000			03612nam a22005055i 4500
001			978-1-4419-8195-0
003			DE-He213
005			20140220083727.0
007			cr nn 008mamaa
008			110504s2011 xxu| s |||| 0|eng d
020			_a9781441981950 _9978-1-4419-8195-0
024	7		_a10.1007/978-1-4419-8195-0 _2doi
050		4	_aR-RZ
072		7	_aMBGR _2bicssc
072		7	_aMED000000 _2bisacsh
082	0	4	_a610 _223
100	1		_aEl-Baz, Ayman S. _eeditor.
245	1	0	_aMulti Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies _h[electronic resource] : _bVolume 1 / _cedited by Ayman S. El-Baz, Rajendra Acharya U, Majid Mirmehdi, Jasjit S. Suri.
264		1	_aBoston, MA : _bSpringer US, _c2011.
300			_aXII, 410p. 222 illus., 97 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		_aIntegrating Shape and Texture in 3D Deformable Models: From Metamorphs to Active Volume Models -- Deformable Model-based Medical Image Segmentation -- Anisotropic Scale Selection, Robust Gaussian Fitting, and Pulmonary Nodule Segmentation in Chest CT Scans -- Computerized Segmentation of Organs by Means of Geodesic Active-Contour Level-Set Algorithm -- Segmentation of Skin Cancer Using External Force Filtering Snake Based on Wavelet Diffusion -- Density and Attachment Agnostic CT pulmonary Nodule Segmentation with Competition-diffusion and New Morphological Operators -- Accurate Modeling of Marginal Signal Distributions In 2d/3d Images -- Automated Ocular Localization in Thermographic Sequences of Contact Lens Wearer -- State-of-the-Art Medical Images Registration Methodologies: A Survey -- Registered 3D Tagged MRI and Ultrasound Myocardial Elastography: Quantitative Strain Comparison -- Unsupervised Change Detection in Multitemporal Images of the Human Retina -- Digital Topology in Brain Image Segmentation and Registration -- Computer-Based Identification of Diabetic Maculopathy Stages Using Fundus Images.
520			_aWith the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.
650		0	_aMedicine.
650		0	_aRadiology, Medical.
650		0	_aComputer vision.
650		0	_aBiomedical engineering.
650	1	4	_aBiomedicine.
650	2	4	_aBiomedicine general.
650	2	4	_aBiomedical Engineering.
650	2	4	_aImage Processing and Computer Vision.
650	2	4	_aImaging / Radiology.
700	1		_aAcharya U, Rajendra. _eeditor.
700	1		_aMirmehdi, Majid. _eeditor.
700	1		_aSuri, Jasjit S. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441981943
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4419-8195-0
912			_aZDB-2-SBL
999			_c105945 _d105945