Multi-scale analysis of lung computed tomography images

A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.Comment: 18 pages, 12 low-resolution figure

Imaging spectroscopic performances for a Si based detection system

We present the imaging and spectroscopic capabilities of a system based on a single photon counting chip (PCC) bump-bonded on a Si pixel detector. The system measures the energy spectrum and the flux, produced by a standard mammographic tube. We have also made some images of low contrast details, achieving good results

Study of the spectral response of CZT multiple-electrode detectors

Cadmium zinc telluride (CZT) is a promising material for room temperature X-ray and gamma-ray detectors. The high atomic number and the wide band-gap give high quantum efficiency and good room temperature performances. Due to hole trapping, particular electrode structures have been developed to provide single-charge carrier collection (electrons), exploiting the excellent charge transport properties of the electrons. In this work, the spectroscopic performances of two CZT detectors (CZT1: 5 mm times 5 mm times 0.90 mm; CZT2: 4.8 mm times 5 mm times 0.55 mm) with five electrodes (cathode, anode and three steering electrodes) were studied. The anode-collecting electrode, surrounded by three steering electrodes (biased for optimum charge collection), is mostly sensitive to electron carriers, overcoming the effects of hole trapping in the measured spectra (hole tailing). We investigated on the spectroscopic response (241Am source; 59.5 keV) of the detectors at different bias voltages of the electrodes. The detectors exhibit excellent energy resolution (CZT1: 2.0% FWHM at 59.5 keV; CZT2: 1.7% FWHM at 59.5 keV; working temperature -10degC) and low tailing (CZT1: FW.1M to FWHM ratio of 1.93 at 59.5 keV; CZT2: 2.35 at 59.5 keV). This study stresses on the excellent spectroscopic properties of the CZT detectors equipped with a custom anode layout, making them very attractive candidates as x-ray spectrometers mainly for medical applications

Low contrast imaging with a GaAs pixel digital detector

A digital mammography system based on a GaAs pixel detector has been developed by the INFN (Istituto Nazionale di Fisica Nucleare) collaboration MED46. The high atomic number makes the GaAs a very efficient material for low energy X-ray detection (10-30 keV is the typical energy range used in mammography). Low contrast details can be detected with a significant dose reduction to the patient. The system presented in this paper consists of a 4096 pixel matrix built on a 200 μm thick semi-insulating GaAs substrate. The pixel size is 170×170 μm2 for a total active area of 1.18 cm2 . The detector is bump-bonded to a VLSI front-end chip which implements a single-photon counting architecture. This feature allows to enhance the radiographic contrast detection with respect to charge integrating devices. The system has been tested by using a standard mammographic tube. Images of mammographic phantoms will be presented and compared with radiographs obtained with traditional film/screen systems. Monte Carlo simulations have been also performed to evaluate the imaging capability of the system. Comparison with simulations and experimental results will be shown

Advantages of quasi-monochromatic X-ray sources in absorption mammography

Mammography is a challenging field of medical imaging. Early detection of breast cancer requires identifying small contrast details. The choice of the appropriate monochromatic energy enhances the visibility of such details. Thomson scattering source can provide tunable quasi-monochromatic X-ray beams. In this work, we investigate by Monte Carlo simulations the optimal monochromatic energy to image mammographic phantoms. In order to mimic a Thomson scattering source, we consider the effect on image quality of the presence of an energy spread and of the presence of higher-order harmonics

Compact x-ray sources for mammographic applications: Monte Carlo simulations of image quality

Thomson scattering x-ray sources can provide spectral distributions that are ideally suited for mammography with sufficient fluence rates. In this article, the authors investigate the effects of different spectral distributions on the image quality in simulated images of a breast mammographic phantom containing details of different compositions and thicknesses. They simulated monochromatic, quasimonochromatic, and polychromatic x-ray sources in order to define the energy for maximum figure of merit (signal-difference-to-noise ratio squared/mean glandular dose), the effect of an energy spread, and the effect of the presence of higher-order harmonics. The advantages of these sources with respect to conventional polychromatic sources as a function of phantom and detail thickness were also investigated. The results show that the energy for the figure of merit peak is between 16 and 27.4 keV, depending on the phantom thickness and detail composition and thickness. An energy spread of about 1 keV standard deviation, easily achievable with compact x-ray sources, does not appreciably affect the image quality

Dissimilarity Application in Digitized Mammographic Images Classification

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, an alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) the training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features extracted from co-occurrence matrix containing spatial statistics information on ROI pixel grey tones. A dissimilarity representation of these features is made before the classification. A feed-forward neural network is employed to distinguish pathological records, from non-pathological ones by the new features. The results obtained in terms of sensitivity and specificity will be presented

Voxel-based Monte Carlo simulation of x-ray imaging and spectroscopy experiments

A Monte Carlo code for the simulation of X-ray imaging and spectroscopy experiments in heterogeneous samples is presented. The energy spectrum, polarization and profile of the incident beam can be defined so that X-ray tube systems as well as synchrotron sources can be simulated. The sample is modeled as a 3D regular grid. The chemical composition and density is given at each point of the grid. Photoelectric absorption, fluorescent emission, elastic and inelastic scattering are included in the simulation. The core of the simulation is a fast routine for the calculation of the path lengths of the photon trajectory intersections with the grid voxels. The voxel representation is particularly useful for samples that cannot be well described by a small set of polyhedra. This is the case of most naturally occurring samples. In such cases, voxel-based simulations are much less expensive in terms of computational cost than simulations on a polygonal representation. The efficient scheme used for calculating the path lengths in the voxels and the use of variance reduction techniques make the code suitable for the detailed simulation of complex experiments on generic samples in a relatively short time. Examples of applications to X-ray imaging and spectroscopy experiments are discussed

Mechanisms Underlying Cell Therapy in Liver Fibrosis : An Overview

Fibrosis is a common feature in most pathogenetic processes in the liver, and usually results from a chronic insult that depletes the regenerative capacity of hepatocytes and activates multiple inflammatory pathways, recruiting resident and circulating immune cells, endothelial cells, non-parenchymal hepatic stellate cells, and fibroblasts, which become activated and lead to excessive extracellular matrix accumulation. The ongoing development of liver fibrosis results in a clinically silent and progressive loss of hepatocyte function, demanding the constant need for liver transplantation in clinical practice, and motivating the search for other treatments as the chances of obtaining compatible viable livers become scarcer. Although initially cell therapy has emerged as a plausible alternative to organ transplantation, many factors still challenge the establishment of this technique as a main or even additional therapeutic tool. Herein, the authors discuss the most recent advances and point out the corners and some controversies over several protocols and models that have shown promising results as potential candidates for cell therapy for liver fibrosis, presenting the respective mechanisms proposed for liver regeneration in each case