Brain tumor segmentation consists of separating the different tumor tissues (solid or active
tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM) …

Abstract Purpose Structural Magnetic Resonance Imaging (MRI) of the brain is an effective
way to study its internal structure. Identifying and classifying brain malignancies is a difficult …

Background In recent years, magnetic resonance imaging (MRI) has become important in
brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by …

Brain tumor segmentation is the process of separating the tumor from normal brain tissues;
in clinical routine, it provides useful information for diagnosis and treatment planning …

Delineation of active tumor region and perifocal edema from Magnetic Resonance (MR)
images of Glioblastoma Multiforme (GBM) is difficult as GBM is highly infiltrating and non …

Medical image quality is crucial to obtaining reliable diagnostics. Most quality controls rely
on routine tests using phantoms, which do not reflect closely the reality of images obtained …

Abstract Magnetic Resonance Image segmentation is a fundamental task in a wide variety of
computed-based medical applications that support therapy, diagnostic and medical …

This study presents a comprehensive framework that integrates a deep learning model with
advanced image preprocessing techniques to improve the multilabel classification of five …

One of the important problems in medical diagnosis is the segmentation and detection of
brain tumor in MR images. The accurate estimation of brain tumor size is important for …

In this paper, computer-based methods for defining tumor region in the brain using MRI
images is presented. Brain tumor detection and segmentation is one of the most challenging …