The segmentation of brain tumors in medical images is a crucial step of clinical treatment.
Manual segmentation is time consuming and labor intensive, and existing automatic …

Segmentation of brain tumor from magnetic resonance imaging is a challenging and time-
consuming task due to the unpredictable appearance of tumor tissue in practical …

Segmentation of tumors in human brain aims to classify different abnormal tissues (necrotic
core, edema, active cells) from normal tissues (cerebrospinal fluid, gray matter, white matter) …

摘要脑肿瘤分割是医学图像处理中的一项重要内容, 其目的是辅助医生做出准确的诊断和治疗,
在临床脑部医学领域具有重要的实用价值. 核磁共振成像(MRI) 是临床医生研究脑部组织结构的 …

Automated segmentation of brain lesions in magnetic resonance images (MRI) is a difficult
procedure due to the variability and complexity of the location, size, shape, and texture of …

Background: Three-Dimensional visualization of brain tumors is very useful in both
diagnosis and treatment stages of brain cancer. Discussion: It helps the oncologist …

The glm R package is commonly used for generalized linear modeling. In this paper, we
evaluate the ability of the glm package to predict binomial outcomes using logistic …

This article provides an improved automated skin lesion segmentation method for
dermoscopic images. There are several stages for this method. These include the pre …

Oncological diseases are getting immense importance in today's Health care scenario.
Computational applications have critical role in medical applications. Accurate detection of …

Energy minimization is of particular interest in medical image analysis. In the past two
decades, a variety of optimization schemes have been developed. In this paper, we present …