LEVEL SET METHOD IN MEDICAL IMAGING SEGMENTATION (HB 2019). Este artículo no está disponible.
Idioma: inglés
Editorial: TAYLOR & FRANCIS, 2019
- Tapa dura
- Nuevo

Librería: UK BOOKS STORE, London, London, Reino UnidoUK BOOKS STORE
Vendedor de IberLibro desde 11 de marzo de 2024
Condición: Nuevo
EUR 472,31
Descripción del artículo del vendedor
Brand New ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
N° de ref. del artículo Cvs 9781138553453
- Título
- LEVEL SET METHOD IN MEDICAL IMAGING SEGMENTATION (HB 2019)
- Autor
- BAZ A E
- Editorial
- TAYLOR & FRANCIS
- Año de publicación
- 2019
- Estado
- New
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 113855345X
- ISBN 13
- 9781138553453
- Edición
- Edición Internacional
Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Ayman El-Baz is a University Scholar and Chair, Bioengineering Department at the University of Louisville, KY. He has over 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnostic systems. He has developed new techniques for the accurate identification of probability mixtures for segmenting multi-modal images, new probability models, and model-based algorithms for recognizing lung nodules and blood vessels in magnetic resonance and computer tomography imaging systems, as well as new registration techniques based on multiple second-order signal statistics, all of which have been reported at multiple international conferences and journal articles. His work related to novel image analysis techniques for autism, dyslexia, and lung cancer has earned multiple awards including the Walter H. Coulter Foundation Early Career in Biomedical Engineering and a Research Scholar Grant from the American Cancer Society. He has authored or coauthored more than 300 technical articles (87 journals, 9 books, 39 book chapters, 144 refereed-conference papers, 74 abstracts published in proceedings and 12 US patents).
Jasjit S. Suri is Chairman of Global Biomedical Technologies, Inc. Roseville, CA. He has spent over 30 years in the fields of biomedical engineering/sciences, software and hardware engineering and its management. He has developed products and worked extensively in the areas of breast, mammography, orthopedics (spine), neurology (brain), angiography, urology and image guided surgery. Dr. Suri has over 100 US/European Patents, 20 Trademarks, 35 books and over 550 peer reviewed articles. He is a Fellow of AIMBE (American Institute of Medical and Biological Engineering).
“Acerca de” puede pertenecer a otra edición de este título.