Abstract
When cells in the brain grow rapidly and uncontrollably, a tumor in the brain may form. If the disease is not diagnosed early, it can be life-threatening. Despite significant efforts and promising outcomes in the field of brain tumor detection, accurate segmentation and classification of brain tumors remain a challenging task. This significantly depends on the location, shape, and size of the tumor which makes it hard to diagnose. Through this survey, we aim to provide a thorough literature review of brain tumor detection which is done through Magnetic Resonance Imaging (MRI). This survey covers various phases of brain tumor detection, including the anatomy of brain tumors, publicly available datasets, enhancement techniques, segmentation, feature extraction, classification, and deep learning, transfer learning, and quantum machine learning methods for brain tumor analysis.
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
2024 Special Focus—Images and Imaginaries from Artificial Intelligence
KEYWORDS
Brain, Tumor, Detection, MRI
