Fig 1.
Flow chart of the proposed work; the clinical data collection procedure using MammoWave system and the proposed lesion localisation using the MammoWave created images.
Fig 2.
The apparatus measurement procedure; the antennas inside the container (covered to absorb microwaves) are fitted at the constant height, in free space and can rotate across the azimuth for collecting the microwave signals from diverse angular locations.
For every transmitting and receiving spot, the complex S21 is gathered from 1 to 9 GHz, along with 5 MHz sampling.
Table 1.
Summary of patient’s information used in this study.
Table 2.
Breast index, patient index, age, examined breast (L /R), breast category (NF, BF, and MF) from the radiologist (gold standard information), lesion position, and dimensions are all listed here.
Fig 3.
Microwave images of a single breast for different conductivity level generated via the MammoWave signal.
(a) represent the image created for σ1 conductivity level, (b) represent the image created for σ2 conductivity, (c) represent the image created for σ3 conductivity, and (d) represent the image created for σ4 conductivity. Images given here are two-dimensional (2D) image in the azimuthal, i.e. coronal, plane. The x-axis and y-axis are given in meter and the colour bar represents the intensity in arbitrary units.
Fig 4.
The flow graph of the adaptive image segmentation using PCNN [31].
Fig 5.
Six PCNN iterations for one MF breast images for different conductivity (a) input image formed using σ1, (b) input image formed using σ2, (c) input image formed using σ3, and (d) input image formed using σ4.
The radiologist study review “MF” for this heterogeneously dense breast has been obtained with the support of mammography images given in the bottom row, giving as output the presence of a cluster of microcalcifications, plus follow-up.
Fig 6.
The results obtained over PCNN iterations for one of the NF+BF breast images with different conductivity: (a) Input image formed using σ1, (b) input image formed using σ2, (c) input image formed using σ3, and (d) input image formed using σ4.
The radiologist study review “NF” for this scattered area of fibroglandular density breast has been obtained with the support of mammography images given in the bottom row.
Fig 7.
Box whisker plot for the examined breast images with the thresholding.
61 breasts’ data have been filtered through Gaussian kernel to decide the threshold value, where the x-axis represent the number of breasts’ index and y-axis represent the peak intensity (arbitrary units) of each breast.
Fig 8.
Confusion matrix obtained from the non-parametric thresholding method.