Dealing with information extracted from a natural image, a medical scan, satellite data or a frame in a video sequence is the purpose of image analysis. In the real world, the stimulus that is received by the retina is perceived as whole and complete information. Between the electromagnetic reception and the perception, physiological and neurological processes construct the final perception and...

H. Handels1; T. M. Deserno2; H.-P. Meinzer3; T. Tolxdorff4 1Institute of Medical Informatics, University of Lübeck, Lübeck, Germany; 2Department of Medical Informatics, Aachen University of Technology (RWTH), Aachen, Germany; 3Department of Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany; 4Institute of Medical Informatics, Charité – University Medic...

BACKGROUND Storage issues and bandwidth over networks have led to a need to optimally compress medical imaging files while leaving clinical image quality uncompromised. METHODS To determine the range of clinically acceptable medical image compression across multiple modalities (CT, MR, and XR), we performed psychometric analysis of image distortion thresholds using physician readers and also ...

The growing repositories of clinical imaging data generate a need for effective image management and access that demands more than simple text-based queries. Content-Based Image Retrieval (CBIR) is an active research field and has drawn attention in recent years. It is a technique to organize and search image archives by their visual content. It is a multi-discipline field that integrates techn...

---Medical Image Analysis is essential in order to detect and diagnose the various types of Cancers. In recent years there is a rise in the death rate of patients suffering from brain cancer and lung cancer. The chances of survival among people can increase if the detection is done in the earlier stage. The widely used diagnose technique is Magnetic Resonance Imaging (MRI), Computed Tomography ...

The improvement in image compression filed is mainly related to the need of rapid and efficient techniques for the storage and transmission of data among individuals. To obtain the maximal capabilities of storage and transmission, different compression algorithms should be compared to find the optimal technique for medical image compression. This work examines the coding properties of the Wavel...

Diffusion tensor magnetic resonance imaging (DT-MRI) is emerging as an important tool in medical image analysis of the brain. However, relatively little work has been done on producing statistics of diffusion tensors. A main difficulty is that the space of diffusion tensors, i.e., the space of symmetric, positivedefinite matrices, does not form a vector space. Therefore, standard linear statist...

Research in big data is focused on deriving knowledge from multiple data formats using intelligent analytics techniques. Medical analytics is a typical example, which encompasses data in multiple formats available as text, images and the data in the databases. Performing large scale image data analysis for near real time results is a challenging task. The challenge here is to extract features w...

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness ...

Medical images have made a great influence on medicine, diagnosis, and treatment. The most important part of image processing is image segmentation. This helps in the selection of Region of interest(ROI) of various medical images, which helps in further processing of the medical image. In this paper, first of all, Medical Image processing is discussed briefly. Then, various Start of the Art met...