The approach of using more than one processor to compute in order to overcome the
complexity of different medical imaging methods that make up an overall job is known as …

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with
applications in disease diagnostics, intervention, and treatment planning. Accurate MRI …

A brain tumor is an unnatural expansion of brain cells that can't be stopped, making it one of
the deadliest diseases of the nervous system. The brain tumor segmentation for its earlier …

This study addresses the formidable challenges encountered in automated brain tumor
segmentation, including the complexities of irregular shapes, ambiguous boundaries, and …

Brain tumors cause death to a lot of people globally. Brain tumor disease is seen as one of
the most lethal diseases since its mortality rate is high. Nevertheless, this rate can be …

Early detection and precise characterization of brain tumors play a crucial role in improving
patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic …

Background: Accurately and automatically segmenting the hippocampus into multiple
subfields on MRI images is crucial for the diagnosis and intervention of various neurological …

Autonomous vehicles and robotic wheelchairs based real world applications need the
automated recognition of roads, route holes, and other irregularities. Traditional techniques …