An efficient brain segmentation technique of magnetic resonance image (MRI) is proposed for the sake of atrophy detection. Early detection of brain atrophy indicates many neurodiseases. The paper also proposes a new simple assessment for brain atrophy as an atrophy ratio measure. Experiments on cognitive normal and atrophied MRI Brain images demonstrate the promising segmentation results of the...

In the study of early brain development, tissue segmentation of neonatal brain MR images remains challenging because of the insufficient image quality due to the properties of developing tissues. Among various brain tissue segmentation algorithms, atlas-based brain image segmentation can potentially achieve good segmentation results on neonatal brain images. However, their performances rely on ...

A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has emerged as a front-line diagnostic tool for brain tumors without ionizing radiation. Manual segmentation of brain tumor extent from 3D MRI volumes is a very time-consuming task and the performance is highly relied on...

Despite recent improvements in the accuracy of brain tumor segmentation, results still exhibit low levels confidence and robustness. Uncertainty estimation is one effective way to change this situation, as it provides a measure segmentation results. In paper, we propose trusted network which can generate robust reliable uncertainty estimations without excessive computational burden modification...

In the frame of medical imaging, accurate segmentation of brain MR images is of interest for many brain disorders. However, due to several factors such noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue segmentation remains a challenging task. So, in this paper, a full automatic framework for segmentation of brain MR images is presented. The framework consis...

In this paper, we present a new automatic segmentation method for magnetic resonance images. The aim of this segmentation is to divide the brain into homogeneous regions and to detect the presence of tumors. Our method is divided into two parts. First, we make a pre-segmentation to extract the brain from the head. Then, a second segmentation is done inside the brain. Several techniques are comb...