A hydrodynamical analysis of the steady-state shock model

In this article some of the hydrodynamical (HD) aspects of steady shocks as described by the steady-state shock model are reviewed and discussed. It is found that, at least in some of the contexts in which the steady-state model is used, the steady-state assumption cannot be satisfied. Moreover, the main result of the present work is that even if the assumptions on steadiness and on the geometry are fully satisfied, serious limitations in the application of the model are found: (i) in the absence of down-stream boundary conditions the model is not related to the physical process(es) that originate the shock, (ii) matter shocked during the presumed phase of steadiness of the shock is not hydrodynamically interacting with previously shocked matter, and (iii) the steady-state model assumes that the flow is stable against perturbations. Furthermore, even if boundary conditions were assumed, the link between the steady model and the astrophysical context would not be strictly speaking the correct HD link. Time-dependent HD computations in different astrophysical contexts (e.g. SNRs and molecular shocks) show that the steady-state approximation is inadequate to describe these post-shock structures. Based on the HD limitations of the steady-state model, it is advised that the model be used to describe post-shock structures only in those astrophysical contexts where full time-dependent HD models have already positively tested the steadiness of the flow. Alternatively, it is suggested to replace the steady-state model either with time-dependent HD models, or with less problematic approximations.Comment: 9 pages, to be published in The Open Astronomy Journal ( http://www.bentham.org/open/toaaj/index.htm

An automated system for lung nodule detection in low-dose computed tomography

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The results obtained on the collected database of low-dose thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.Comment: 9 pages, 9 figures; Proceedings of the SPIE Medical Imaging Conference, 17-22 February 2007, San Diego, California, USA, Vol. 6514, 65143

Computer-aided detection of pulmonary nodules in low-dose CT

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical CT images with 1.25 mm slice thickness is being developed in the framework of the INFN-supported MAGIC-5 Italian project. The basic modules of our lung-CAD system, a dot enhancement filter for nodule candidate selection and a voxel-based neural classifier for false-positive finding reduction, are described. Preliminary results obtained on the so-far collected database of lung CT scans are discussed.Comment: 3 pages, 4 figures; Proceedings of the CompIMAGE - International Symposium on Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications, 20-21 Oct. 2006, Coimbra, Portuga

A scalable system for microcalcification cluster automated detection in a distributed mammographic database

A computer-aided detection (CADe) system for microcalcification cluster identification in mammograms has been developed in the framework of the EU-founded MammoGrid project. The CADe software is mainly based on wavelet transforms and artificial neural networks. It is able to identify microcalcifications in different datasets of mammograms (i.e. acquired with different machines and settings, digitized with different pitch and bit depth or direct digital ones). The CADe can be remotely run from GRID-connected acquisition and annotation stations, supporting clinicians from geographically distant locations in the interpretation of mammographic data. We report and discuss the system performances on different datasets of mammograms and the status of the GRID-enabled CADe analysis.Comment: 6 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, October 23-29, 2005, Puerto Ric

Recombination Line vs. Forbidden Line Abundances in Planetary Nebulae

Recombination lines (RLs) of C II, N II, and O II in planetary nebulae (PNs) have been found to give abundances that are much larger in some cases than abundances from collisionally-excited forbidden lines (CELs). The origins of this abundance discrepancy are highly debated. We present new spectroscopic observations of O II and C II recombination lines for six planetary nebulae. With these data we compare the abundances derived from the optical recombination lines with those determined from collisionally-excited lines. Combining our new data with published results on RLs in other PNs, we examine the discrepancy in abundances derived from RLs and CELs. We find that there is a wide range in the measured abundance discrepancy Delta(O+2) = log O+2(RL) - log O+2(CEL), ranging from approximately 0.1 dex up to 1.4 dex. Most RLs yield similar abundances, with the notable exception of O II multiplet V15, known to arise primarily from dielectronic recombination, which gives abundances averaging 0.6 dex higher than other O II RLs. We compare Delta(O+2) against a variety of physical properties of the PNs to look for clues as to the mechanism responsible for the abundance discrepancy. The strongest correlations are found with the nebula diameter and the Balmer surface brightness. An inverse correlation of Delta(O+2) with nebular density is also seen. Similar results are found for carbon in comparing C II RL abundances with ultraviolet measurements of C III].Comment: 48 pages, 14 figures, accepted for publication in the Astrophysical Journal Supplemen

A scalable Computer-Aided Detection system for microcalcification cluster identification in a pan-European distributed database of mammograms

A computer-aided detection (CADe) system for microcalcification cluster identification in mammograms has been developed in the framework of the EU-founded MammoGrid project. The CADe software is mainly based on wavelet transforms and artificial neural networks. It is able to identify microcalcifications in different kinds of mammograms (i.e. acquired with different machines and settings, digitized with different pitch and bit depth or direct digital ones). The CADe can be remotely run from GRID-connected acquisition and annotation stations, supporting clinicians from geographically distant locations in the interpretation of mammographic data. We report the FROC analyses of the CADe system performances on three different dataset of mammograms, i.e. images of the CALMA INFN-founded database collected in the Italian National screening program, the MIAS database and the so-far collected MammoGrid images. The sensitivity values of 88% at a rate of 2.15 false positive findings per image (FP/im), 88% with 2.18 FP/im and 87% with 5.7 FP/im have been obtained on the CALMA, MIAS and MammoGrid database respectively.Comment: 6 pages, 5 figures; Proceedings of the ITBS 2005, 3rd International Conference on Imaging Technologies in Biomedical Sciences, 25-28 September 2005, Milos Island, Greec

Spatially resolved spectroscopy of Cassiopeia A with MECS on board B⃗eppo{\vec Beppo}SAX

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Automated detection of lung nodules in low-dose computed tomography

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector computed-tomography (CT) images has been developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, consisting in a 3D dot-enhancement filter for nodule detection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The database used in this study consists of 17 low-dose CT scans reconstructed with thin slice thickness (~300 slices/scan). The preliminary results are shown in terms of the FROC analysis reporting a good sensitivity (85% range) for both internal and sub-pleural nodules at an acceptable level of false positive findings (1-9 FP/scan); the sensitivity value remains very high (75% range) even at 1-6 FP/scanComment: 4 pages, 2 figures: Proceedings of the Computer Assisted Radiology and Surgery, 21th International Congress and Exhibition, Berlin, Volume 2, Supplement 1, June 2007, pp 357-35