Autor/Autorin: Sjöstrand Karl
Karl Sjöstrand recieved his Ph.D. degree in MathematicalnModelling from the Technical University of Denmark in 2007 andnhis master of science degree in computer systems engineering fromnthe Technical Faculty at the University of Lund, Sweden, in 2003.
This book presents the development and application ofregularized statistical methods for the analysis ofanatomical structures. One of the comprehensive goalsof this type of research is to use non-invasivemedical imaging devices for the detection of diseaseswhich are otherwise difficult to diagnose at an earlystage. Statistics represents a quintessential part ofsuch investigations as they are preluded by aclinical hypothesis that must be verified based onobserved data. The massive amounts of image dataproduced in each examination pose an important andinteresting statistical challenge, in that there aremany more image features (variables) than subjects(observations), making an infinite number ofsolutions possible. To arrive at a unique andinteresting answer, the analysis must be regularizedin a sensible manner. This book describes suchregularization options, discusses efficientalgorithms which make the analysis of large data setsfeasible, and gives examples of applications.
This book presents the development and application of
regularized statistical methods for the analysis of
anatomical structures. One of the comprehensive goals
of this type of research is to use non-invasive
medical imaging devices for the detection of diseases
which are otherwise difficult to diagnose at an early
stage. Statistics represents a quintessential part of
such investigations as they are preluded by a
clinical hypothesis that must be verified based on
observed data. The massive amounts of image data
produced in each examination pose an important and
interesting statistical challenge, in that there are
many more image features (variables) than subjects
(observations), making an infinite number of
solutions possible. To arrive at a unique and
interesting answer, the analysis must be regularized
in a sensible manner. This book describes such
regularization options, discusses efficient
algorithms which make the analysis of large data sets
feasible, and gives examples of applications.
Karl Sjöstrand recieved his Ph.D. degree in Mathematical
Modelling from the Technical University of Denmark in 2007 and
his master of science degree in computer systems engineering from
the Technical Faculty at the University of Lund, Sweden, in 2003.
Über den Autor
Karl Sjöstrand recieved his Ph.D. degree in Mathematical
Modelling from the Technical University of Denmark in 2007 and
his master of science degree in computer systems engineering from
the Technical Faculty at the University of Lund, Sweden, in 2003.
Klappentext
This book presents the development and application of
regularized statistical methods for the analysis of
anatomical structures. One of the comprehensive goals
of this type of research is to use non-invasive
medical imaging devices for the detection of diseases
which are otherwise difficult to diagnose at an early
stage. Statistics represents a quintessential part of
such investigations as they are preluded by a
clinical hypothesis that must be verified based on
observed data. The massive amounts of image data
produced in each examination pose an important and
interesting statistical challenge, in that there are
many more image features (variables) than subjects
(observations), making an infinite number of
solutions possible. To arrive at a unique and
interesting answer, the analysis must be regularized
in a sensible manner. This book describes such
regularization options, discusses efficient
algorithms which make the analysis of large data sets
feasible, and gives examples of applications.
