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. Ed(S): El-Baz, Ayman; Acharya U., Rajendra; Mirmehdi, Majid; Suri, Jasjit - Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies - 9781441981943 - V9781441981943
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Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies

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Description for Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies Hardback. Advances in image-guided cancer surgery have enlarged the role of image segmentation and registration. This book reviews current methodologies, to help physicians delineate anatomical structures, enhance the accuracy of diagnosis and improve treatment planning. Editor(s): El-Baz, Ayman; Acharya U., Rajendra; Mirmehdi, Majid; Suri, Jasjit. Num Pages: 410 pages, 20 black & white tables, biography. BIC Classification: MBGR; MJCL; MMP; MQW; UG. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 23. Weight in Grams: 839.
With 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 ... Read more

Product Details

Format
Hardback
Publication date
2011
Publisher
Springer-Verlag New York Inc. United States
Number of pages
410
Condition
New
Number of Pages
410
Place of Publication
New York, NY, United States
ISBN
9781441981943
SKU
V9781441981943
Shipping Time
Usually ships in 5 to 9 working days
Ref
99-4

About . Ed(S): El-Baz, Ayman; Acharya U., Rajendra; Mirmehdi, Majid; Suri, Jasjit
Ayman S. El-Baz is currently assistant professor of Bioengineering in the Department of Bioengineering at the University of Louisville (UofL). Dr. El-Baz is an expert in the fields of bioimaging modeling and computer assisted diagnosis systems. Dr. El-Baz has extensive experience in automated detection, segmentation, and diagnosis of lung nodules in LDCT images. Dr. El-Baz received his Doctorate from University ... Read more

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