Andere Kunden interessierten sich auch für
![Image Segmentation in Experimental Mechanics]( "Image Segmentation in Experimental Mechanics")
Image Segmentation in Experimental Mechanics44,99 €![Edge Detection using Rough Set Theory]( "Edge Detection using Rough Set Theory")
Edge Detection using Rough Set Theory26,99 €![Hyperspectral Data Classification Using Contourlet Transform]( "Hyperspectral Data Classification Using Contourlet Transform")
Hyperspectral Data Classification Using Contourlet Transform36,99 €![LIQUID LEVEL SENSING]( "LIQUID LEVEL SENSING")
LIQUID LEVEL SENSING51,99 €![High-level System Modeling with SystemC and TLM]( "High-level System Modeling with SystemC and TLM")
High-level System Modeling with SystemC and TLM38,99 €![Locally Convex Spaces]( "Locally Convex Spaces")
Locally Convex Spaces58,99 €![Probabilistic segmentation of intravascular ultrasound sequences]( "Probabilistic segmentation of intravascular ultrasound sequences")
Probabilistic segmentation of intravascular ultrasound sequences32,99 €
Recent developments in medical imaging technology
have changed the practice of medicine, providing
physicians with powerful, non-invasive methods for
studying the internal anatomy and function of the
human body. These advances in imaging techniques
offer both a great opportunity and a tremendous
challenge for the image processing community to
develop new tools to help the analysis and
interpretation of the vast amount of complex medical
imaging data. The work presented in this book is
motivated by the fascinating task of studying the
structural and functional relationship of the human
brain, with the specific aim of developing
geometrically accurate and topologically correct
methods for automatic segmentation of 3D magnetic
resonance brain images. Several new methods are
reported in this book, which should help provide new
insights in understanding the medical image
segmentation problem and the challenges it poses, and
help promote future development in the fields of
image processing, signal processing, computer vision,
and medical imaging.
have changed the practice of medicine, providing
physicians with powerful, non-invasive methods for
studying the internal anatomy and function of the
human body. These advances in imaging techniques
offer both a great opportunity and a tremendous
challenge for the image processing community to
develop new tools to help the analysis and
interpretation of the vast amount of complex medical
imaging data. The work presented in this book is
motivated by the fascinating task of studying the
structural and functional relationship of the human
brain, with the specific aim of developing
geometrically accurate and topologically correct
methods for automatic segmentation of 3D magnetic
resonance brain images. Several new methods are
reported in this book, which should help provide new
insights in understanding the medical image
segmentation problem and the challenges it poses, and
help promote future development in the fields of
image processing, signal processing, computer vision,
and medical imaging.