Assessment of despeckle filtering algorithms for segmentation of breast tumours from ultrasound images

• Autorzy: Kriti , Virmani Jitendra , Agarwal Ravinder

Identyfikatory

DOI

10.1016/j.bbe.2018.10.002

• Języki publikacji: EN

Abstrakty

EN

In the present work, the performance assessment of despeckle filtering algorithms has been carried out for (α) noise reduction in breast ultrasound images and (b) segmentation of benign and malignant tumours from breast ultrasound images. The despeckle filtering algorithms are broadly classified into eight categories namely local statistics based filters, fuzzy filters, Fourier filters, multiscale filters, non-linear iterative filters, total variation filters, non-local mean filters and hybrid filters. Total 100 breast ultrasound images (40 benign and 60 malignant) are processed using 42 despeckle filtering algorithms. A despeckling filter is considered to be appropriate if it preserves edges and features/structures of the image. Edge preservation capability of a despeckling filter is measured by beta metric (β) and feature/structure preservation capability is quantified using image quality index (IQI). It is observed that out of 42 filters, six filters namely Lee Sigma, FI, FB, HFB, BayesShrink and DPAD yield more clinically acceptable images in terms of edge and feature/structure preservation. The qualitative assessment of these images has been done on the basis of grades provided by the experienced participating radiologist. The pre-processed images are then fed to a segmentation module for segmenting the benign or malignant tumours from ultrasound images. The performance assessment of segmentation algorithm has been done quantitatively using the Jaccard index. The results of both quantitative and qualitative assessment by the radiologist indicate that the DPAD despeckle filtering algorithm yields more clinically acceptable images and results in better segmentation of benign and malignant tumours from breast ultrasound images.

Słowa kluczowe

EN

breast ultrasound; speckle noise; despeckling filter; image quality metrics; structure preservation; edge preservation; image segmentation

PL

ultrasonografia piersi; szum plamkowy; jakość obrazu; segmentacja obrazu

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 1
• Strony: 100--121
• Opis fizyczny: Bibliogr. 99 poz., rys., tab.

Twórcy

autor

Kriti

• Thapar Institute of Engineering and Technology, Patiala, Punjab, India

autor

Virmani Jitendra

• CSIR-Central Scientific Instruments Organisation (CSIR-CSIO), Chandigarh 160030, India

autor

Agarwal Ravinder

• Thapar Institute of Engineering and Technology, Patiala, Punjab, India

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).