Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …

Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …

Medical image processing is a rapidly growing and concentrating topic today. Medical
image analysis techniques are used to diagnose and cure illnesses. One such fundamental …

CNN is inspired from Primary Visual (V1) neurons. It is a typical deep learning technique
and can help teach machine how to see and identify objects. In the most recent decade …

Brain image segmentation is one of the most time-consuming and challenging procedures in
a clinical environment. Recently, a drastic increase in the number of brain disorders has …

This study proposes a lightweight automatic 3D algorithm with an attention mechanism for
the segmentation of brain-tumor images to address the challenges. Accurate segmentation …

Purpose: Segmentation is one of the critical steps in analyzing medical images since it
provides meaningful information for the diagnosis, monitoring, and treatment of brain tumors …

Abstract The Internet of Medical Things (IoMT) combines the Internet of Things (IoT) with
medical equipment to provide better patient comfort, cost-effective medical solutions, faster …

Next-generation wireless networks have to be robust and self-sustained. Internet of things
(IoT) is reshaping the technological adaptation in the daily life of human beings. IoT …

The Internet of Medical Things (IoMT) has revolutionized Ambient Assisted Living (AAL) by
interconnecting smart medical devices. These devices generate a large amount of data …