Over the past two decades, computer-aided detection and diagnosis have emerged as a
field of research. The primary goal is to enhance the diagnostic and treatment procedures for …

Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US
image segmentation is crucial in image analysis. Recently, deep learning-based methods …

Although deep learning techniques have made significant advances in the field of images,
existing methods still face challenges in processing complex, noisy images. In view of the …

Our study develops a computer-aided diagnosis (CAD) system for breast ultrasound by
presenting an innovative frequency domain technique for extracting mass irregularity …

Purpose: Several applications require the super-resolution of noisy images and the
preservation of geometrical and texture features. State-of-the-art super-resolution methods …

Ultrasound imaging is a fast, widespread, and essential diagnostic technique for examining
the body's internal anatomy to find abnormal tissues or diseases. However, speckle noise in …

Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics,
particularly in the field of medical imaging. In this study, we investigated the application of …

This paper proposes a novel deep-learning framework for super-resolution ultrasound
images and videos in terms of spatial resolution and line reconstruction. To this end, we up …

The versatile nature of ultrasound imaging finds applications in various fields. A point
contact excitation and detection method is generally used for visualizing the acoustic waves …

Accurate diagnosis of atherosclerotic coronary artery stenosis largely depends on
intravascular ultrasound (IVUS) image quality. Coherent sources present during IVUS …