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Aware's JPEG 2000 Implementation WHITE PAPER JPEG2000 for Medical Imaging 05.13 Copyright ©2013 Aware, Inc. All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means, electronic, mechanical photocopying, recording, or otherwise without the prior written permission of Aware, Inc. This document is for information purposes only and is subject to change without notice. Aware, Inc. assumes no responsibility for the accuracy of the information. AWARE MAKES NO WARRANTIES, EXPRESS OR IMPLIED, IN THIS DOCUMENT. “Aware” is a registered trademark of Aware, Inc. Other company and brand, product and service names are trademarks, service marks, registered trade- marks or registered service marks of their respective holders. WP_JPEG2000Med_0513_v01 Aware’s JPEG 2000 Implementation The healthcare industry requires modern open The Aware initial implementation of the ISO/IEC standards-based image compression techniques 15444-1 JPEG 2000 standard was designed and optimized for medical data and workflows implemented by a team of specialists with more than a decade of experience providing compression/ implemented by complex medical systems that decompression, image viewing and image process- acquire and manage digital medical imagery. ing software for medical OEMs. Incorporating almost twenty years of experience, the API brings unprec- These requirements led to the adoption of JPEG 2000 edented reliability and expertise to users. The API is as a wavelet compression standard (ISO/IEC 15444-1) clean, easy to understand, and easy to implement. Both the encoder and decoder are optimized through and its inclusion as a valid compression method in a combination of algorithmic and coding techniques DICOM. that efficiently utilize the design of modern CPUs. Reference implementations of the JPEG 2000 ISO DIRECT SUPPORT FOR DICOM standard, or baseline implementations, are designed The Aware JPEG 2000 API fully supports the input to address a sampled cross section of encoding and and output of single and multi-frame DICOM format- ted data. The API will parse, encode, decode and decoding options to provide a reference of how the reformat the DICOM data. JPEG 2000 support was standard could be used. However, these reference added to the DICOM standard in November 2001 with the publication of “Digital Imaging and Communica- implementations are not optimized and their feature tions in Medicine (DICOM) Supplement 61: JPEG sets are not flexible enough for specialized medical 2000 Transfer Syntaxes.” As described in Supplement 61, WG 4’s motivation was based on the fact that “… applications. there are both real and perceived limitations” with tra- ditional JPEG. “…WG 4 began to investigate alterna- tives, particularly those based on wavelet transforma- Aware, Inc. was the first commercial organization tion, multi-resolution analysis and more sophisticated to provide wavelet based compression algorithms entropy coders than Huffman coding.” The adoption as commercial off-the-shelf libraries designed for of JPEG 2000 as an ISO standard provided DICOM integration in larger systems. Twenty years of R&D with a timely solution. Both the JPEG 2000 lossless combined with a strong commercial focus have kept compression and lossy compression algorithms have Aware in the forefront of the wavelet based image and been accepted for use. data compression market. Today, wavelet compres- sion techniques are ubiquitous across a spectrum of medical imaging systems that require compression and streaming. Multi Frame DICOM Multi Frame DICOM This paper talks about some of the major features of the Aware JPEG 2000 implementation: RAW Aware J2K n Direct support for DICOM objects JPEG 2000 Single Frame DICOM Object Single Frame DICOM n Compress to quality target RAW J2K n Fully-compliant fixed point decompression The paper also introduces features of the JPEG 2000 Figure 1 - The Aware JPEG2000 library includes standard such as 3D volumetric compression and native support for DICOM input/output JPIP that are applicable to medical applications. ©2013 Aware, Inc. JPEG2000 for Medical Imaging | 3 Aware supports the following transfer syntaxes, Research attempts to closely correlate expert human enables transcoding between them and can extract measures of image quality with that of a machine. image data as separate files: The field of image processing and compression typically uses methods that compare each pixel of n DICOM with embedded raw image the original, uncompressed, image with the same pixel of the compressed image. Images with large n DICOM with embedded JPEG 2000 differences across large numbers of pixels are n DICOM with embedded JPEG or Lossless JPEG considered to have been degraded more than an image with small differences across fewer numbers Aware’s JPEG 2000 library enables full DICOM file of pixels. parsing, access to the most commonly used tags and a data dictionary that supports the most com- A common quantitative measure that uses this monly used tags. The Aware JPEG 2000 software also technique is called the “mean square criterion”. provides support for multi-frame DICOM files and full In many image-coding applications, the mean square support for all of the image color spaces used within error is often expressed in terms of a peak signal- DICOM. to-noise ratio, pSNR. The Aware API functions implement this pSNR measurement. COMPRESS TO TARGET QUALITY Aware’s JPEG 2000 API includes functions that The process of selecting a target compression ratio enable an image to be compressed to a target pSNR (e.g. 10:1) or target file size (e.g. 64 kbytes) does not value which is a machine measurable quantity of always correspond to an accurate measure of image image degradation. Both the entire image can be quality. An acceptable compression ratio of X for one compressed to a target pSNR and each quality layer image type (e.g. CT) may introduce an unacceptable can be coded to its own pSNR value. The ability to degree of image degradation for another image type encode each quality layer to a separate quality level (e.g. MR). A useful feature in the Aware JPEG 2000 can be used with the progressive display capabilities API is the ability to encode an image to a specified of JPEG 2000 to set minimum image quality values for target image quality. each layer that is transmitted and displayed. The JPEG 2000 standard includes lossy and lossless 22500 68 compression techniques. Lossy compression results 21500 67 in smaller data size but, depending on the amount of compression, may result in image degradation. Loss- 20500 66 less compression will maintain 100% image integrity 19500 65 but is limited to compression ratios of 2:1 to 3:1 on average. 18500 64 17500 63 pSNR (dB) The use of lossy compression techniques with medi- File Size (bytes) cal images requires controls to maintain image qual- 16500 62 ity. A commonly used practice is to select a target 15500 File Size 61 compression ratio or a target file size that has been pSNR predetermined to provide diagnostic quality. The 14500 60 1 4 7 10 13 16 19 22 25 28 31 34 37 optimal compression ratio is chosen through empirical methods and is influenced by the characteristics of an Slice Number image. The size, resolution, dynamic range, bit depth, Figure 2 - Compression to Target File Size: noise content and frequency components of an image Constant compression results in different levels of image affect its compressibility. distortion for each image in a CT series. This process of optimal compression ratio selec- Figure 2 shows a graph of file size vs. pSNR for a series tion for each modality type can be further modified of 38 CT images from one study. All of the images were to reflect how the images will be used (fast brows- compressed using Aware JPEG 2000 and a target com- ing, reference viewing or diagnostic reading), who pression ratio of 30:1. The original images have a dimen- the user is (radiologist, clinician, insurance provider) sion of 512 x 512 pixels and a bit depth of 16 bits per and the characterization of system resources such as pixel. The data shows that while each image was com- available bandwidth, memory, and processor. pressed to the same target file size, the resulting pSNR, or distortion varies from image to image. ©2013 Aware, Inc. JPEG2000 for Medical Imaging | 4 Figure 3 shows the same series of images Aware’s technology also provides a method by which compressed to a target pSNR of 64 dB. The to specify a target pSNR for each quality layer within resulting compressed images were within a 0.3 dB the JPEG 2000 file. Figure 4 shows a plot of the actual range of the specified target pSNR while the resulting pSNR and the Target pSNR for a JPEG 2000 file with file sizes varied +20% to -20% around the mean file 10 quality layers. size. Setting the image distortion level to a constant pSNR results in different levels of compression for The Aware J2K Encoder enables very accurate pSNR each image in a CT series. distortion control for each quality layer of an image. This Graph Shows Specified and Actual pSNR Values for each layer. Baseline or reference implementations 22500 68 of JPEG 2000 may use one of two methods to specify the amount of compression applied to an image, 21500 67 compression ratio, or target file size. 20500 66 The Aware implementation provides an additional 19500 65 method: compression to target pSNR. The Aware 18500 64 “compress-to-target pSNR” functionality provides a pSNR (dB) robust and repeatable method to compress medical 17500 63 File Size (bytes) image data with a machine measurable quality 16500 62 metric. File Size pSNR 15500 61 14500 60 FULLY COMPLIANT FIXED-POINT DECOMPRESSION 1 4 7 10 13 16 19 22 25 28 31 34 37 FOR OPTIMUM PRECISION AND SPEED Slice Number Medical imaging systems and JPEG 2000 require pre- Figure 3 - Compression to Target Quality: cise decoding of image data such that an ISO-com- pliant JPEG 2000 decoder passes precision testing.
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