000 04122nam a22005055i 4500
001 978-1-4614-7245-2
003 DE-He213
005 20200421112038.0
007 cr nn 008mamaa
008 131115s2014 xxu| s |||| 0|eng d
020 _a9781461472452
_9978-1-4614-7245-2
024 7 _a10.1007/978-1-4614-7245-2
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aComputational Intelligence in Biomedical Imaging
_h[electronic resource] /
_cedited by Kenji Suzuki.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aXV, 406 p. 209 illus., 114 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _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.
520 _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.
650 0 _aEngineering.
650 0 _aRadiology.
650 0 _aComputer graphics.
650 0 _aComputational intelligence.
650 0 _aBiomedical engineering.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aBiomedical Engineering.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
650 2 4 _aSignal, Image and Speech Processing.
650 2 4 _aImaging / Radiology.
700 1 _aSuzuki, Kenji.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461472445
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-7245-2
912 _aZDB-2-ENG
942 _cEBK
999 _c56474
_d56474