1,722,019 research outputs found
Competition Authorities and political decisions
Full text linkThe jurisprudence has highlighted the constitutional implications of the competition enforcement, as a competence of the State prevailing over regional ones. However, the economic crisis and fears of out-control globalization have diminished the collective confidence in competition as a factor of economic growth. The Italian Competition Authority has been relegated back to the position of an ordinary administration by the Constitutional Court. Moreover, national governments aim to regain a leading role in crucial choices for economic development, e.g. regarding the control of mergers. At the same time, the debate on the goals of competition law has reopened, after a period of unchallenged domination of efficiency as a paradigm. More attention should be paid to the long-term consequences of the concentration of economic power, even if justified by productive efficiency and immediate benefits for consumers
Terapia dei fibromi con ultrasuoni e RMN (FUS)
No full textTitolo corso: “Attualità in ginecologia e ostetricia 2013”
Sede: Splendid Hotel La Torre - Palermo (PA)
Data: 8 Marzo 2013
Intervento: Terapia dei fibromi con ultrasuoni e RMN (FUS)
Relatore: Dott. Cesare Gagliard
Cystic lymphangioma of adrenal gland. Case report and review of the literature
Full text linkIl linfoangioma surrenalico cistico è una neoplasia beni-
gna rara che origina da una ectasia dei vasi linfatici; questa
lesione si localizza, più frequentemente, nella regione del collo,
ascellare e mediastinica.
Lo scopo di questo studio è descrivere il caso di una
donna di 60 anni con dolore addominale ricorrente che si è sot-
toposta ad un esame ecografico che ha mostrato la presenza di
una massa cistica in corrispondenza del polo superiore del
rene; quindi l’origine della massa, il surrene, è stata identificata
attraverso la Tomografia Compiuterizzata, eseguita con mezzo
di contrasto. Successivamente la paziente ha effettuato la
Risonanza Magnetica che ha meglio caratterizzato la lesione; la
Risonanza Magnetica ha suggerito la diagnosi di linfoangioma
cistico attraverso la diagnosi differenziale tra masse solide e
cistiche.Infine la diagnosi radiologica è stata confermata dalla
biopsiaCystic lymphangioma of adrenal gland (CL) is a rare benign neoplasm that begin from an ectasia of lynfatic vessel; this lesion is localized, most frequently, in neck, axillary and mediastinal region. The purpose of this study is to describe the case of a 60 years old patient with recurrent abdominal pain that underwent ultrasound scan that showed a cystic mass in upper renal pole; than the origin of the mass, the adrenal gland, was identify by Computer Tomography, performed using contrast material. Subsequently the patient underwent to Magnetic Resonance (MR) that better characterized the lesion; MR was enabled to suggest CL by differential diagnosis between solid and cystic mass of adrenal gland. Finally radiological diagnosis was confirmed from biopsy
A novel solution based on scale invariant feature transform descriptors and deep learning for the detection of suspicious regions in mammogram images.
Full text linkBackground: Deep learning methods have become popular for their high‑performance rate in the classification and detection of events in computer vision tasks. Transfer learning paradigm is widely adopted to apply pretrained convolutional neural network (CNN) on medical domains overcoming the problem of the scarcity of public datasets. Some investigations to assess transfer learning knowledge inference abilities in the context of mammogram screening and possible combinations with unsupervised techniques are in progress. Methods: We propose a novel technique for the detection of suspicious regions in mammograms that consist of the combination of two approaches based on scale invariant feature transform (SIFT) keypoints and transfer learning with pretrained CNNs such as PyramidNet and AlexNet fine‑tuned on digital mammograms generated by different mammography devices. Preprocessing, feature extraction, and selection steps characterize the SIFT‑based method, while the deep learning network validates the candidate suspicious regions detected by the SIFT method. Results: The experiments conducted on both mini‑MIAS dataset and our new public dataset Suspicious Region Detection on Mammogram from PP (SuReMaPP) of 384 digital mammograms exhibit high performances compared to several state‑of‑the‑art methods. Our solution reaches 98% of sensitivity and 90% of specificity on SuReMaPP and 94% of sensitivity and 91% of specificity on mini‑MIAS. Conclusions: The experimental sessions conducted so far prompt us to further investigate the powerfulness of transfer learning over different CNNs and possible combinations with unsupervised techniques. Transfer learning performances’ accuracy may decrease when the training and testing images come out from mammography devices with different properties
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