Paper Info
Title
Multi-level analysis and information extraction considerations for validating 4D models of human function
Abstract
Recent research trends focus on how multiscale biomedical information can be modeled and transformed into knowledge, in order to lead to a less interfering but also more individualized diagnosis and therapy. In order to assess the clinical importance of models of human pathology (e.g. cancer), it is necessary to validate them with prior and post treatment clinical data which in turn requires the determination of the tumor size and shape with high resolution, accuracy and precision, as well as structural and physiological information. This paper discusses some of the most important image analysis challenges in order to define an optimal method for extracting more accurate and precise anatomical and functional information related to the underlying pathology, which can be used for initializing and validating models of pathophysiology as well as simulations/predictions of the response to therapeutical regimes.
Year
DOI
Venue
2007
10.1007/978-3-540-73321-8_81
HCI (12)
Keywords
Field
DocType
underlying pathology,information extraction consideration,functional information,high resolution,human function,post treatment clinical data,multi-level analysis,multiscale biomedical information,important image analysis challenge,physiological information,human pathology,clinical importance,individualized diagnosis,modeling,information extraction,image analysis,virtual physiological human
Human Pathology,Data mining,Computer science,Virtual Physiological Human,Information extraction,Initialization
Conference
Volume
ISSN
Citations 
4561
0302-9743
1
PageRank 
References 
Authors
0.38
7
8
Name
Order
Citations
PageRank
Kostas Marias113428.80
Dimitra D. Dionysiou2286.05
Georgios S. Stamatakos33310.84
Fotini Zacharopoulou410.38
Eleni Ch. Georgiadi581.90
Thanasis Margaritis661.60
Thomas G. Maris743.97
Ioannis G. Tollis81240162.75