Over the past two decades, medical imaging and diagnostic techniques have gained
immense attraction due to the rapid development in computing, internet, data storage and …

Stroke is one of the prominent causes of death in the recent days. The existence of
susceptible plaque in the carotid artery can be used in ascertaining the possibilities of …

Several applications of complex-valued networks have been reported for computer vision
tasks like image processing and classification. However, complex-valued convolutional …

This paper introduces a novel denoising approach making use of a deep convolutional
neural network to preserve image edges. The network is trained by using the edge map …

In this paper, a comprehensive method using symmetric normal inverse Gaussian (NIG)
parameters of the sub-bands of EEG signals calculated in the dual-tree complex wavelet …

Image denoising performs a prominent role in medical image analysis. In many cases, it can
drastically accelerate the diagnostic process by enhancing the perceptual quality of noisy …

Deep neural-network has been widely used in natural image denoising. However, due to the
lack of label of real ultrasound (US) B-mode image for de-speckling, the deep neural …

Speckle reduction is an important pre-processing stage for ultrasound medical image
processing. In this paper, an adaptive fuzzy logic approach for speckle noise reduction in …

Breast ultrasound is an important tool used in the medical treatment and diagnosis of breast
tumor. However, noise defined as speckles are generated inevitably. Although the existence …

This paper investigates the image despeckling issue in the wavelet domain. A maximum a
posteriori (MAP) estimation-based image despeckling approach is proposed by …