Accurate medical image segmentation is essential for diagnosis, surgical planning and many other applications. Convolutional Neural Networks (CNNs) have shown to be state-of-the-art automatic segmentation methods while the result still needs to be refined to become accurate and robust enough for clinical use. We propose a deep learning-based interactive segmentation method in order to improve t...

OBJECTIVE To design a novel ex-vivo acquisition technique to establish a common framework to validate different segmentation techniques for oncological PET images. To evaluate several automatic segmentation algorithms on this set of images. MATERIAL AND METHODS In 15 patients with cancer, ex-vivo PET studies of surgical specimens removed during surgery were performed after injection of (18)F-...

Automatic video segmentation plays an important role in a wide range of computer vision and image processing applications. Recently, various methods have been proposed for this purpose. The problem is that most of these methods are far from real-time processing even for low-resolution videos due to the complex procedures. To this end, we propose a new and quite fast method for automatic video s...

Audio transcriptions from Automatic Speech Recognition systems are a continuous stream of words that are difficult to read. Segmenting these transcriptions into thematically distinct stories and categorizing the stories by topics increases readability and comprehensibility. However, manually defined topic categories are rarely available, and the cost of annotating a large corpus with thousands ...

A fine-grained segmentation of Radio or TV broadcasts is an essential step for most multimedia processings. Applying segmentation algorithms to the speech transcripts seems straightforward. Yet, most of these algorithms are not suited when dealing with short segments or noisy data. In this paper, we propose a new segmentation technique inspired from the image segmentation field and relying on a...

The first task to be accomplished in speech recognition is the segmentation and labeling of records. Regarding speech, this is a very complicated and costly procedure, although of most importance because at the present time many available speech corpora are not segmented. This paper proposes a semi-automatic segmentation method in order to reduce the manual segmentation burden of a very large c...

introduction this research addresses the automatic extraction of alluvial fans using four methods of segmentation from satellite data. this segmentation method divides images into partitions. it is typically used to recognize objects or other relevant purposes in digital images (fu, 2013:3260). alluvial fans have always been a landform that attracts human because they are suitable areas for liv...

There has been a significant increase from 2010 to 2016 in the number of people suffering from spine problems. The automatic image segmentation of the spine obtained from a computed tomography (CT) image is important for diagnosing spine conditions and for performing surgery with computer-assisted surgery systems. The spine has a complex anatomy that consists of 33 vertebrae, 23 intervertebral ...