Abstract Aim To identify the sac and defect using deep learning algorithms to compute hernial volume in an automated fashion. Materials methods 70 ventral hernia CT scans were used. Slices with annotated computer vision tools. 80% of data was used for training validation. 20% testing. We a combination 3D reconstruction train models. The model output compared manual annotation by experts. Result...

Hexoses and pentoses can be measured either singly or in combination, with an o-anisidine reagent. It has the advantages of a fastreactionrateand relativelylittle interference from hexoses (Amax = 660 nm) in the measurement of pentoses. A simple subtraction of absorbance attributable to glucose at the maximum for pentoses (465 nm) is sufficient for satisfactory pentose estimation in urine. The ...

Providing valuable semantic descriptors of multimedia content is a topic of high interest for music content processing. Such descriptors should merge the two predicates of (1) being useful for different operations such as retrieval, visual representation of collections, classification, etc., and (2) being automatically extractable from the source. In this paper the semantic descriptor concept m...

The NIST Automated Computer Time Service (ACTS) is a telephone time service designed to provide computers with telephone access to time generated by the National Institute of Standards and Technology at accuracies approaching 1 ms. Features of the service include automated estimation by the transmitter of the telephone-line delay, advanced alert for changes to and from daylight saving time, and...

By using the test-driven development practice of the Extreme Programming methodology, programmers write extensive automated unit and acceptance tests. This paper outlines an approach for utilizing the results of these automated tests to estimate software system reliability and for providing feedback to developers on the quality of their test cases. Our initial reliability estimation and feedbac...

This paper presents a system for the automated inference of complex mental states from observed facial expressions and head gestures in video. Head actions are identified from image-based pose estimation. Facial actions, including asymmetric ones, are extracted from motion, color and shape parameters. A multi-level dynamic Bayesian network classifier models complex mental states as a sequence o...

In this paper we propose a model based approach to determine correspondences and pose of objects in automated visual inspection applications. The method does not consider correspondence and pose estimation problems as two distinct processes. Rather they are viewed as two cooperative processes and implemented through a proposed new composite chromosome structure of Genetic Algorithm (GA). GA evo...

Binding estimation after refinement (BEAR) is a novel automated computational procedure suitable for correcting and overcoming limitations of docking procedures such as poor scoring function and the generation of unreasonable ligand conformations. BEAR makes use of molecular dynamics simulation followed by MM-PBSA and MM-GBSA binding free energy estimates as tools to refine and rescore the stru...

This paper presents an automated and clinicallytested method for detection of brain abnormalities and tumor-edema segmentation using the MRI sequences. It follows a Radiologist’s approach to the brain diagnosis using multiple MRI sequences instead of any prior models or training phases. Our procedure consists of the following steps: a) Pre-processing of the MRI sequences, T2, T1 and T1 post con...

Magnetic resonance spectroscopic imaging (MRSI) provides simultaneous observation of MR spectra from multiple volumes over the observed region, and is a powerful tool for in vivo studies of metabolism. The quantification of MRSI data is widely used [ 1,2] in in vivo biomedical studies, however, traditional quantification methods of M R spectra data are time consuming and unsuitable for processi...