1,025 research outputs found
An automatic system to discriminate malignant from benign massive lesions in mammograms
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,
Ital
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
GPCALMA: a Grid Approach to Mammographic Screening
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, Ital
VisIVO - Integrated Tools and Services for Large-Scale Astrophysical Visualization
VisIVO is an integrated suite of tools and services specifically designed for
the Virtual Observatory. This suite constitutes a software framework for
effective visual discovery in currently available (and next-generation) very
large-scale astrophysical datasets. VisIVO consists of VisiVO Desktop - a stand
alone application for interactive visualization on standard PCs, VisIVO Server
- a grid-enabled platform for high performance visualization and VisIVO Web - a
custom designed web portal supporting services based on the VisIVO Server
functionality. The main characteristic of VisIVO is support for
high-performance, multidimensional visualization of very large-scale
astrophysical datasets. Users can obtain meaningful visualizations rapidly
while preserving full and intuitive control of the relevant visualization
parameters. This paper focuses on newly developed integrated tools in VisIVO
Server allowing intuitive visual discovery with 3D views being created from
data tables. VisIVO Server can be installed easily on any web server with a
database repository. We discuss briefly aspects of our implementation of VisiVO
Server on a computational grid and also outline the functionality of the
services offered by VisIVO Web. Finally we conclude with a summary of our work
and pointers to future developments
An Automatic System to Discriminate Malignant from Benign Massive Lesions on Mammograms
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, Greec
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
Phase Contrast Imaging Using a Single Picosecond X-ray Pulse of the Inverse Compton Source at the Bnl Accelerator Test Facility
Inverse Compton scattering (ICS) X-ray sources are of current interest due to their novel features that enable new methods in medical and biological imaging. As a compelling example of such a possibility, we present an experimental demonstration of single shot inline phase contrast imaging using the ICS source located at the BNL Accelerator Test Facility. The phase contrast effect is clearly observed in the images obtained. Further, its qualities are shown to be in agreement with the predictions of theoretical models through comparison of experimental and simulated images of a set of plastic wires of differing composition and size. We also display an example of application of the technique to single shot phase contrast imaging of a biological sample
Hallmarks of mechanochemistry: From nanoparticles to technology
The aim of this review article on recent developments of mechanochemistry (nowadays established as a part of chemistry) is to provide a comprehensive overview of advances achieved in the field of atomistic processes, phase transformations, simple and multicomponent nanosystems and peculiarities of mechanochemical reactions. Industrial aspects with successful penetration into fields like materials engineering, heterogeneous catalysis and extractive metallurgy are also reviewed. The hallmarks of mechanochemistry include influencing reactivity of solids by the presence of solid-state defects, interphases and relaxation phenomena, enabling processes to take place under non-equilibrium conditions, creating a well-crystallized core of nanoparticles with disordered near-surface shell regions and performing simple dry time-convenient one-step syntheses. Underlying these hallmarks are technological consequences like preparing new nanomaterials with the desired properties or producing these materials in a reproducible way with high yield and under simple and easy operating conditions. The last but not least hallmark is enabling work under environmentally friendly and essentially waste-free conditions (822 references).Slovak Grant Agency VEGA 2/0009/11, 2/0043/11Slovak Agency for Science and Development APVV VV-0189-10, VV-0528-11Russian Foundation for Basic Research 10-03-00942a, 12-03-00651aMinistry of Science and Higher education in Poland CUT/c-1/DS/KWC/2008-2012, PB1T09B02330, NN209145136, NN20914893
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