Yazar: Kentucky, USA) El-Baz Ayman (University of Louisville

Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can significantly increase the patient’s chance for survival. For this reason, CAD sy …

Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can significantly increase the patient’s chance for survival. For this reason, CAD sy …

Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which …

This book covers the state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis. It includes several prominent imaging modalities such as MRI, CT, and P …

This book covers the state-of-the-art approaches for automated non-invasive systems for early cardiovascular disease diagnosis. It includes several prominent imaging modalities such as MRI, CT, and P …

Today’s healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information te …

Today’s healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information te …

This book covers state-of-the-art medical image analysis approaches currently pursued in autism research. Chapters cover recent advances in diagnosis using structural neuroimaging. All aspects of ima …

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 techniq …

Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging anal …

Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging anal …

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 …

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 …

Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which …

Lung cancer remains the leading cause of cancer-related deaths worldwide. Early diagnosis can improve the effectiveness of treatment and increase a patient”s chances of survival. Thus, there is an u …

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 …

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 techniq …

This book covers state-of-the-art medical image analysis approaches currently pursued in autism research. Chapters cover recent advances in diagnosis using structural neuroimaging. All aspects of ima …

This book covers novel strategies and state of the art approaches for automated non-invasive systems for early prostate cancer diagnosis. Prostate cancer is the most frequently diagnosed malignancy a …

This book covers novel strategies and state of the art approaches for automated non-invasive systems for early prostate cancer diagnosis. Prostate cancer is the most frequently diagnosed malignancy a …