Among the currently proposed brain segmentation methods, brain tumor segmentation
methods based on traditional image processing and machine learning are not ideal enough …

The accuracy of brain tumor diagnosis based on medical images is greatly affected by the
segmentation process. The segmentation determines the tumor shape, location, size, and …

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 …

Brain tumors are difficult to treat and cause substantial fatalities worldwide. Medical
professionals visually analyze the images and mark out the tumor regions to identify brain …

Automatic and precise segmentation and classification of tumor area in medical images is
still a challenging task in medical research. Most of the conventional neural network based …

In this paper, premature head lump recognition along with analysis is dangerous to clinic.
Therefore, segmentation of paying attention to growth neighborhood desires near subsists …

A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …

Detecting and classifying a brain tumor is a challenge that consumes a radiologist's time and
effort while requiring professional expertise. To resolve this, deep learning techniques can …

Identification of brain tumors attends a critical role in evaluating tumors and making
decisions about care as per their grades. Several imaging methods are employed to identify …

In medical field, brain tumor detection is an arduous task. Early segmentation of brain tumor
is a crucial challenge to save the patient's life by deep learning (DL). For efficient and …