{"id":234,"date":"2016-03-24T10:37:22","date_gmt":"2016-03-24T09:37:22","guid":{"rendered":"http:\/\/www.imagenglab.com\/newsite\/?page_id=234"},"modified":"2016-10-23T16:27:20","modified_gmt":"2016-10-23T14:27:20","slug":"alumni","status":"publish","type":"page","link":"https:\/\/www.imagenglab.com\/newsite\/education\/alumni\/","title":{"rendered":"Alumni"},"content":{"rendered":"

 <\/p>\n

A.A. 2014\/2015<\/strong><\/em><\/span><\/p>\n

\"restuccia\"\u00a0Marzia Restuccia
\nBeing awarded with an Erasmus Placement travel grant, Marzia spent 3 months at CIBM (C\u00e8ntre d’Imagerie Biomedicale) in Lausanne (Switzerland). There, she learnt fMRI techniques, taking part in experimental acquisitions on phantoms and voluntary subjects. She continued her\u00a0work and her BSc work focusing on the optimization of strategies for fMRI data acquisition and analysis such as: investigation on best flip angle, data preprocessing for calculation of activation maps, compensation of breathing and heartbeat artifacts.<\/p>\n

 <\/p>\n

\"2014-12-09_19.06.34\"\u00a0 Vincenzo Grillo
\nVincenzo was selected for an external internship in the framework of the project \u201cMessaggeri della Conoscenza\u201d. He spent two months at Massachusetts General Hospital \u2013 Harvard Medical School in Boston (MA, USA) where he was involved in the generation of a synthetic phantom to be used for dose calculation purpose. He discussed\u00a0his BSc thesis by generating proton radiography projections from the phantom for dose modelling with Geant4.<\/p>\n

 <\/p>\n

\"limardi.resized_77\"\u00a0 Davide Limardi<\/p>\n

During his BSc thesis @imagenglab he investigated a new approach for atlas selection in MABS applications. The technique relies on features detection on CT images based on morphology in the Head and Neck district.<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

  A.A. 2014\/2015 \u00a0Marzia Restuccia Being awarded with an Erasmus Placement travel grant, Marzia spent 3 months at CIBM (C\u00e8ntre d’Imagerie Biomedicale) in Lausanne (Switzerland). There, she learnt fMRI techniques, taking part in experimental acquisitions on phantoms and voluntary subjects. She continued her\u00a0work and her BSc work focusing on the optimization of strategies for fMRI Read more about Alumni<\/span>[…]<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":39,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"spay_email":""},"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/P9htfR-3M","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":249,"url":"https:\/\/www.imagenglab.com\/newsite\/education\/thesis\/","url_meta":{"origin":234,"position":0},"title":"Thesis","date":"24 March 2016","format":false,"excerpt":"Imagenglab provides host and facilities to MSc and BSc students who\u00a0want to work on one of the following topics: \u00a0 Influence of Image Compression Algorithms on Computer Vision Detectors and Descriptors Performances. Prerequisites: basic python knowledge. Data Mining Approach to define new Maintenance Prioritization Index for Medical Equipment . \u00a0\u2026","rel":"","context":"Similar post","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":331,"url":"https:\/\/www.imagenglab.com\/newsite\/mf_spadea\/","url_meta":{"origin":234,"position":1},"title":"Maria Francesca Spadea","date":"17 April 2016","format":false,"excerpt":"Contact: mfspadea at imagenglab.com Sketch\u00a0bio: Maria Francesca Spadea graduated in 2002 in Mechanical Engineer at University of Calabria and she received a PhD degree in Biomedical Engineer in 2006 from Politecnico di Milano University. Since 2007, she has been Assistant Professor at the Department of Experimental and Clinical Medicine of\u2026","rel":"","context":"Similar post","img":{"alt_text":"","src":"https:\/\/i1.wp.com\/www.imagenglab.com\/newsite\/wp-content\/uploads\/2016\/04\/Screen-Shot-2016-10-11-at-12.07.52.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":302,"url":"https:\/\/www.imagenglab.com\/newsite\/salvatore_scaramuzzino\/","url_meta":{"origin":234,"position":2},"title":"Salvatore Scaramuzzino","date":"16 April 2016","format":false,"excerpt":"download contact vCard \u00a0 Sketch\u00a0bio: As an engineer, Salvatore likes to work with numbers, since they give him confidence. But he is also attracted by images, numerical images (of course!), because of the expressive power and the density of information that an image can include. He thinks that medical imaging\u2026","rel":"","context":"Similar post","img":{"alt_text":"","src":"https:\/\/i2.wp.com\/www.imagenglab.com\/newsite\/wp-content\/uploads\/2016\/03\/18305918213_3f0c99f374_o-e1457692904280-293x300.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":184,"url":"https:\/\/www.imagenglab.com\/newsite\/pddca\/","url_meta":{"origin":234,"position":3},"title":"PDDCA","date":"15 March 2016","format":false,"excerpt":"PDDCA A Public Domain Database for Computational Anatomy version 1.4.1 This database is provided and maintained by Dr. Gregory C Sharp (Harvard Medical School - MGH, Boston) and his group. The data here provided have been used for the \"Head and Neck Auto Segmentation MICCAI Challenge (2015)\". To cite the\u2026","rel":"","context":"Similar post","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":100,"url":"https:\/\/www.imagenglab.com\/newsite\/research\/mabs\/","url_meta":{"origin":234,"position":4},"title":"MABS","date":"14 March 2016","format":false,"excerpt":"Multi Atlas Based Segmentation In collaboration with Dr. Gregory C. Sharp, Radiation Oncology Department, Massachusetts General Hospital - Harvard Medical School, Boston, USA. Dr. Karl Fritscher,\u00a0Department for Biomedical Image Analysis, UMIT, Austria. Multi Atlas Based Segmentation (MABS) is a methodology for automatic image segmentation that\u00a0is proving to be able to\u2026","rel":"","context":"Similar post","img":{"alt_text":"MABS2","src":"https:\/\/i1.wp.com\/www.imagenglab.com\/newsite\/wp-content\/uploads\/2016\/03\/MABS2.png?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":84,"url":"https:\/\/www.imagenglab.com\/newsite\/startup\/sphere\/","url_meta":{"origin":234,"position":5},"title":"SPHERE","date":"11 March 2016","format":false,"excerpt":"\u00a0 \u00a0 \u00a0 SPHERE \u2013 Smart Pocket HEalth Record \u2013 is a new solution for remote patient monitoring (RPM). Current mobile devices for telemedicine require data connection (Wi-Fi or Bluetooth) in order to perform a routine test and send the collected measures to a healthcare professional in real-time. This increases\u2026","rel":"","context":"Similar post","img":{"alt_text":"sphere_matching","src":"https:\/\/i0.wp.com\/www.imagenglab.com\/newsite\/wp-content\/uploads\/2016\/03\/sphere_matching-300x199.jpg?resize=350%2C200","width":350,"height":200},"classes":[]}],"_links":{"self":[{"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/pages\/234"}],"collection":[{"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/comments?post=234"}],"version-history":[{"count":4,"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/pages\/234\/revisions"}],"predecessor-version":[{"id":570,"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/pages\/234\/revisions\/570"}],"up":[{"embeddable":true,"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/pages\/39"}],"wp:attachment":[{"href":"https:\/\/www.imagenglab.com\/newsite\/wp-json\/wp\/v2\/media?parent=234"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}