introduction: having a desirable image in a market can be considered as an asset for an organization. therefore, using proper approaches, managers of such organizations must monitor and manage the image of their organizations in order to achieve their organizational goals and their customer’s satisfaction. as an important sector of every society, managers of hospitals also must try their best t...

1. Original contribution of this work: Development of a shape classiication method. Development of a novel approach to aligning arbitrary shapes in a common coordinate-parameterization frame. Accuracy improvements of current 2-D exible shape registration methods. Application of the developed methods to brain model design and MR brain image segmentation. 2. Importance of the contribution: Shape ...

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combinat...

Image segmentation plays a major role in the analysis of medical image disease diagnosis. Image features extracted is the basis for precise image segmentation. Variable nature of image features, such as size, shape, intensity, color, texture etc., cause complexity in the image segmentation and analysis of the image nature. Existing work estimate the effectiveness of the level-set shape beside w...

Medical imagining is one of the major disciplines for analyzing human tissues non-invasively. Image segmentation is a sub-process in image processing that divides the given image into meaningful regions that can used for further classification and analysis. This step is challenging, as it difficult to identify precisely and extract that portion of the image having abnormal tissues for further d...

Image Processing, Optimization and Prediction of an Image play a key role in Computer Science. Image processing provides a way to analyze and identify an image .Many areas like medical image processing, Satellite images, natural images and artificial images requires lots of analysis and research on optimization. In Image Optimization and Prediction we are combining the features of Query Optimiz...

The availability of digital imagers inside hospitals and their ever growing inspection capabilities have established digital medical images as a key component of many pathologies diagnosis, follow-up and treatment. To face the growing image analysis requirements, automated medical image processing algorithms have been developed over the two past decades. In parallel, medical image databases hav...

The development of methods to accurately and reproducibly recover useful quantitative information from medical images is often hampered by uncertainties in handling these data related to image acquisition parameters, the variability of normal human anatomy and physiology, the presence of disease or other abnormal coditions, and a variety of other factors. In this talk, several image analysis st...

In this paper we present a novel technique for non-rigid medical image registration and correspondence finding based on a multiple-layer flexible mesh template matching technique. A statistical anatomical model is built in the form of a tetrahedral mesh, which incorporates both shape and density properties of the anatomical structure. After the affine transformation and global deformation of th...

both for diagnosis and for planning of appropriate treatment. Therefore medical imaging as the methodology of physical investigations have become one of the most important tools in the whole of biomedical engineering, and also the market of imaging devices can be found as a very fast developing parts of Med-systems. Based on the variety of modern medical imaging devices, a physician can obtain ...