kingdom.
Riccardo LoretoniBreast Unit, Foligno Hospital, Foligno, Italy.
Michele DurantiDepartment of Diagnostic Imaging, Perugia Hospital, Perugia, Italy.
Lorenzo SaniUBT - Umbria Bioengineering Technologies Srl, Perugia, Italy.
Alessandro VispaUBT - Umbria Bioengineering Technologies Srl, Perugia, Italy.
Giovanni RaspaUBT - Umbria Bioengineering Technologies Srl, Perugia, Italy.
Mohammad GhavamiSchool of Engineering, London South Bank University, London, United Kingdom.
Sandra DudleySchool of Engineering, London South Bank University, London, United Kingdom.
Gianluigi TiberiSchool of Engineering, London South Bank University, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Breast NeoplasmsMicrowave ImagingAlgorithmsBreastDiagnostic ImagingFemaleHumansMicrowavesNeural Networks, Computer

Identifiers

PMID35862368
PMCPMC9302781

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.