Using a Priori Information for Improving the Compression of Medical Images
نویسندگان
چکیده
This paper presents the methods of improving the compression efficiency by incorporating a priori information in compression process. The characteristic of medical images can be used for choosing proper procedures of compression algorithm and constructing suitable new data conversion techniques for increasing the compression effectiveness and better preserving diagnostic accuracy. As an example of applying a priori information, lossless DPCM-based and lossy block DCT-based algorithms are used. Achieved increasing of compression efficiency is from 6 to 35 % for different medical modalities and up to 50 % for the sequences of US images.
منابع مشابه
Medical Image Compression Based on Region of Interest
Medical images show a great interest since it is needed in various medical applications. In order to decrease the size of medical images which are needed to be transmitted in a faster way; Region of Interest (ROI) and hybrid lossless compression techniques are applied on medical images to be compressed without losing important data. In this paper, a proposed model will be presented and assessed...
متن کاملMEDICAL IMAGE COMPRESSION: A REVIEW
Within recent years the use of medical images for diagnosis purposes has become necessity. The limitation in transmission and storage space also growing size of medical images has necessitated the need for efficient method, then image Compression is required as an efficient way to reduces irrelevant and redundancy of the image data in order to be able to store or transmits data. It also reduces...
متن کاملAssessment of the Wavelet Transform for Noise Reduction in Simulated PET Images
Introduction: An efficient method of tomographic imaging in nuclear medicine is positron emission tomography (PET). Compared to SPECT, PET has the advantages of higher levels of sensitivity, spatial resolution and more accurate quantification. However, high noise levels in the image limit its diagnostic utility. Noise removal in nuclear medicine is traditionally based on Fourier decomposition o...
متن کاملA New Method for Improving Computational Cost of Open Information Extraction Systems Using Log-Linear Model
Information extraction (IE) is a process of automatically providing a structured representation from an unstructured or semi-structured text. It is a long-standing challenge in natural language processing (NLP) which has been intensified by the increased volume of information and heterogeneity, and non-structured form of it. One of the core information extraction tasks is relation extraction wh...
متن کاملDecision Support System for Age-Related Macular Degeneration Using Convolutional Neural Networks
Introduction: Age-related macular degeneration (AMD) is one of the major causes of visual loss among the elderly. It causes degeneration of cells in the macula. Early diagnosis can be helpful in preventing blindness. Drusen are the initial symptoms of AMD. Since drusen have a wide variety, locating them in screening images is difficult and time-consuming. An automated digital fundus photography...
متن کامل