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Biomedical subjects

M E Fantacci

Publications and source records attributed to M E Fantacci.

5 recordsLinked to original sources
PubMed2006

A completely automated CAD system for mass detection in a large mammographic database.

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

Algorithms↗
PubMed2006

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 detector allowed its use with a larger pinhole collimator than could be used with the CZT detector. Additionally, the improved pinhole collimator and alignment features of the apparatus permitted much more rapid setup for acquisition of x-ray spectra than was possible on the system described in the earlier work. These improvements in detector technology, collimation and ease of alignment, as well as low cost, make this apparatus attractive as a tool for both laboratory research and advanced mammography quality control.

Calibration↗
PubMed2005

GPCALMA: a Grid-based tool for mammographic screening.

OBJECTIVES: The next generation of high energy physics (HEP) experiments requires a GRID approach to a distributed computing system: the key concept is the Virtual ORGANISATION (VO), a group of distributed users with a common goal and the will to share their resources. METHODS: A similar approach, applied to a group of hospitals that joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. The application code makes use of neural networks for the image analysis and is useful in improving the radiologists' diagnostic performance. GRID services allow remote image analysis and interactive online diagnosis, with a potential for a relevant reduction of the delays presently associated with screening programs. RESULTS AND CONCLUSIONS: A prototype of the system, based on AliEn GRID Services [1], is already available, with a central server running common services [2] 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. Thanks to the PROOF facility [3], the result of a query can be used as input for analysis algorithms, which are executed on the nodes where the input images are stored,. The selected approach avoids data transfers for all the images with a negative diagnosis and allows an almost real time diagnosis for the set of images with high cancer probability.

Algorithms↗
PubMed2004

A study on two different CAD systems for mammography as an aid to radiological diagnosis in the search of microcalcification clusters.

OBJECTIVE: The aim of the present study was to evaluate the efficacy of two different computer aided detection (CAD) systems for mammography in improving radiological diagnosis in the search of microcalcification clusters. The CAD systems used are: the SecondLooktrade mark (CADx Medical Systems, Canada) commercial system and the CALMA (computer assisted library in MAmmography) research CAD system. Three radiologists were asked to read mammographic images with and without the support of the CAD systems. MATERIAL AND METHODS: Three radiologists with respectively 3, 5 and 7 years of practice in mammogram reading in an Italian public hospital analysed a dataset composed of 120 digitized mammograms of healthy subjects with no lesion (proven by a radiological follow up of at least 3 years) and 70 images of patients with malignant cluster of microcalcification (proven by histopathological examination) both with no CAD support as well as with the help of the SecondLooktrade mark system. After 3 months they were asked to observe the same digitized mammograms with the assistance of the CALMA system. The radiologists worked independently and were unaware of the final diagnosis. The values of the area A(z) under the ROC curve, diagnostic sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were evaluated with and without the support of the CAD systems. The reading time and qualitative evaluations of each radiologist were also reported. RESULTS: With the support of the two CAD systems an improvement in A(z) area was obtained ranging from 0.01 to 0.04. Sensitivity increased from +8.6 to +15.7% and specificity decreased from 0.8 to 4.2%. CONCLUSION: In our study, not conditioned by the dataset, the CAD systems as second reader produced an increase in overall sensitivity of up to 15.7%, with a little decrease in specificity of up to 4.2%. Based on these results both CAD systems might be used in the current practise to improve the sensitivity values of conventional reading (radiologist alone). The results of this study show that no significant differences exist in term of A(z), sensitivity and specificity between CALMA and CADx.

Breast Diseases↗