ROI Segmentation on DICOM Images in Noisy Environment
A CAD Approach
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Recently Computer Aided Diagnosis (CAD) has become one of the important and major research subjects in medical imaging and diagnostic radiology. The basic concept of CAD is to provide a computer output as a second opinion to assist radiologists' image interpretation by improving accuracy and consistency of radiological diagnosis and also by reducing the image reading time. The goal of CAD is to improve the quality and accuracy of radiological diagnosis. This book gives basic idea of CAD and detailed information about the Region of Interest (ROI) segmentation performed on DICOM lung images to e...
Recently Computer Aided Diagnosis (CAD) has become one of the important and major research subjects in medical imaging and diagnostic radiology. The basic concept of CAD is to provide a computer output as a second opinion to assist radiologists' image interpretation by improving accuracy and consistency of radiological diagnosis and also by reducing the image reading time. The goal of CAD is to improve the quality and accuracy of radiological diagnosis. This book gives basic idea of CAD and detailed information about the Region of Interest (ROI) segmentation performed on DICOM lung images to extract the lung nodules from lung portion using various edge detection operators with and without noise.The results are helpful to study and analyze the influence of noise and can be included in the CAD system based on an automatic diagnosis for early detection of lung cancer by extracting the nodules from the lung regions included in chest DICOM images.
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