Computed tomographic (CT) images are widely used in the diagnosis of stroke. In this
paper, we present an automated method to detect and classify an abnormality into acute …

Computed tomography images are widely used in the diagnosis of ischemic stroke because
of its faster acquisition and compatibility with most life support devices. This paper presents …

Neuroimaging plays an important role in the diagnosis brain lesions such as tumors, strokes
and infections. Within this context, magnetic resonance diffusion-weighted imaging (DWI) is …

Image segmentation is a primary step in image analysis used to separate the input image
into meaningful regions. MRI is an advanced medical imaging technique widely used in …

This article presents an unsupervised method for segmenting brain computed tomography
scans. The proposed methodology involves image feature extraction and application of …

With the evolution of technology, the fields of medicine and science have also witnessed
numerous advancements. In medical emergencies, a few minutes can be the difference …

Ischemic stroke is a condition in which brain stops working due to lack of blood supply
resulting in death of brain cells. Magnetic Resonance Imaging is widely used to detect …

Neuroimaging investigation is an essential parameter to detect infarct lesion in stroke
patients. Precise detection of brain lesions is an important task related to impaired behavior …

Gaussian Mixture Model for MRI Image Segmentation to Build a Three-Dimensional Image on
Brain Tumor Area 1 Introduction Page 1 MATEMATIKA, MJIAM, 2020, Volume 36, Number 3 …

This work proposes a methodology for segmenting structures and brain tissues in computed
tomography scans using unsupervised deep learning. The methodology involves extracting …