Research in the medical imaging field using deep learning approaches has become
progressively contingent. Scientific findings reveal that supervised deep learning methods' …

Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …

Deep learning methods utilizing Convolutional Neural Networks (CNNs) have led to
dramatic advances in automated understanding of medical images. However, in many …

Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Aims A large number of clinical trials have proved that if breast cancer is diagnosed at an
early stage, it could give patients more treatment options and improve the treatment effect …

The solid rocket engine is the main power unit of various missile weapons today, and it also
has a wide range of applications in the aerospace field. However, in the process of welding …

In this paper, a new classification approach of breast cancer based on Fully Convolutional
Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful …

In medical image analysis, multi-view modeling is crucial for pathology detection when the
target lesion is presented in different views, eg mass lesions in breasts. Currently …

Detection of breast mass plays a very important role in making the diagnosis of breast
cancer. For faster detection of breast cancer caused by breast mass, we developed a novel …