Radiologists encounter significant challenges when segmenting and determining brain
tumors in patients because this information assists in treatment planning. The utilization of …

Background and Objective Automatic tumor segmentation is a critical component in clinical
diagnosis and treatment. Although single-modal imaging provides useful information, multi …

The symmetrical segmentation of brain tumor images is crucial for both clinical diagnosis
and computer-aided prognosis. Traditional manual methods are not only asymmetrical in …

The online measurement of the surface roughness of cold-rolled strip steel plays a
significant role in the steel manufacturing process. However, the traditional mechanism …

Background Advances in high-throughput technologies have originated an ever-increasing
availability of omics datasets. The integration of multiple heterogeneous data sources is …

Automatic segmentation of brain tumors employing images from multi-modalities is important
for preoperative diagnosis and prognostic assessment. The rich complementary information …

Background Two types of non-invasive, radiation-free, and inexpensive imaging
technologies that are widely employed in medical applications are ultrasound (US) and …

Automatic medical image segmentation has shown great potential in recent years.
Howerver, magnetic resonance images (MRI) usually have the characteristics of noise and …

Purpose A brain tumor is defined as any group of atypical cells occupying space in the brain.
There are more than 120 types of them. MRI scans are used for brain tumor diagnosis since …

Magnetic resonance (MR) imaging is widely used for assessing infant head and brain
development and for diagnosing pathologies. The main goal of this work is the development …