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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/scan, Comment: 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 357-359

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, 65143R

Evaluating the degree of malignancy of a massive lesion on the basis of the mere visual analysis of the mammogram is a non-trivial task. We developed a semi-automated system for massive-lesion characterization with the aim to support the radiological diagnosis. A dataset of 226 masses has been used in the present analysis. The system performances have been evaluated in terms of the area under the ROC curve, obtaining A_z=0.80+-0.04., Comment: 4 pages, 2 figure; Proceedings of the Frontier Science 2005, 4th International Conference on Frontier Science, 12-17 September, 2005, Milano, Italy

We are developing a computer-aided detection (CAD) system for the identification of small pulmonary nodules in screening CT scans. The main modules of our system, i.e. a dot-enhancement filter for nodule candidate selection and a neural classifier for false positive finding reduction, are described. The preliminary results obtained on the so-far collected database of lung CT are discussed., Comment: 4 pages, 1 figure; Proceedings of the Frontier Science 2005, 4th International Conference on Frontier Science, 12-17 September, 2005, Milano, Italy

A computer-aided detection (CADe) system for the identification of microcalcification clusters in digital mammograms has been developed. It is mainly based on the application of wavelet transforms for image filtering and neural networks for both the feature extraction and the classification procedures. This CADe system is easily adaptable to different databases. We report and compare the FROC curves obtained on the private database we used for developing the CADe system and on the publicly available MIAS database. The results achieved on the two databases show the same trend, thus demonstrating the good generalization capability of the system., Comment: 4 pages, 1 figure; Proceedings of the Frontier Science 2005, 4th International Conference on Frontier Science, 12-17 September, 2005, Milano, Italy

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images with 1.25 mm slice thickness is presented. 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 results obtained on the collected database of lung CT scans are discussed., Comment: 3 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, Oct. 29 - Nov. 4, 2006, San Diego, California

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, Portugal

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 Rico

Mammography is widely recognized as the most reliable technique for early detection of breast cancers. Automated or semi-automated computerized classification schemes can be very useful in assisting radiologists with a second opinion about the visual diagnosis of breast lesions, thus leading to a reduction in the number of unnecessary biopsies. We present a computer-aided diagnosis (CADi) system for the characterization of massive lesions in mammograms, whose aim is to distinguish malignant from benign masses. The CADi system we realized is based on a three-stage algorithm: a) a segmentation technique extracts the contours of the massive lesion from the image; b) sixteen features based on size and shape of the lesion are computed; c) a neural classifier merges the features into an estimated likelihood of malignancy. A dataset of 226 massive lesions (109 malignant and 117 benign) has been used in this study. The system performances have been evaluated terms of the receiver-operating characteristic (ROC) analysis, obtaining A_z = 0.80+-0.04 as the estimated area under the ROC curve., Comment: 6 pages, 3 figures; Proceedings of the ITBS 2005, 3rd International Conference on Imaging Technologies in Biomedical Sciences, 25-28 September 2005, Milos Island, Greece

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, Greece

The use of automatic systems in the analysis of medical images has proven to be very useful to radiologists, especially in the framework of screening programs, in which radiologists make their first diagnosis on the basis of images only, most of those corresponding to healthy patients, and have to distinguish pathological findings from non-pathological ones at an early stage. In particular, we are developing preprocessing methods to be applied for pulmonary nodule Computer Aided Detection in low-dose lung Multi Slice CT (Computed Tomography) images., Comment: 5 pages, 2 figures, Computer Assisted Radiology and Surgery, Proceedings of the 19th International Congress and Exhibition, Berlin, June 22 - 25, 2005

A system for the automated detection of massive lesions in mammograms is presented. The approach we adopted is a pixel-based and multi-level one. Each pixel in a mammogram is flagged with the appropriate class membership, e.g. massive lesions or normal breast tissue., Comment: 1 page, Computer Assisted Radiology and Surgery, Proceedings of the 19th International Congress and Exhibition, Berlin, June 22 - 25, 2005

A breast neoplasia is often marked by the presence of microcalcifications and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. Our collaboration, among italian physicists and radiologists, has built a large distributed database of digitized mammographic images and has developed a Computer Aided Detection (CADe) system for the automatic analysis of mammographic images and installed it in some Italian hospitals by a GRID connection. Regarding microcalcifications, in our CADe digital mammogram is divided into wide windows which are processed by a convolution filter; after a self-organizing map analyzes each window and produces 8 principal components which are used as input of a neural network (FFNN) able to classify the windows matched to a threshold. Regarding massive lesions we select all important maximum intensity position and define the ROI radius. From each ROI found we extract the parameters which are used as input in a FFNN to distinguish between pathological and non-pathological ROI. We present here a test of our CADe system, used as a second reader and a comparison with another (commercial) CADe system., Comment: 4 pages, Proceedings of the 4th International Symposium on Nuclear and Related Techniques 2003, Vol. unico, pp. d10/1-d10/4 Havana, Cuba

