Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without tex...

brain mr images tissue segmentation is one of the most important parts of the clinical diagnostic tools. pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy but they need a large amount of labeled data, which is hard, expensive and slow to obtain. moreove...

Dynamic textures can be defined as repetitive patterns that exhibit both spatial and temporal coherence. The problem of capturing this intrinsic behavior of a dynamic texture by learning a model from an input video is addressed. Application of a model-based method to dynamic texture synthesis, video compression and videoediting is demonstrated. Results from a method for segmentation of multiple...

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneo...

BACKGROUND The measurement of dynamic parameters, such as the length of applanation and the amplitude of deformation, is significant for evaluating corneal properties. Most of the corneal properties (related to shape) including the anterior corneal curvature and the thickness of cornea can be easily measured using some existing techniques. However, they only provide the static or pseudo-dynamic...

The automatic segmentation of land cover features, within very high resolution (VHR) satellite imagery, is a complex task which is important to geo-spatial applications such as urban planning, crop monitoring and change detection. The dynamic grey-value variety of VHR imagery, along with environmental interference factors, such as cloud cover and poor lighting, impede the automation of land cov...

Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI) segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this ...

Objective: MRI-guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment two-dimensional (2D) upper abdominal dynamic MRI (dMRI) is developed for this purpose. Methods: 2D coronal dynamic M...

Rectal tumour segmentation in dynamic contrast-enhanced MRI (DCE-MRI) is a challenging task, and an automated and consistent method would be highly desirable to improve the modelling and prediction of patient outcomes from tissue contrast enhancement characteristics - particularly in routine clinical practice. A framework is developed to automate DCE-MRI tumour segmentation, by introducing: per...