000			02256cam a2200277zu 4500
001			88835316
003			FRCYB88835316
005			20250107104138.0
006			m o d
007			cr un
008			250107s2016 fr | o|||||0|0|||eng d
020			_a9780128040768
035			_aFRCYB88835316
040			_aFR-PaCSA _ben _c _erda
100	1		_aWu, Guorong
245	0	1	_aMachine Learning and Medical Imaging _c['Wu, Guorong']
264		1	_bElsevier Science _c2016
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aWu, Guorong
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88835316 _qtext/html _a
520			_aMachine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.Demonstrates the application of cutting-edge machine learning techniques to medical imaging problemsCovers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomicsFeatures self-contained chapters with a thorough literature reviewAssesses the development of future machine learning techniques and the further application of existing techniques
999			_c14821 _d14821