Research Of Medical Image Compression Technology Based On DICOM Standards

As a great number of medical image equipments,such as ultrasonic instruments,radiation and CT,have entered hospitals,digital medical image data have been widely used and the PACS emerged.PACS is a kind of picture archiving and communication system(Picture Archiving & Communication System,PACS)for medical image sampling,storing,administration and transmission.So the medical images in PACS must abide by uniform standards. American radiation institute and national electrical manufactures association established the DICOM(Digital Imaging and Communication in Medicine) standard,i.e,medical digital imaging and communication standard which consists of medical digital imaging and communication transmission.And this has become the general images standard in PACS now.The quantity of medical images is so large that it is a great chalienge to the performance of the storage equipments and the transmission equipments.On the premise of not affecting the clinic diagnosis,it is quite necessary to compress the medical images.Combining with clinic operability,this paper does deep research and discussion on medical images compression algorithm on the basis of DICOM formation of medical images,lifting integer wavelet and neural network algorithm.The main work of this paper is as follows(1)This paper mainly focuses on a new kind of image compression algorithm,which takes advantage of a 9/7 lifting wavelet filter with rational coefficients and combines BP neural network and human vision system,on the basis of lifting wavelet transformation.To improve the quality of reconstructed image,the algorithm in this paper adopts improved filter with rational coefficients,and it overcomes the irreversibility of the compression process caused by float coefficients.After wavelet transformation,the wavelet coefficients are blocked by frequency band and imported to BP network to do self-organizing learning compression.Then the validity of different reconstructed images via different BP networks algorithms was discussed and the optimal algorithm was chosen by simulation.Due to the preprocessing,the wavelet coefficients of which the numerical value is in close agreement and the energy is concentrated,which would benefit network learning.At last,the reconstructed image is of good vision effect and better peak signal to noise ratio(PSNR),and the algorithm is easy to operate.(2)Using Visual C++ visual programming technology,medical images software compression system in windows operation system is developed.It mainly achieves the algorithm proposed in this paper, the classical EZW coding compression method and the transformation between DICOM and BMP files.Users can choose different image compression quality with visual scroll bar,and can decide the final compression ratio via previewing images of different PSNR value.(3)A DICOM files operating software is developed.As a DICOM file includes unique file head and data format,it can't be browsed in general computer.Meanwhile,medical images are of great difference in pixels depth,so the normal displaying range always can only reflect parts of the information included by the images.Therefore, this paper gives a method to transform the DICOM files to bitmap files format,and linearly transform the images data in the windows area into the largest displaying area of the display,and adapt the width and position of the window,in order to observe all information of the medical image.This method makes it possible to browse the DICOM file in any common computer...