Automatic medical image classification refers to assigning an medical image into a class, among a number of image categories. Due to computational complexity, it is an important task in the content based image retrieval (CBIR). In this paper, we propose a method for classification and retrieval of medical images using multi-feature extraction method. Here, edge and patch based methods are used ...

Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical pr...

This chapter describes a semantic dialogue system for radiologists in a comprehensive case study within the large-scale MEDICO project. MEDICO addresses the need for advanced semantic technologies in the search for medical image and patient data. The objectives are, first, to enable a seamless integration of medical images and different user applications by providing direct access to image sema...

Content-based image retrieval (CBIR) is an important multimedia application. In recently emerged MPEG-7 standard, image content is described by perceptual features such as color, texture and shape. Many shapebased image retrieval techniques have been proposed in literature. However, almost all of these techniques assume isolated objects and use only shape feature for retrieval. General image re...

introduction: the manual and paper-based process of production and storage of medical records in iran have led to difficulties in filing and retrieval of the medical records. one of the usual solutions is using computerized medical records via electronic storage of paper-based medical records. the aim of this study was to recognize using computerized medical records in nine selected hospitals. ...

The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image retrieval method for a special medical image retrieval problem where the images in the retrieval database can be annotated into one of the pre-defined labels. Even more, a user may query the database with an image that is close to but not exactly wha...

In medical imaging DICOM (Digital Imaging and Communications in Medicine) format is the most commonly used format. Various medical imaging sources generate images in this format, which are collected in large database repository [1]. Various modalities of medical images such as CT scan, XRay, Ultrasound, Pathology, MRI, Microscopy, etc [2] are used to collect these images. From the analysis of t...

 Background: The most expensive variable in the operating room (OR) is time. Lean Process Management is being used in the medical field to improve efficiency in the OR. Streamlining individual processes within the OR is crucial to a comprehensive time saving and cost-cutting health care strategy. At our institution, one hour of OR time costs approximately $500, exclusive of supply and personnel...

Large efforts have been made for general applications of content-based image retrieval (CBIR). Established CBIRsystems globally evaluate color, texture, and also shape for retrieval. In medical imaging, local image characteristics are fundamental for image interpretation, which is based on a large amount of a-priori knowledge. Therefore, CBIR is rather seldom applied to medical images. Successf...