Generative Adversarial Networks (GANs) have been very successful for synthesizing the
images in a given dataset. The artificially generated images by GANs are very realistic. The …

Abstract Machine learning and deep learning are two subsets of artificial intelligence that
involve teaching computers to learn and make decisions from any sort of data. Most recent …

Colorectal cancer (CRC) is one of the most common causes of cancer and cancer-related
mortality worldwide. Performing colon cancer screening in a timely fashion is the key to early …

Lesion segmentation in ultrasound images is an essential yet challenging step for early
evaluation and diagnosis of cancers. In recent years, many automatic CNN-based methods …

This review examines the recent developments in deep learning (DL) techniques applied to
multimodal fusion image segmentation for liver cancer. Hepatocellular carcinoma is a highly …

Abstract Generative Adversarial Networks (GANs) have shown promising prospects and
achieved significant results in medical image analysis tasks. This article provides a …

Although generative models are still being developed, image reconstruction and generation
tasks have evolved dramatically. Since the most popular generative models still have some …

Colorectal cancer (CRC) is one of the most common causes of cancer and cancer-related
mortality worldwide. Performing colon cancer screening in a timely fashion is the key to early …

Purpose The goal of this work is to explore the best optimizers for deep learning in the
context of medical image segmentation and to provide guidance on how to design …

The liver is the second-largest organ in the human body and is essential for digesting food
and removing toxic substances. Viruses, obesity, alcohol use, and other factors can damage …