Fuzzy technique for microcalcifications clustering in digital mammograms

Background Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer Aided Detection (CAD) systems could turn out to be very useful in breast cancer control. Methods In this paper we present a potentially powerful microcalcifications cluster enhancement method applicable to digital mammograms. The segmentation phase employs a form filter, obtained from LoG filter, to overcome the dependence from target dimensions and to optimize the recognition efficiency. A clustering method, based on a Fuzzy C-means (FCM), has been developed. The described method, Fuzzy C-means with Features (FCM-WF), was tested on simulated clusters of microcalcifications, implying that the location of the cluster within the breast and the exact number of microcalcifications are known.The proposed method has been also tested on a set of images from the mini-Mammographic database provided by Mammographic Image Analysis Society (MIAS) publicly available. Results The comparison between FCM-WF and standard FCM algorithms, applied on both databases, shows that the former produces better microcalcifications associations for clustering than the latter: with respect to the private and the public database we had a performance improvement of 10% and 5% with regard to the Merit Figure and a 22% and a 10% of reduction of false positives potentially identified in the images, both to the benefit of the FCM-WF. The method was also evaluated in terms of Sensitivity (93% and 82%), Accuracy (95% and 94%), FP/image (4% for both database) and Precision (62% and 65%). Conclusions Thanks to the private database and to the informations contained in it regarding every single microcalcification, we tested the developed clustering method with great accuracy. In particular we verified that 70% of the injected clusters of the private database remained unaffected if the reconstruction is performed with the FCM-WF. Testing the method on the MIAS databases allowed also to verify the segmentation properties of the algorithm, showing that 80% of pathological clusters remained unaffected

A Fuzzy Logic C-Means Clustering Algorithm to Enhance Microcalcifications Clusters in Digital Mammograms

The detection of microcalcifications is a hard task, since they are quite small and often poorly contrasted against the background of images. The Computer Aided Detection (CAD) systems could be very useful for breast cancer control. In this paper, we report a method to enhance microcalcifications cluster in digital mammograms. A Fuzzy Logic clustering algorithm with a set of features is used for clustering microcalcifications. The method described was tested on simulated clusters of microcalcifications, so that the location of the cluster within the breast and the exact number of microcalcifications is known

Surgical treatment of chronic acromioclavicular dislocation with biologic graft vs synthetic ligament: A prospective randomized comparative study

Background: Acromioclavicular (AC) dislocation involves complete loss of articular contact; it is defined as chronic when it follows conservative management or unsuccessful surgical treatment. Materials and methods: The study compared the clinical and radiographic outcomes of AC joint stabilization performed in 40 patients with chronic dislocation using a biological allograft (group A) or a synthetic ligament (group B). Demographic data included: M/F: 25/15; mean age: 35 ± 3.2 years; previous surgery in 11 patients, including Weaver-Dunn (3), coracoacromial ligament repair (4), stabilization with K-wires (4). Dislocation was type III in 14 (35 %) and type IV in 26 (65 %) patients. Clinical assessment was with the Constant-Murley score (pre- and postoperative) and with the modified UCLA score. Enrollment started in January 2004 and was completed in March 2008. Patients were evaluated at 1 and 4 years. Postoperative X-rays were examined to assess joint stability in the coronal and axial planes, coracoclavicular ossification, and signs of AC joint osteoarthritis and distal clavicular osteolysis. Results: The "biological" group achieved significantly better clinical scores than the "synthetic" group at both 1 and 4 years. Poor subjective satisfaction and lower clinical scores were found in the 3 patients (1 from group A and 2 from group B) who experienced complete postoperative dislocation. No significant correlations were found with other radiographic parameters. Conclusions: The biological graft afforded better clinical and radiographic outcomes than the synthetic ligament in patients with chronic AC joint instability. Fixation to the clavicle constitutes the main weakness of both approaches and needs improving. © 2012 The Author(s)

Automatic detection of lung nodules in CT datasets based on stable 3D mass–spring models

We propose a computer-aided detection (CAD) system which can detect small-sized (from 3 mm) pulmonary nodules in spiral CT scans. A pulmonary nodule is a small lesion in the lungs, round-shaped (parenchymal nodule) or worm-shaped (juxtapleural nodule). Both kinds of lesions have a radio-density greater than lung parenchyma, thus appearing white on the images. Lung nodules might indicate a lung cancer and their early stage detection arguably improves the patient survival rate. CT is considered to be the most accurate imaging modality for nodule detection. However, the large amount of data per examination makes the full analysis difficult, leading to omission of nodules by the radiologist. We developed an advanced computerized method for the automatic detection of internal and juxtapleural nodules on low-dose and thin-slice lung CT scan. This method consists of an initial selection of nodule candidates list, the segmentation of each candidate nodule and the classification of the features computed for each segmented nodule candidate.The presented CAD system is aimed to reduce the number of omissions and to decrease the radiologist scan examination time. Our system locates with the same scheme both internal and juxtapleural nodules. For a correct volume segmentation of the lung parenchyma, the system uses a Region Growing (RG) algorithm and an opening process for including the juxtapleural nodules. The segmentation and the extraction of the suspected nodular lesions from CT images by a lung CAD system constitutes a hard task. In order to solve this key problem, we use a new Stable 3D Mass–Spring Model (MSM) combined with a spline curves reconstruction process. Our model represents concurrently the characteristic gray value range, the directed contour information as well as shape knowledge, which leads to a much more robust and efficient segmentation process. For distinguishing the real nodules among nodule candidates, an additional classification step is applied; furthermore, a neural network is applied to reduce the false positives (FPs) after a double-threshold cut. The system performance was tested on a set of 84 scans made available by the Lung Image Database Consortium (LIDC) annotated by four expert radiologists. The detection rate of the system is 97% with 6.1 FPs/CT. A reduction to 2.5 FPs/CT is achieved at 88% sensitivity. We presented a new 3D segmentation technique for lung nodules in CT datasets, using deformable MSMs. The result is a efficient segmentation process able to converge, identifying the shape of the generic ROI, after a few iterations. Our suitable results show that the use of the 3D AC model and the feature analysis based FPs reduction process constitutes an accurate approach to the segmentation and the classification of lung nodules

