We present a tool which supports CT specialists in exploring the parameter and result space of volume segmentation pipelines. In a preprocessing step, the user samples the parameter space of a number of pipelines to be analysed. Our sampling tool supports arbitrary pipeliness that can be parametrized via the command line. The user can then explore the space of possible results of the sampled pi...

customers segmentation and analyzing their behavior at fast moving costumer goods (fmgs) industries which deal with a large number of customers with a variety of characteristics causes the marketing activities to be targeted and leads to effective communication with the customers. segmentation, a data mining approach, which leads to the discovery of similar groups of customers, is usually done ...

We present a damage pattern mining framework for hurricane data on residential houses using aerial photographs with 1:3000 based scale. The vertical photographs are normally collected for an overview of a disaster area or for more detailed assessment. Damage on roof, especially for shingles torn off, is expected to be discovered in a more efficient and automatic way instead of going through the...

In biomedical imaging reliable segmentation of objects (e.g. from small cells up to large organs) is of fundamental importance for automated medical diagnosis. New approaches for multi-scale segmentation can considerably improve performance in case of natural variations in intensity, size and shape. This paper aims at segmenting objects of interest based on shape contours and automatically find...

OBJECTIVE Develop a real-time algorithm to automatically discriminate suppressions from non-suppressions (bursts) in electroencephalograms of critically ill adult patients. METHODS A real-time method for segmenting adult ICU EEG data into bursts and suppressions is presented based on thresholding local voltage variance. Results are validated against manual segmentations by two experienced hum...

Virtually all segmentation methods require parameter tuning, quite a difficult task, mostly performed manually through a troublesome trial-and-error process. To overcome this difficulty, an earlier work describes an automatic parameter adjustment method using Genetic Algorithms (GAs), given an initial set of reference object samples. The method performs well only for homogeneous objects. Howeve...

Multi-scale/multi-level geographic object-based image analysis (MS-GEOBIA) methods are becoming widely-used in remote sensing because single-scale/single-level (SSGEOBIA) methods are often unable to obtain an accurate segmentation and classification of all land use/land cover (LULC) types in an image. However, there have been few comparisons between SS-GEOBIA and MS-GEOBIA approaches for the pu...

The segmentation of satellite images is a valuable tool to obtain useful information about the spatial distribution of different land cover types. The use of segmentation algorithms instead of the traditional pixel-by-pixel classifiers used to produce land cover maps results on images that exhibit a more homogeneous distribution of classes, showing the piecewise spatial continuity of the real w...

Graph cuts based interactive segmentation has become very popular over the last decade. In standard graph cuts, the extraction of foreground object in a complex background often leads to many segmentation errors and the parameter λ in the energy function is hard to select. In this paper, we propose an iterated graph cuts algorithm, which starts from the sub-graph that comprises the user labeled...

Introduction: Brain tumors such as glioma are among the most aggressive lesions, which result in a very short life expectancy in patients. Image segmentation is highly essential in medical image analysis with applications, particularly in clinical practices to treat brain tumors. Accurate segmentation of magnetic resonance data is crucial for diagnostic purposes, planning surgical treatments, a...