Next-Gen brain tumor classification: pioneering with deep learning and fine-tuned conditional generative adversarial networks.

ABSTRACT: Brain tumor has become one of the fatal causes of death worldwide in recent years, affecting many individuals annually and resulting in loss of lives. Brain tumors are characterized by the abnormal or irregular growth of brain tissues that can spread to nearby tissues and eventually throughout the brain. Although several traditional machine learning and deep learning techniques have been developed for detecting and classifying brain tumors, they do not always provide an accurate and timely diagnosis. This study proposes a conditional generative adversarial network (CGAN) that leverages the fine-tuning of a convolutional neural network (CNN) to achieve more precise detection of brain tumors. The CGAN comprises two parts, a generator and a discriminator, whose outputs are used as inputs for

SUBMITTER: Asiri AA 

PROVIDER: S-EPMC10702976 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature