10-04-2017, 08:32 PM
Abstract
Over the last decade, a picture archiving and communications system (PACS) has been accepted by an increasing number of clinical organizations. Today, PACS is considered as an essential image management and productivity enhancement tool. Image compression could further increase the attractiveness of PACS by reducing the time and cost in image transmission and storage as long as 1) image quality is not degraded and 2) compression and decompression can be done fast and inexpensively. Compared to JPEG, JPEG 2000 is a new image compression standard that has been designed to provide improved image quality at the expense of increased computation. Typically, the decompression time has a direct impact on the overall response time taken to display images after they are requested by the radiologist or referring clinician. In this paper, we present a fast JPEG 2000 decoder running on a low-cost programmable processor. It can decode a losslessly compressed 2048 2048 CR image in 1.51 s. Using this kind of a decoder, performing JPEG 2000 decompression at the PACS display workstation right before images are displayed becomes viable. A response time of 2 s can be met with an effective transmission throughput between the central short-term archive and the workstation of 4.48 Mb/s in case of CT studies and 20.2 Mb/s for CR studies. We have found that JPEG 2000 decompression at the workstation is advantageous in that the desired response time can be obtained with slower communication channels compared to transmission of uncompressed images. Index Terms Digital Imaging and Communications in Medicine committee (DICOM), fast decoder, image compression, JPEG 2000, picture archiving and communications system (PACS), response time.
I. INTRODUCTION
OVER the last decade, a picture archiving and communications system (PACS) has been accepted by an increasing number of clinical organizations [1]. Today, PACS is considered by clinicians and hospital administrators alike as an essential image management and productivity enhancement tool. PACS aims at providing an all-digital radiology department in hospitals for acquisition, distribution, display, and archival of images from various imaging modalities. Image compression has increased the viability of teleradiology applications by reducing the bandwidth requirements and allowing expeditious and cost-effective delivery of medical images to radiologists located elsewhere for primary diagnosis [2]. Similarly, image compression can make the implementation of PACS more at- tractive by reducing transmission and storage requirements and making it more responsive. Data compression can be lossless or lossy. Lossless compression can reconstruct the original image without any change, but has limited compression capabilities. Clunie [3] evaluated various lossless compression techniques for medical images and reported a compression ratio ranging from 1.66 to 3.91. Lossy compression can achieve a higher compression ratio at the cost of some information loss in the compression/decompression process. Several studies [4] [6] have been performed to evaluate the effect of lossy compression on the diagnostic quality of the image. All these studies used transform-based compression techniques based on either discrete cosine transform (DCT) or discrete wavelet transform (DWT) and reported compression ratios ranging from 10:1 to 20:1 as being suitable for the purpose of making primary diagnosis on CR images. Wavelet-based compression is regarded as being superior to DCT-based compression methods [4], [7], [8]. However, lack of an international standard based on the wavelet transform has hindered its widespread use in medical imaging. Some companies use their own proprietary wavelet-based compression techniques, which is allowed within the framework of the Digital Imaging and Communications in Medicine committee (DICOM), but it does not facilitate interconnectivity, particularly across equipment and systems from different vendors. The International Standards Organization (ISO) has recently standardized a new image compression standard, JPEG 2000 [9]. Similar to JPEG, it is a transform-based compression technique and supports both lossless and lossy modes. It utilizes wavelet transform properties along with bit-plane and arithmetic coding to achieve better compression. Foos et al. [10] conducted a study to compare the diagnostic quality of images compressed using JPEG 2000 to that using JPEG. For CR images, they concluded that there is no loss of diagnostic information for both compression standards with 1 bit per pixel (bpp). At bit rates lower than 1 bpp, JPEG-compressed images showed more degradation due to blocking artifacts arising from the use of 8 8 DCT. For CT images, they observed JPEG 2000 compressed images as being superior at all bit rates. JPEG 2000 has been designed to provide improved compression, i.e., at the same bit rate, it offers better quality images or at the same image quality, and it produces lower bit rates, compared to the existing standards at the expense of a significantly increased amount of computation, leading to longer compression and decompression times.
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