Health literacy in Mediterranean general population

INTRODUCTION Health literacy refers to "the ability to obtain, process, and understand basic health information and access health services in order to make informed choices." In essence, being able to acquire, understand, and use information for one's own health. METHODS Observational study through the administration of a face-to-face questionnaire conducted between July and September 2020 on 260 individuals residing between Calabria and Sicily, aged between 18 and 89 years. Questions related to education, lifestyle (alcohol, smoking, and physical activity). Multiple-choice questions to assess health literacy and conceptual skills, ability to find information on health topics and services, use of preventive medicine especially vaccinations, and ability to make decisions about one's own health. RESULTS Of 260, 43% were male and 57% female. The most represented age group is between 50 and 59 years. Forty-eight percent of respondents had a high school diploma. 39% smoke and 32% habitually consume alcoholic beverages; only 40% engage in physical activity. Ten percent had a low level of health literacy, average 55%, adequate 35%. CONCLUSIONS Given the importance of adequate HL on health choices and on individual and public wellbeing, it is essential to expand the knowledge of the individual, through public and private information campaigns and with an increasing involvement of family physicians, who are fundamental in training and informing their patients

HEp-2 Cell Classification with heterogeneous classes-processes based on K-Nearest Neighbours

We present a scheme for the feature extraction and classification of the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary processes specific to each class of patterns to search. Our set of processes consists of preprocessing,features extraction and classification. The choice of methods, features and parameters was performed automatically, using the Mean Class Accuracy (MCA) as a figure of merit. We extract a large number (108) of features able to fully characterize the staining pattern of HEp-2 cells. We propose a classification approach based on two steps: the first step follows the one-against-all(OAA) scheme, while the second step follows the one-against-one (OAO) scheme. To do this, we needed to implement 21 KNN classifiers: 6 OAA and 15 OAO. Leave-one-out image cross validation method was used for the evaluation of the 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

An evaluation of gambling addiction and video lottery in the South of Italy

Nowadays, pathological gambling is an emerging health problem. The Diagnostic and Statistical Manual of Mental Disorders 5 (DSM 5) renames it as 'Gambling Disorder' (GD), thus recognising its highly dependent status. A study was conducted from April 2016 to August 2017 to evaluate the prevalence of this phenomenon by administering an ad hoc questionnaire to adult individuals (both sexes) over the age of 18.  We analysed a sample of 562 individuals with DSM 5 criteria. We obtained a score > 4 indicating a possible mild gambling disorder in 1.6% of the sample and a score > 6 corresponding to a moderate GD in 2.3% of the sample. We observed that the main motivations for gambling were “having fun” and “the prospect of winning” and 10.9% of respondents had played more than they intended. Furthermore, "problematic" players showed to be more prone to alcohol abuse than "social" players (p < 0.001). Only 7.5% of respondents had already gambling problems in their family (involving in particular their mothers). The phenomenon is, therefore, quite common in our area and, indeed, 64.1% of the sample believes that gambling is a problem in their own territory, however only 20.6% would know where to find help. In conclusion, given the high socio-economic impact of this phenomenon, we believe that it is imperative to establish structured preventions programs in order to to contain the spread of this phenomenon.  Key words

Vaccination coverage in healthcare workers: a multicenter cross-sectional study in Italy

IntroductionIn recent years, a phenomenon known as "vaccine hesitancy" has spread throughout the world, even among health workers, determining a reduction in vaccination coverage (VC). A study aimed at evaluating VC among healthcare workers (HCWs) in 10 Italian cities (L'Aquila, Genoa, Milan, Palermo, Sassari, Catanzaro, Ferrara, Catania, Naples, Messina) was performed.Materials and methodsAnnex 3 of the Presidential Decree n. 445 of 28 December 2000 was used to collect information on the vaccination status of HCWs. The mean and standard deviation (SD) were calculated with regard to the quantitative variable (age), while absolute and relative frequencies were obtained for categorical data (sex, professional profile, working sector, vaccination status). The connection between VC and the categorical variables was evaluated by chi-square method (statistical significance at p<0.05). The statistical analyses were performed by SPSS and Stata software.ResultsA total of 3,454 HCWs participated in the project: 1,236 males and 2,218 females. The sample comprised: physicians (26.9%), trainee physicians (16.1%), nurses (17.2%) and other professional categories (9.8%). Low VC was generally recorded. Higher VC was found with regard to polio, hepatitis B, tetanus and diphtheria, while coverage was very low for measles, mumps, rubella, pertussis, chickenpox and influenza (20-30%). ConclusionsThis study revealed low VC rates among HCWs for all the vaccinations. Measures to increase VC are therefore necessary in order to prevent HCWs from becoming a source of transmission of infections with high morbidity and/or mortality both within hospitals and outside

Recent results on heavy-ion induced reactions of interest for neutrinoless double beta decay at INFN-LNS

Abstract. The possibility to use a special class of heavy-ion induced direct reactions, such as double charge exchange reactions, is discussed in view of their application to extract information that may be helpful to determinate the nuclear matrix elements entering in the expression of neutrinoless double beta decay halflife. The methodology of the experimental campaign presently running at INFN - Laboratori Nazionali del Sud is reported and the experimental challenges characterizing such activity are describe