Controlled despeckling (structure/edges/feature preservation with smoothing the
homogeneous areas) is a desired pre-processing step for the design of computer-aided …

Convolutional neural networks (CNNs) have been extensively utilized in medical image
processing to automatically extract meaningful features and classify various medical …

Breast cancer is the type of cancer that affects women the most frequently in the world.
Additionally, it is the highest cause of death for women. For the detection and treatment of …

This study aims to enable effective breast ultrasound image classification by combining
deep features with conventional handcrafted features to classify the tumors. In particular, the …

Deep learning and image processing are used to classify and segment breast tumor images,
specifically in ultrasound (US) modalities, to support clinical decisions and improve …

Breast cancer is one of the deadliest cancer types affecting women worldwide. As with all
types of cancer, early detection of breast cancer is of vital importance. Early diagnosis plays …

Purpose Breast cancer is a prominent cancer type with high mortality. Early detection of
breast cancer could serve to improve clinical outcomes. Ultrasonography is a digital imaging …

Breast tumor is one of the major cause of death among women all over the world.
Ultrasound imaging-based breast abnormality detection and classification play a vital role to …

Female accounts for approximately 50% of the total population worldwide and many of them
had breast cancer. Computer‐aided diagnosis frameworks could reduce the number of …

This paper examines and assesses state-of-the-art proposed machine and deep learning
techniques for breast cancer identification and classification based on breast screening …