A Survey on Human Cancer Categorization Based on Deep Learning - Ibrahim, Ahmad; Mohamed, Hoda K.; Maher, Ali; Zhang, Baochang (Frontiers in Artificial Intelligence, 2022)
The recent few years witnessed the fast growth of deep learning, which involves deep neural networks, and the development of the computing capability of computer devices, following an advance of Graphics Processing Units (GPUS). Deep learning prototypically can successfully categorize histopathological images which involve imaging classification, article discovery, and image description. Various research teams apply deep learning to medical diagnosis, especially of cancer disease. The deep neural networks, mainly the Convolutional Neural Networks (CNN), detect the conventional visual features of a variety of disease diagnoses, e.g., lung, skin, brain, prostate, and breast cancer. CNN has a procedure of perfectly investigating medicinal science images. This paper assesses the main deep learning concepts relevant to the medicinal image investigation and surveys several charities in the field. In addition, it covers the main categories of imaging procedures in medication. The survey comprises the usage of deep learning for object detection and classification. Also, a serious discussion of exposed challenges and trends for upcoming research.