The next generation of High Energy Physics (HEP) experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the Virtual Organisation (VO), a group of distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and proved to be useful in improving the radiologists' performances in the diagnosis. GRID technologies allow remote image analysis and interactive online diagnosis, with a potential for a relevant reduction of the delays presently associated to screening programs. A prototype of the system, based on AliEn GRID Services, is already available, with a central Server running common services and several clients connecting to it. Mammograms can be acquired in any location; the related information required to select and access them at any time is stored in a common service called Data Catalogue, which can be queried by any client. The result of a query can be used as input for analysis algorithms, which are executed on nodes that are in general remote to the user (but always local to the input images) thanks to the PROOF facility. The selected approach avoids data transfers for all the images with a negative diagnosis (about 95% of the sample) and allows an almost real time diagnosis for the 5% of images with high cancer probability., Comment: 9 pages, 4 figures; Proceedings of the HealthGrid Workshop 2004, January 29-30, Clermont-Ferrand, France

The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed database of digitised mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) software which is integrated in a station that can also be used for acquire new images, as archive and to perform statistical analysis. The images are completely described: pathological ones have a consistent characterization with radiologist's diagnosis and histological data, non pathological ones correspond to patients with a follow up at least three years. The distributed database is realized throught the connection of all the hospitals and research centers in GRID tecnology. In each hospital local patients digital images are stored in the local database. Using GRID connection, GPCALMA will allow each node to work on distributed database data as well as local database data. Using its database the GPCALMA tools perform several analysis. A texture analysis, i.e. an automated classification on adipose, dense or glandular texture, can be provided by the system. GPCALMA software also allows classification of pathological features, in particular massive lesions analysis and microcalcification clusters analysis. The performance of the GPCALMA system will be presented in terms of the ROC (Receiver Operating Characteristic) curves. The results of GPCALMA system as "second reader" will also be presented., Comment: 6 pages, Proceedings of the Seventh Mexican Symposium on Medical Physics 2003, Vol. 682/1, pp. 67-72, Mexico City, Mexico

The next generation of High Energy Physics experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the "Virtual Organisation" (VO), a group of geographycally distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and shows performances similar to radiologists in the diagnosis. GRID technologies will allow remote image analysis and interactive online diagnosis, with a relevant reduction of the delays presently associated to screening programs., Comment: 4 pages, 3 figures; to appear in the Proceedings of Frontier Detectors For Frontier Physics, 9th Pisa Meeting on Advanced Detectors, 25-31 May 2003, La Biodola, Isola d'Elba, Italy

The use of an automatic system for the analysis of mammographic images has proven to be very useful to radiologists in the investigation of breast cancer, especially in the framework of mammographic-screening programs. A breast neoplasia is often marked by the presence of microcalcification clusters and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. In the framework of the GPCALMA (GRID Platform for Computer Assisted Library for MAmmography) project, the co-working of italian physicists and radiologists built a large distributed database of digitized mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) system, able to make an automatic search of massive lesions and microcalcification clusters. The CAD is implemented in the GPCALMA integrated station, which can be used also for digitization, as archive and to perform statistical analyses. Some GPCALMA integrated stations have already been implemented and are currently on clinical trial in some italian hospitals. The emerging GRID technology can been used to connect the GPCALMA integrated stations operating in different medical centers. The GRID approach will support an effective tele- and co-working between radiologists, cancer specialists and epidemiology experts by allowing remote image analysis and interactive online diagnosis., Comment: 5 pages, 5 figures, to appear in the Proceedings of the 13th IEEE-NPSS Real Time Conference 2003, Montreal, Canada, May 18-23 2003

Purpose of this work is the development of an automatic system which could be useful for radiologists in the investigation of breast cancer. A breast neoplasia is often marked by the presence of microcalcifications and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. GPCALMA (Grid Platform Computer Assisted Library for MAmmography), a collaboration among italian physicists and radiologists, has built a large distributed database of digitized mammographic images (at this moment about 5500 images corresponding to 1650 patients). This collaboration has developed a CAD (Computer Aided Detection) system which, installed in an integrated station, can also be used for digitization, as archive and to perform statistical analysis. With a GRID configuration it would be possible for the clinicians tele- and co-working in new and innovative groupings ('virtual organisations') and, using the whole database, by the GPCALMA tools several analysis can be performed. Furthermore the GPCALMA system allows to be abreast of the CAD technical progressing into several hospital locations always with remote working by GRID connection. We report in this work the results obtained by the GPCALMA CAD software implemented with a GRID connection., Comment: 6 pages, 4 figures, to appear in CARS 2003 Proceedings, Computer Assisted Radiology and Surgery 17th International Congress and Exhibition, London, June 25-28, 2003

