A Wavelet - Fuzzy Combination Based Approach for Efficient Cancer Characterization in Breast Ultrasound Images

Badawy, Samir Mohamed; Zidan, Hassan E.; Mohamed, Azza H.; Hefnawy, Alaa A.; GadAllah, Mohammed Tarek; El‐Banby, Ghada M.

doi:10.1109/iceem52022.2021.9480631

Cited by 2 publications

(3 citation statements)

References 22 publications

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“…Breast cancer is the second common cancer worldwide after lung cancer, the fifth common cause of cancer death [97,98]. X-ray-based Mammography [97], Breast ultrasound (BUS) imaging [99][100][101], and Magnetic resonance imaging (MRI) [102,103], are the three most famous imaging techniques utilized for breast cancer screening. X-ray-based screening mammography, beginning in the 1980s, helps in the early detection of breast cancer [97].…”

Section: A Breast Cancermentioning

confidence: 99%

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Photoacoustic Imaging in Medicine – A Review

GadAllah

Mohamed

Hefnawy

et al. 2022

MEJ. Mansoura Engineering Journal

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This photoacoustic imaging (PAI) in medicine paper started with an introduction to PAI and the famous photoacoustic techniques including photoacoustic tomography (PAT), multispectral optoacoustic tomography (MSOT), photoacoustic microscopy (PAM), raster-scan optoacoustic mesoscopy (RSOM), and photoacoustic elastography (PAE). A modest review about noncontact laser ultrasound (LUS), having the advantage of operator-independent image quality, has been also demonstrated. A concise review of most of PAI's medical applications is demonstrated including cancer screening (for breast, thyroid, ovarian, prostate, lung, and skin), tissue oxygenation measurements, brain imaging, imaging-guided surgery (IGS), and the guidance of high intensity focused ultrasound (HIFU). Some safety considerations contributed with medical ultrasound and lasers have been then presented. In conclusion, more scientific and clinical development in the field of PAI is expected, and an increase in approved devices that utilize PAI's techniques in medical applications is also expected to serve wide sectors of medicine, whether diagnostic or therapeutic.

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Section: A Breast Cancermentioning

confidence: 99%

“…But it uses ionizing radiation, painful breast compression, and has poor performance in radiodense breasts. BUS imaging can be utilized as mammography's adjunct [100,101]. However, X-ray and BUS imaging are both suffer from having non-optimal sensitivity and specificity [104].…”

Section: A Breast Cancermentioning

confidence: 99%

Photoacoustic Imaging in Medicine – A Review

GadAllah

Mohamed

Hefnawy

et al. 2022

MEJ. Mansoura Engineering Journal

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“…It uses a distinct value of thresholds at each level of the wavelet decomposition. It helps to select a threshold value that is efficient for data as well as minimizes risk (12) . https://www.indjst.org/…”

Section: Thresholdingmentioning

confidence: 99%

A Hybrid Image Denoising Method Based on Discrete Wavelet Transformation with Pre-Gaussian Filtering

Gupta¹

2022

IJST

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Background/Objectives: At the time of acquisition and transmission noise is embedded with the images. It introduces new but unwanted information (noise) in images. The elimination of noise to analyze such data is an essential step in preprocessing. The purpose of this study is to propose a novel image denoising approach to recover original images at high noise densities without introducing unwanted artifacts. Methods: A new hybrid method based on approximation subband thresholding with pre-Gaussian filtering is presented in this study. Google Colab as a platform and python as a programming language is used for the implementation of the proposed technique. To evaluate the performance Peak Signal to Noise Ratio (PSNR) is chosen. The standard jpeg images (Cameraman, Lena, Astronaut, Cat) have been taken as an input and random noise with different noise ratios (σ =0.05,0.20,0.30,0.50) is applied to get the noisy images for the experiment. In random noise scenarios, the proposed method experimented on different grayscale standard images, and performance is compared with different existing methods. Findings: The standard images with different noise ratios are denoised by the proposed method, and the quality of images is calculated in terms of PSNR. The results obtained from the proposed method on different standard images improve PSNR (PSNR= 25.80dB, σ =0.50) at high noise levels significantly. Novelty: Gaussian filter improve the quality of images. However, when wavelet decomposition is blended with filtered image and thresholding is applied on approximation band improved the quality of images. Hence, the proposed method has a wide area of application to improve image quality in the field of character recognition, agriculture, medical science, and remote sensing.

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A Wavelet - Fuzzy Combination Based Approach for Efficient Cancer Characterization in Breast Ultrasound Images

Cited by 2 publications

References 22 publications

Photoacoustic Imaging in Medicine – A Review

Photoacoustic Imaging in Medicine – A Review

A Hybrid Image Denoising Method Based on Discrete Wavelet Transformation with Pre-Gaussian Filtering

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