La scoperta dei raggi X e del fenomeno della radioattività e le loro ricadute sul mondo medico

La scoperta dei raggi X da parte di Wilhelm Conrad Röntgen avvenuta l'8 Novembre 1895 è una pietra miliare non solo per la fisica nucleare, ma segna anche l'inizio della nuova disciplina medica della radiologia diagnostica e della radioterapia. In questo articolo, si descrive come Röntgen arrivò alla scoperta dei raggi X e come dopo pochi anni Henri Becquerel ed i coniugi Curie arrivarono a scoprire e a studiare il fenomeno della radioattività, che rappresenta il fondamento della Medicina Nucleare. Segue quindi una breve descrizione delle maggiori tecniche diagnostiche e terapeutiche che derivano da queste scoperte, che sono presentate in dettaglio in altri articoli di questo volume. Infine, si introduce la disciplina della Radioprotezione, che permette un utilizzo ottimale delle radiazioni ionizzanti in campo medico, limitandone i rischi associati

A robustness verification system for mobile phone authentication based on gestures using Linear Discriminant Analysis

This article evaluates an authentication technique for mobiles based on gestures. Users create a remindful identifying gesture to be considered as their in-air signature. This work analyzes a database of 120 gestures of different vulnerability, obtaining an Equal Error Rate (EER) of 9.19% when robustness of gestures is not verified. Most of the errors in this EER come from very simple and easily forgeable gestures that should be discarded at enrollment phase. Therefore, an in-air signature robustness verification system using Linear Discriminant Analysis is proposed to infer automatically whether the gesture is secure or not. Different configurations have been tested obtaining a lowest EER of 4.01% when 45.02% of gestures were discarded, and an optimal compromise of EER of 4.82% when 19.19% of gestures were automatically rejected

Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performanc

Silicon Photomultipliers (SiPM) as novel photodetectors for PET

Next generation PET scanners should fulfill very high requirements in terms of spatial, energy and timing resolution. Modern scanner performances are inherently limited by the use of standard photomultiplier tubes. The use of Silicon Photomultipliers (SiPMs) is proposed for the construction of a 4D-PET module of 4.8×4.8 cm2 aimed to replace the standard PMT based PET block detector. The module will be based on a LYSO continuous crystal read on two faces by Silicon Photomultipliers. A high granularity detection surface made by SiPM matrices of 1.5 mm pitch will be used for the x–y photon hit position determination with submillimetric accuracy, while a low granularity surface constituted by 16 mm2 SiPM pixels will provide the fast timing information (t) that will be used to implement the Time of Flight technique (TOF). The spatial information collected by the two detector layers will be combined in order to measure the Depth of Interaction (DOI) of each event (z). The use of large area multi-pixel Silicon Photomultiplier (SiPM) detectors requires the development of a multichannel Data Acquisition system (DAQ) as well as of a dedicated front-end in order not to degrade the intrinsic detector capabilities and to manage many channels. The paper describes the progress made on the development of the proof of principle module under construction at the University of Pisa

Advanced radiation measurement techniques in diagnostic radiology and molecular imaging.

This paper reports some technological advances recently achieved in the fields of micro-CT and small animal PET instrumentation. It highlights a balance between image-quality improvement and dose reduction. Most of the recent accomplishments in these fields are due to the use of novel imaging sensors such as CMOS-based X-ray detectors and silicon photomultipliers (SiPM). Some of the research projects carried out at the University of Pisa for the development of such advanced radiation imaging technology are also described

Cherenkov luminescence measurements with digital silicon photomultipliers: a feasibility study.

BackgroundA feasibility study was done to assess the capability of digital silicon photomultipliers to measure the Cherenkov luminescence emitted by a β source. Cherenkov luminescence imaging (CLI) is possible with a charge coupled device (CCD) based technology, but a stand-alone technique for quantitative activity measurements based on Cherenkov luminescence has not yet been developed. Silicon photomultipliers (SiPMs) are photon counting devices with a fast impulse response and can potentially be used to quantify β-emitting radiotracer distributions by CLI.MethodsIn this study, a Philips digital photon counting (PDPC) silicon photomultiplier detector was evaluated for measuring Cherenkov luminescence. The PDPC detector is a matrix of avalanche photodiodes, which were read one at a time in a dark count map (DCM) measurement mode (much like a CCD). This reduces the device active area but allows the information from a single avalanche photodiode to be preserved, which is not possible with analog SiPMs. An algorithm to reject the noisiest photodiodes and to correct the measured count rate for the dark current was developed.ResultsThe results show that, in DCM mode and at (10-13) °C, the PDPC has a dynamic response to different levels of Cherenkov luminescence emitted by a β source and transmitted through an opaque medium. This suggests the potential for this approach to provide quantitative activity measurements. Interestingly, the potential use of the PDPC in DCM mode for direct imaging of Cherenkov luminescence, as a opposed to a scalar measurement device, was also apparent.ConclusionsWe showed that a PDPC tile in DCM mode is able to detect and image a β source through its Cherenkov radiation emission. The detector's dynamic response to different levels of radiation suggests its potential quantitative capabilities, and the DCM mode allows imaging with a better spatial resolution than the conventional event-triggered mode. Finally, the same acquisition procedure and data processing could be employed also for other low light levels applications, such as bioluminescence

A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications

Authentication in mobile devices through hand gesture recognition

This article proposes an innovative biometric technique based on the idea of authenticating a person on a mobile device by gesture recognition. To accomplish this aim, a user is prompted to be recognized by a gesture he/she performs moving his/her hand while holding a mobile device with an accelerometer embedded. As users are not able to repeat a gesture exactly in the air, an algorithm based on sequence alignment is developed to correct slight differences between repetitions of the same gesture. The robustness of this biometric technique has been studied within 2 different tests analyzing a database of 100 users with real falsifications. Equal Error Rates of 2.01 and 4.82% have been obtained in a zero-effort and an active impostor attack, respectively. A permanence evaluation is also presented from the analysis of the repetition of the gestures of 25 users in 10 sessions over a month. Furthermore, two different gesture databases have been developed: one made up of 100 genuine identifying 3-D hand gestures and 3 impostors trying to falsify each of them and another with 25 volunteers repeating their identifying 3- D hand gesture in 10 sessions over a month. These databases are the most extensive in published studies, to the best of our knowledge