We present a general analysis of B_{s,d}-> l^+ l^- and K_L -> l^+ l^- decays in supersymmetric models with non-minimal sources of flavour mixing. In spite of the existing constraints on off-diagonal squark mass terms, these modes could still receive sizeable corrections, mainly because of Higgs-mediated FCNCs arising at large tan(beta). The severe limits on scenarios with large tan(beta) and non-negligible {tilde d}^i_{R(L)}-{d-tilde}^j_{R(L)} mixing imposed by the present experimental bounds on these modes and Delta B=2 observables are discussed in detail. In particular, we show that scalar-current contributions to K_L -> l^+ l^- and B-{bar B} mixing set non-trivial constraints on the possibility that B_s -> l^+ l^- and B_d -> l^+ l^- receive large corrections., Comment: 18 pages, 4 figures (v2: minor changes, published version)

We analyse the sensitivity to physics beyond the SM of T-odd correlations in $K_{\ell 4}$ decays, which do not involve the lepton polarization. We show that a combined analysis of $K^+_{\mu 4}$ and $K^-_{\mu 4}$ decays can lead to new constraints about CP violation in $\Delta S=1$ charged-current interactions, complementary to those obtained from the transverse muon polarization in $K_{\mu 3}$ and of comparable accuracy., Comment: 6 pages (LaTeX)

We analyse scalar flavour-changing neutral currents of down-type quarks in models with two Higgs doublets, coupled separately to up- and down-type quarks, in the limit where the ratio of the two expectation values ($\tan \beta = v_u/v_d$) is large. We clarify the origin of this phenomenon, both in $\Delta F=1$ and $\Delta F=2$ processes, analysing differences and analogies between supersymmetric and non-supersymmetric models. We confirm previous findings of a sizeable enhancement at large $\tan\beta$ of specific $\Delta F=1$ and $\Delta F=2$ amplitudes in the MSSM and, in these cases, we discuss how large-$\tan\beta$ corrections can be controlled beyond lowest order. Finally, we emphasize the unique role of the rare processes $B_{s,d} \to \tau^+ \tau^-$ and $B_{s,d} \to \mu^+ \mu^-$ in probing this scenario., Comment: 22 pages, Latex, 6 figures; v3: minor misprints corrected with respect to the published version

We computed the B_K parameter on the lattice by using a non-perturbatively improved Wilson action. From our quenched simulation, in the MSbar scheme and at mu=2 GeV, we obtain B_K=0.73(7)^{+0.05}_{-0.01}. To gain some insight in the systematic errors due to the use of the quenched approximation, we also made the unquenched computation with Wilson fermions. We do not observe any significant deviation with respect to the quenched result., Comment: 17 pages (LaTeX2e), 2 PostScript figures; version to appear in JHEP

We present the results of a quenched lattice calculation of the operator matrix elements relevant for predicting the Bs width difference. Our main result is (\Delta\Gamma_Bs/\Gamma_Bs)= (4.7 +/- 1.5 +/- 1.6) 10^(-2), obtained from the ratio of matrix elements, R(m_b)=<\bar B_s^0|Q_S|B_s^0>/<\bar B_s^0|Q_L|B_s^0>=-0.93(3)^(+0.00)_(-0.01). R(m_b) was evaluated from the two relevant B-parameters, B_S^{MSbar}(m_b)=0.86(2)^(+0.02)_(-0.03) and B_Bs^{MSbar}(m_b) = 0.91(3)^(+0.00)_(-0.06), which we computed in our simulation., Comment: 21 pages, 7 PostScript figures

Several quantities relevant to phenomenological studies of the mixing of neutral B mesons are computed on the lattice. Our main results are: f_{Bd} sqrt(B_{Bd})=206(28)(7) MeV, f_{Bs} sqrt(B_{Bs})/f_{Bd}sqrt(B_{Bd})=1.16(7). We also obtain the related quantities f_{Bs}sqrt(B{Bs})=237(18)(8) MeV, f_{Bd}= 174(22)(+7-0)(-4-0) MeV, f_{Bs}= 204(15)(+7-0)(+3-0) MeV, f_{Bs}/f_{Bd}=1.17(4)(+0-1), f_{Bd}/f_{Ds}=0.74(5). After combining our results with the experimental world average (Delta m_d), we predict (Delta m_s)=15.8(2.1)(3.3) ps^{-1}. We have also computed the relevant parameters for mixing of neutral D mesons which may be useful in some extensions of the Standard Model. All the quantities were obtained from a quenched simulation with a non-perturbatively improved Clover action at beta=6.2, corresponding to a lattice spacing 1/a=2.7(1) GeV, on a sample of 200 gauge-field configurations. A discussion of the main systematic errors is also presented., Comment: 21 pages (LaTeX2e), 5 PostScript figures