LEADER 01193nam0-22003371i-450- 001 990000039680403321 010 $a0-08-028388-8 035 $a000003968 035 $aFED01000003968 035 $a(Aleph)000003968FED01 035 $a000003968 100 $a20011111d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aSession on remote sensing 1980$eproceedings of the topical meeting of the COSPAR ISC C of the COSPAR twenty-thirdplenary meeting held in Budapest, 2-14 June 1980$fedited by A.B. Kahle (Session A1) G. Weill (Session A1) and W.D. Carter (Session A2). 210 $aOxford$cPergamon Press$d1981 215 $aVII, 314 p.$cill.$d24 cm 225 1 $aAdvances in space research$vVol. 1. n. 10 610 0 $aCongressi$aBudapest$a1980 610 0 $aRilevamento a distanza$aCongressi 676 $a621.367 702 1$aKahle,$bAnne B. 710 12$aCOSPAR PLENARY MEETING, 23., Budapest, 1980$0331751 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000039680403321 952 $a13 G 31 10$b32455$fFINBC 959 $aFINBC 996 $aSession on remote sensing 1980$9106259 997 $aUNINA DB $aING01 LEADER 01719nam 2200373 n 450 001 996392536303316 005 20200824121840.0 035 $a(CKB)4940000000107872 035 $a(EEBO)2240960222 035 $a(UnM)99862398e 035 $a(UnM)99862398 035 $a(EXLCZ)994940000000107872 100 $a19921028d1647 uh | 101 0 $aeng 135 $aurbn||||a|bb| 200 10$aHis Majesties most gratious ansvver at the delivery of the propositions for peace$b[electronic resource] $eCertified to the Parliament by a letter from the Earle of Pembrook, and the commissioners. Who presented them to the King on Tuesday last, at Hampton Court, Septemb. 7. 1647. Also His Majesties last propositions 210 $a[London $cs.n.]$dPrinted in the yeare, 1647 215 $a[2], 6 p 300 $aPlace of publication from Wing. 300 $aThe propositions referred to in the title are Charles I's of May 12, 1647; his answer is narrated on page 6, in "A letter from a gentleman at Hampton Court", which is dated at end: the 8. of Septemb. 1647. 300 $aAnnotation on Thomason copy: "7ber [i.e.September] 9th". 300 $aReproduction of the original in the British Library. 330 $aeebo-0018 607 $aGreat Britain$xHistory$yCivil War, 1642-1649$xPeace$vEarly works to 1800 701 $aPembroke$b Philip Herbert$cEarl of,$f1584-1650.$01002124 701 $aCharles$cKing of England,$f1600-1649.$0793295 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bWaOLN 906 $aBOOK 912 $a996392536303316 996 $aHis Majesties most gratious ansvver at the delivery of the propositions for peace$92374210 997 $aUNISA LEADER 03987oam 2200505 450 001 9910299741703321 005 20190911103512.0 010 $a1-4614-7245-8 024 7 $a10.1007/978-1-4614-7245-2 035 $a(OCoLC)866648058 035 $a(MiFhGG)GVRL6UQX 035 $a(EXLCZ)993710000000073381 100 $a20131022d2014 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 00$aComputational intelligence in biomedical imaging /$fKenji Suzuki, editor 205 $a1st ed. 2014. 210 1$aNew York :$cSpringer,$d2014. 215 $a1 online resource (xv, 406 pages) $cillustrations (some color) 225 0 $aGale eBooks 300 $aDescription based upon print version of record. 311 $a1-4614-7244-X 320 $aIncludes bibliographical references and index. 327 $aBrain Disease Classification and Progression using Machine Learning Techniques -- The Role of Content-Based Image Retrieval in Mammography CAD -- A Novel Image-based Approach for Early Detection of Prostate Cancer using DCE-MRI -- Computational Intelligent Image Analysis for Assisting Radiation Oncologists? Decision Making in Radiation Treatment Planning -- Computational Anatomy in the Abdomen: Automated Multi-Organ and Tumor Analysis from Computed Tomography -- Liver Volumetry in MRI by using Fast Marching Algorithm Coupled with 3D Geodesic Active Contour Segmentation -- Computer-aided Image Analysis for Vertebral Anatomy on X-ray CT Images -- Robust Segmentation of Challenging Lungs in CT using Multi-Stage Learning and Level Set Optimization -- Bone Suppression in Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined with Total Variation Minimization Smoothing and Consistency Processing -- Image Segmentation for Connectomics using Machine Learning -- Image Analysis Techniques for the Quantification of Brain Tumors on MR Images -- Respiratory and Cardiac Function Analysis on the Basis of Dynamic Chest Radiography -- Adaptive Noise Reduction and Edge Enhancement in Medical Images by using ICA -- Subtraction Techniques for CT and DSA and Automated Detection of Lung Nodules in 3D CT. 330 $aThis book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients? medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians? decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. 606 $aArtificial intelligence$xMedical applications 606 $aComputational intelligence 606 $aImaging systems in medicine 615 0$aArtificial intelligence$xMedical applications. 615 0$aComputational intelligence. 615 0$aImaging systems in medicine. 676 $a006.3 676 $a006.6 676 $a610.28 676 $a616.07/540285 702 $aSuzuki$b K$g(Kenji), 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910299741703321 996 $aComputational Intelligence in Biomedical Imaging$91979698 997 $aUNINA