Design and Performance Test of an Implementable Rectenna Encapsulated in a Human Tissue Bio-Case Model

A brain tumor refers to abnormal growth of cells in the brain.Possible reasons: Although the exact causes are often unknown, certain things can increase or influence someone's chances of getting a brain tumor such as exposure to radiation and a family history of brain cancer; All classes, throughout the world in all age groups suffered an escalation in brain neoplasia incidence over the past years.An estimated 78,980 new cases of primary malignant and nonmalignant brain tumors were diagnosed in the US in 2018.Even though there has been a wealth Abstract: Brain tumor segmentation is one of the most challenging jobs in medical image analysis.The goal of this process is to accurately delineate the regions affected by brain tumors.In recent years, deep learning techniques have produced encouraging outcomes in various computer vision challenges, like image classification, object detection, and semantic segmentation.These techniques have also been effectively applied to brain tumor segmentation, yielding encouraging outcomes.This review provides a comprehensive analysis of the latest deep learning-based approaches for brain tumor segmentation, highlighting the significant advancements made with cutting-edge technologies.Initially, a brief outine of brain tumors and the methods used for their segmentation is presented.Next, cutting-edge algorithms are covered, with an emphasis on the most current evolutions in DL techniques.Ultimately, a review of the situation is given, along with an outlook on how MRI-based brain tumor segmentation techniques will progress going forward addressing in great detail technological topics including multi-modality processes, segmentation under imbalanced situations, and network architecture design.We also offer enlightening talks about potential future paths for development.