Thoracic and abdominal multi-organ segmentation has been a challenging problem due to the inter-subject variance of human thoraxes and abdomens as well as the complex 3D intra-subject variance among organs. In this paper, we present a preliminary method for automatically segmenting multiple organs using non-enhanced CT data. The method is based on a simple framework using generic tools and requ...

An algorithm is presented for fully automated brain tumor segmentation from only two magnetic resonance image modalities. The technique is based on three steps: (1) alternating different levels of automatic histogram-based multi-thresholding step, (2) performing an effective and fully automated procedure for skull-stripping by evolving deformable contours, and (3) segmenting both Gross Tumor Vo...

We employed Fuzzy Connectedness method to perform an intraoperative segmentation [1]. We limited the region to be analyzed, so the processing time became less than ten seconds. The accuracy of the presented method was validated in nine patients with glioma. Goodness-of-match between the manual and automatic segmentation was evaluated by two established measurements of segmentation accuracy, Per...

In wide area networks, retrieving the relevant text is a challenging task for information retrieval because most of the information requests are text based. The focus of paper is on the similarity measurement, performance evaluation and design of information retrieval techniques using the four similarity functions i.e. Jaccard, Cosine, Dice and Overlap. The performance evaluation of these simil...

This paper describes our approach to the Detailed Analysis subtask of the PAN 2012 competition. Our experiments deal with monolingual plagiarism cases, only. We use a simple set-based algorithm, that employs Dice’s coefficient as a similarity measure. Furthermore we employ basic strategies from Information Retrieval and Natural Language Processing for stop word removal and language detection. W...

This paper offers a new method inspired by classic importance-performance analysis (IPA) that provides a global index of importance versus performance for firms together with a new version of the IPA diagram. The index compares two rankings of the same set of features regarding importance and performance, taking into account under-performing features. The marginal contribution of each feature t...

The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance ...

BACKGROUND AND PURPOSE Robust, automated segmentation algorithms are required for quantitative analysis of large imaging datasets. We developed an automated method that identifies and labels brain tumor-associated pathology by using an iterative probabilistic voxel labeling using k-nearest neighbor and Gaussian mixture model classification. Our purpose was to develop a segmentation method which...

The precise and accurate segmentation of the vertebral column is essential in the diagnosis and treatment of various orthopedic, neurological, and oncological traumas and pathologies. Segmentation is especially challenging in the presence of pathology such as vertebral compression fractures. In this paper, we propose a method to produce segmentations for osteoporotic compression fractured verte...