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010   $a9783319948782
010   $a3319948784
024 7 $a10.1007/978-3-319-94878-2
035   $a(OCoLC)1084756745
035   $a(MiFhGG)GVRL59N5
035   $a(CKB)4100000007598223
035   $a(MiAaPQ)EBC5654958
035   $a(MiFhGG)9783319948782
035   $a(DE-He213)978-3-319-94878-2
035   $a(EXLCZ)994100000007598223
100   $a20190129d2019      u|         0
101 0 $aeng
135   $aurun#---uuuua
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aArtificial Intelligence in Medical Imaging $eOpportunities, Applications and Risks /$fedited by Erik R. Ranschaert, Sergey Morozov, Paul R. Algra
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (xv, 373 pages) $cillustrations (chiefly color), charts
225 0 $aGale eBooks
311 08$a9783319948775 
311 08$a3319948776 
320   $aIncludes bibliographical references and index.
327   $aPART I: INTRODUCTION: Introduction: Game changers in radiology -- PART II: TECHNIQUES: The role of medical imaging computing, informatics and machine learning in healthcare -- History and evolution of A.I. in medical imaging -- Deep Learning and Neural Networks in imaging: basic principles -- PART III DEVELOPMENT of AI APPLICATIONS: Imaging biomarkers -- How to develop A.I. applications -- Validation of A.I. applications -- PART IV: BIG DATA IN RADIOLOGY: The value of enterprise imaging -- Data mining in radiology -- Image biobanks -- The quest for medical images and data -- Clearance of medical images and data -- Legal and ethical issues in AI -- PART V: CLINICAL USE OF A.I. IN RADIOLOGY: Pulmonary diseases -- Cardiac diseases -- Breast cancer -- Neurological diseases -- PART VI: IMPACT of A.I. on RADIOLOGY: Applications of A.I. beyond image analysis -- Value of structured reporting for A.I. -- The role of A.I. for clinical trials -- Market and economy of A.I.: evolution -- The role of an A.I. ecosystem for radiology -- Advantages and risks of A.I. for radiologists -- Re-thinking radiology.
330   $aThis book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implicationsfor radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
606   $aRadiology
606   $aComputer networks
606   $aMedical informatics
606   $aRadiology
606   $aComputer Communication Networks
606   $aHealth Informatics
615  0$aRadiology.
615  0$aComputer networks.
615  0$aMedical informatics.
615 14$aRadiology.
615 24$aComputer Communication Networks.
615 24$aHealth Informatics.
676   $a616.0757
702   $aRanschaert$b Erik R.
702   $aMorozov$b S. P$g(Sergei? Pavlovich),
702   $aAlgra$b P. R.
801  0$bMiFhGG
801  1$bMiFhGG
906   $aBOOK
912   $a9910337534203321
996   $aArtificial Intelligence in Medical Imaging$91735009
997   $aUNINA