0000000000490593
AUTHOR
Pasquale Delogu
A test to evaluate the impact of the CAD tools in mammographic diagnosis
In this work we present the results of a study about the impact of CAD tools on Sensitivity and Specificity in mammographic diagnosis. The approach is aimed to evaluate the statistical significance through the comparison of these figures of merit obtained in different situations. For this purpose two different CAD tools, the CALMA station (INFN project) and the SecondLook™ station (by CADx) have been used as a support for radiologists.
Preprocessing methods for nodule detection in lung CT
Abstract 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.
Distributed medical images analysis on a Grid infrastructure
In this paper medical applications on a Grid infrastructure, the MAGIC-5 Project, are presented and discussed. MAGIC-5 aims at developing Computer Aided Detection (CADe) software for the analysis of medical images on distributed databases by means of GRID Services. The use of automated systems for analyzing medical images improves radiologists’ performance; in addition, it could be of paramount importance in screening programs, due to the huge amount of data to check and the cost of related manpower. The need for acquiring and analyzing data stored in different locations requires the use of Grid Services for the management of distributed computing resources and data. Grid technologies allow…
GPCALMA: A Grid-based tool for mammographic screening
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…
GPCALMA, a mammographic CAD in a GRID connection
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…
GPCALMA: An Italian mammographic database of digitized images for research
In this work the implementation of a database of digitized mammograms is described. The digitized images were collected since 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals, as a first step in order to develop and implement a Computer Aided Detection (CAD) system. 3369 mammograms were collected from 967 patients; they were classified according to the type and the morphology of the lesions, the type of the breast tissue and the type of pathologies. A dedicated Graphical User Interface was developed for mammography visualization and processing, in order to support the medical diagnosis directly on a high-resolution screen. The database has be…
MAGIC-5: an Italian mammographic database of digitised images for research
The implementation of a database of digitised mammograms is discussed. The digitised images were collected beginning in 1999 by a community of physicists in collaboration with radiologists in several Italian hospitals as a first step in developing and implementing a computer-aided detection (CAD) system. All 3,369 mammograms were collected from 967 patients and classified according to lesion type and morphology, breast tissue and pathology type. A dedicated graphical user interface was developed to visualise and process mammograms to support the medical diagnosis directly on a high-resolution screen. The database has been the starting point for developing other medical imaging applications,…
Comparison of two portable solid state detectors with an improved collimation and alignment device for mammographic x-ray spectroscopy
We describe a portable system for mammographic x-ray spectroscopy, based on a 2 X 2 X 1 mm3 cadmium telluride (CdTe) solid state detector, that is greatly improved over a similar system based on a 3 X 3 X 2 mm3 cadmium zinc telluride (CZT) solid state detector evaluated in an earlier work. The CdTe system utilized new pinhole collimators and an alignment device that facilitated measurement of mammographic x-ray spectra. Mammographic x-ray spectra acquired by each system were comparable. Half value layer measurements obtained using an ion chamber agreed closely with those derived from the x-ray spectra measured by either detector. The faster electronics and other features of the CdTe detecto…
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…