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...
With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The centr...
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.
Advances in image-guided cancer surgery have enlarged the role of image segmentation and registration. This book reviews current methodologies, to hel...
Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis.
Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obtain clinically useful information. The second is the accurate and fast inferring of meaningful and clinically valid CAD decisions and/or predictions on the basis of model-guided image analysis.
To help address...
Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-gu...
As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their...
As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic tech...
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.
Advances in image-guided cancer surgery have enlarged the role of image segmentation and registration. This book reviews current methodologies, to hel...
"There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients"--
"There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze B...