Abstract Machine learning (ML) algorithms have made a tremendous impact in the field of
medical imaging. While medical imaging datasets have been growing in size, a challenge …

Magnetic resonance (MR) brain image segmentation of different anatomical structures or
tissue types has become a critical requirement in the diagnosis of neurological diseases …

Vehicle-mounted ground-penetrating radar (GPR) technology is an effective means of
detecting railway subgrade diseases. However, existing methods of GPR data interpretation …

In this paper, we present a semi-supervised clustering-based framework for discovering
coherent subpopulations in heterogeneous image sets. Our approach involves limited …

Automatic defects detection in Magnetic Resonance Images (MRI) is a crucial factor in
several diagnostic applications. This paper presents an intelligent Neural Networks (NN) …

(∗ 通信作者电子邮箱lihongliang@ ucas. ac. cn) 摘要: 医学影像分割是计算机辅助诊断中的一
项基础且关键的任务, 目的在于从像素级别准确识别出目标器官, 组织或病变区域 …

In many real binary classification problems, in addition to the presence of positive and
negative classes, we are also given the examples of third neutral class, ie, the examples …

Two semi-supervised feature extraction methods are proposed for electroencephalogram
(EEG) classification. They aim to alleviate two important limitations in brain–computer …

Due to the limitation of ethics and the number of professional annotators, pixel-wise
annotations for medical images are hard to obtain. Thus, how to exploit limited annotations …

Nowadays, automatic defects detection in MR images is very important in many diagnostic
and therapeutic applications. Because of high quantity data in MR images and blurred …