A brain Magnetic resonance imaging (MRI) scan of a single individual consists of several
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …

This volume contains the proceedings of the 7th Euro-China Conference on Intelligent Data
Analysis and Applications (ECC 2021), which is hosted by Communication University of …

Background: The brain magnetic resonance imaging (MRI) image segmentation method
mainly refers to the division of brain tissue, which can be divided into tissue parts such as …

In recent years, brain magnetic resonance imaging (MRI) image segmentation has drawn
considerable attention. MRI image segmentation result provides a basis for medical …

Purpose Screening is the predominant strategy for the early detection of breast cancer.
However, image analysis depends on the experience of the radiologist, inserting subjective …

Global digitization trends and the application of high technology in the garment market are
still too slow to integrate, despite the increasing demand for automated solutions. The main …

The outbreak of coronavirus is intense in most countries around the world. The Region of
Interest (ROI) extraction in medical images plays a vital role in the disease diagnosis and …

Background In recent years, with the acceleration of life rhythm and increased pressure, the
problem of sleep disorders has become more and more serious. It affects people's quality of …

Automatic medical image segmentation via convolutional neural networks (CNNs) has
shown promising results. However, they may not always be robust enough for clinical use …

The conventional K‐Means clustering algorithm is widely used for grouping similar data
points by initially selecting random centroids. However, the accuracy of clustering results is …