Colorectal cancer has a great incidence rate worldwide, but its early detection significantly
increases the survival rate. Colonoscopy is the gold standard procedure for diagnosis and …

SARS-CoV-2 is a novel virus that has been affecting the global population by spreading
rapidly and causing severe complications, which require prompt and elaborate emergency …

Medical imaging refers to several different technologies that are used to view the human
body to diagnose, monitor, or treat medical conditions. It requires significant expertise to …

Featured Application This dataset can be used for supervised training of models for
colorectal polyp detection, localisation, segmentation and classification. Abstract Colorectal …

Artificial intelligence (AI) in GI endoscopy holds tremendous promise to augment clinical
performance, establish better treatment plans, and improve patient outcomes. Although …

Analysis of colonoscopy images plays a significant role in early detection of colorectal
cancer. Automated tissue segmentation can be useful for two of the most relevant clinical …

Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …

Purpose Data augmentation is a common technique to overcome the lack of large annotated
databases, a usual situation when applying deep learning to medical imaging problems …

With the advancement of computer vision, artificial intelligence, and remote sensing
technologies, deep learning algorithms are increasingly used in terrestrial, airborne, and …

With constant research in the last decade, Object Detection has become one of the rapidly
evolving sub-fields of Deep Learning. As a result, the complexity and applications of Object …