In this study, we investigated automatic laughter segmentation in meetings. We first performed laughterspeech discrimination experiments with traditional spectral features and subsequently used acousticphonetic features. In segmentation, we used Gaussian Mixture Models that were trained with spectral features. For the evaluation of the laughter segmentation we used time-weighted Detection Error...

This paper presents an automatic method for the surveying of cutaneous hemangiomas by means of a fully automatic hemangioma segmentation and a ruler visible in the images to be examined. The spatial resolution of the images is determined by computing the maximum Euclidean distance between two marks of the ruler. The segmentation of regions belonging to the hemangioma is accomplished with a pre-...

This thesis investigates the evaluation of automatic and manual text segmentation. Text segmentation is the process of placing boundaries within text to create segments according to some task-dependent criterion. An example of text segmentation is topical segmentation, which aims to segment a text according to the subjective definition of what constitutes a topic. A number of automatic segmente...

In this paper we present a robust skull-stripping method for the isolation of cerebral tissue in 3D Time-of-Flight (TOF) magnetic resonance angiographic images of the brain. 3D TOF images are often acquired in case of cerebral vascular diseases, because of their good blood-to-background-contrast. Skull-stripping is an essential preprocessing step towards a better segmentation as well as direct ...

Vessel segmentation is an important prerequisite for many medical applications. While automatic vessel segmentation is an active field of research, interaction and visualization techniques for semi-automatic solutions have gotten far less attention. Nevertheless, since automatic techniques do not generally achieve perfect results, interaction is necessary. Especially for tasks that require an i...

Spinal cord segmentation is a developing area of research intended to aid the processing and interpretation of advanced magnetic resonance imaging (MRI). For example, high resolution three-dimensional volumes can be segmented to provide a measurement of spinal cord atrophy. Spinal cord segmentation is difficult due to the variety of MRI contrasts and the variation in human anatomy. In this stud...

The study of neural circuit reconstruction, i.e., connectomics, is a challenging problem in neuroscience. Automated and semi-automated electron microscopy (EM) image analysis can be tremendously helpful for connectomics research. In this paper, we propose a fully automatic approach for intra-section segmentation and inter-section reconstruction of neurons using EM images. A hierarchical merge t...

Automatic cell segmentation has various application potentials in cytometry and histometry. In this paper, an automatic cluster (touching) cell segmentation approach using the dominant contour feature points has been presented. Dominant feature points are the locations of indentation on the contour of the cluster. First, dominant feature points on the contour of the cluster are detected by dist...

Spectral domain optical coherence tomography (SD-OCT) is used for cross-section imaging, in ophthalmology for retinal tissue. Extracting structural information about the retinal layers is becoming increasingly important, as this has the potential to expand retinal disease research and improve diagnosis. The purpose of our study was to facilitate a robust and efficient algorithm for segmentation...

This paper presents an automatic method of medical image segmentation used inthe study of the Central Nervous System (CNS) by multilevel thresholding based on histogram difference. Our method produced a performance of an 88.6%, for the considered testing images, when the results where compared with those provided by a human expert. Keywordsmedical image, Magnetic Resonance Imaging (MRI), image ...