Machine Learning and Medical Imaging

Nonfiction, Computers, Application Software, Business Software, General Computing
Cover of the book Machine Learning and Medical Imaging by , Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9780128041147
Publisher: Elsevier Science Publication: August 11, 2016
Imprint: Academic Press Language: English
Author:
ISBN: 9780128041147
Publisher: Elsevier Science
Publication: August 11, 2016
Imprint: Academic Press
Language: English

Machine 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 problems
  • Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics
  • Features self-contained chapters with a thorough literature review
  • Assesses the development of future machine learning techniques and the further application of existing techniques
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Machine 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.

More books from Elsevier Science

Cover of the book Gene Therapy of the Central Nervous System: From Bench to Bedside by
Cover of the book Development of Pedotransfer Functions in Soil Hydrology by
Cover of the book Advances in Inorganic Chemistry by
Cover of the book Engineered Nanoparticles by
Cover of the book Malware Forensics by
Cover of the book How to Cheat at Securing SQL Server 2005 by
Cover of the book Handbook of Thin Film Deposition by
Cover of the book Nanocarriers for Cancer Diagnosis and Targeted Chemotherapy by
Cover of the book Concerning Amines by
Cover of the book The Mitochondrion in Aging and Disease by
Cover of the book Advances in Heterocyclic Chemistry by
Cover of the book Advances in Clean Hydrocarbon Fuel Processing by
Cover of the book The Art of Investigative Interviewing by
Cover of the book Driving Climate Change by
Cover of the book Basic AC Circuits by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy