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Medical imaging information system.
~
Rashed, Amira Ahmed Yassine.
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Medical imaging information system.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Medical imaging information system./
作者:
Rashed, Amira Ahmed Yassine.
面頁冊數:
73 p.
附註:
Adviser: Khaled A. Kamel.
Contained By:
Masters Abstracts International40-01.
標題:
Computer Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1405332
ISBN:
0493303006
Medical imaging information system.
Rashed, Amira Ahmed Yassine.
Medical imaging information system.
- 73 p.
Adviser: Khaled A. Kamel.
Thesis (M.S.)--University of Louisville, 2001.
In this thesis we provide a framework for a medical web based application. Therefore, we implement and apply optimized volume rendering algorithms based on exploitation of data coherence to reduce rendering times significantly.
ISBN: 0493303006Subjects--Topical Terms:
626642
Computer Science.
Medical imaging information system.
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In this thesis we provide a framework for a medical web based application. Therefore, we implement and apply optimized volume rendering algorithms based on exploitation of data coherence to reduce rendering times significantly.
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Biology and medicine rely fundamentally on anatomy. Not only do we need anatomical knowledge to understand normal and abnormal function; anatomy also provides a framework for organizing other kinds of biomedical data. Anatomy as a science studies the structures and spaces that make up the body, and the relationships among them. We can broadly classify representations of these entities and their relationships as either spatial or symbolic. Quantitative spatial information derives primarily from images and includes, for example, annotated images, 3D models, 3D scenes. Symbolic information, on the other hand, includes metadata about the images and 3D models (file names, date of digitization, and so on).
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Volume rendering techniques are used for interpretation and visualization of three-dimensional scalar data sets that have been generated by medical imaging and by numerical simulation and modeling of physical, chemical and biological phenomena. Recent improvements in medical image data generation and acquisition techniques have resulted in large data sets that have to be processed for diagnostic and therapeutic purposes, but its use has been limited by its high computational expense.
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