Embedded Reversible Medical Image Compression Using Integer Wavelet Transform

Wavelet Packet Compression of Medical Images

Objective To evaluate the teaching effects of case introduced method based on pic- ture archiving and communication system （ PACS ） system in medical imaging course. Methods Totally 148 students （ 2009 grade ） majored in five-year clinical medicine from Xiangya Medical College were divided into 10 groups; the 10 groups were taken randomly as control group （ n=75 ） and experimental group （ n=73 ）. Control group used traditional teaching methods （ film teaching ） while experimental group used case introduced method based on PACS system. Effects of teaching between were evaluated by questionnaire and test. χ^2 test was used to compare students＇ theoretical test scores, with α level = 0.05. Results Based on results of questionnaires, more students in experimental group than in control group hold that case introduced method based on PACS system can achieve the purpose of teaching, improve interests in learning, and strengthen the mastery of knowledge. Test scores showed that the percentage of students scored 90-100 and 80-89 （ respectively 14%, 75% ） in experimental group was significantly higher than that in control group （respectively 5%, 66% ） （χ^2 =17.932, P=O.O00 ）. Conclusions Application of case introduced method based on PACS system in medical imaging course not only improve students＇ motivation to learn and their clinica~ ability-, but also allow teachers to find and correct short- comings of students timely, therefore, it is worth promoting. Key words: Picture archiving and communication system; Case introduced method; Prac-tice teaching

Picture archiving and communication systems (PACS) is a current research topic in both the United States and Japan. During the past 6 years, our department has been working in this field very closely with our colleagues in Japan. In July 1 986, we attended the Third International Symposium on Picture Archiving and Communication Systems/Personal Health Data Recording Systems (JPACS) in conjunction with the Fifth Symposium on Medical Imaging and Technology (JAMIT) at the National Cancer Center in Tokyo. After the meeting, we visited various PACS research and development laboratories at major imaging manufacturers and hospitals. We summarized our impressions in a commentary: “Picture Archiving and Communication Systems in Japan” [1 ]. Since then, we have successfully implemented two PACS modules, one in the pediatric radiology section and one in the coronary care unit [2, 3]. More than 200 visitors from Japan have come to see our facilities. Among these visitors was Professor T. Takahasi from Kyoto University Hospital, who was the program chairman of the Eighth Symposium of JAMIT/Sixth International Symposium on PACS in July 1 989. After his visit, he extended an invitation to us to give the keynote speech, “Recent Progress in PACS” for the meeting. We took this opportunity to go back to Japan and repeat the hospital and laboratory tour in order to observe their research and development progress in PACS during the past 3 years. This paper is a summary of our opinion ofthe changes that have occurred in Japan since our last visit of the status of PACS in that country compared with that in ours. The JAMIT Meeting and the JPACS Meeting

Strategic Environmental Assessment (SEA) Process towards the Sustainable Design and Construction of Computer, Communication, Network Engineering, Machine Learning and Artificial Intelligence Systems

Steganography which is an art as well as a science of invisible transmission arrived as a saviour by providing utmost security through various techniques. Medical Image Steganography is a special subcategory of Image Steganography. It has come a long way to make the transmission of medical images more and more safe and to make sure that the diagnostic reading of the image does not get affected. Security is the most crucial aspect of communication in today’s world. While sharing documents on the internet, one needs assurance of privacy and secrecy, as these days’ communication is not only restricted to chatting but plays a vital role in almost all sectors. This paper discusses various algorithms used in medical image steganography and analyse the best out of all based on various characteristics of the algorithms like robustness, PSNR (Peak signal-to-noise ratio) value, MSE (Mean Squared Error) value, payload capacity etc.

Multicenter Research Studies in Radiology

In recent years most of researcher’s has done tremendous work in the field of medical image applications such as Magnetic Resonance Imaging (MRI), Ultra Sound, CT scan but still there are many research and experiments in medical imaging field and diagnosing of human health by Health Care Institutes. There is a growing interest for medical imaging de-noising as a hot area of research and also imaging equipment as a device. It is used for better image processing and highlighting the important features. These images are affected with random noise during acquisition, analyzing and Transmission process. This results in blurry image visible in low contrast. Wavelet transforms have effective method to separate the noise from the original medical image by using threshold techniques without affecting the important data of an image. Wavelet transform enables us to use the forward wavelet transform to represent sub-band of the original image in decomposition process then reconstructing this sub band coefficients to original image using inverse wavelet transform. In this work, the quality of medical image has been evaluated using filter assessment parameters like Variance, standard deviation, the squared difference error between original medical image & de-noised image (MSE) and the ratio between original image & noisy image. From numerical results, we can see that the algorithm is efficient de-noising of noisy medical image. When, investigating with Baye’s threshold techniques it achieved the Best value of peak signal to noise ratio (PSNR). For best medical image de-noising, the wavelet based de-noising algorithm has been investigated and results of Baye’s techniques and hard & soft threshold methods have been compared.

Com o advento dos equipamentos digitais de diagnóstico médico, houve uma diminuição do uso de filmes emradiologia. Em contrapartida, o gerenciamento de imagens médicas (IMs) digitalizadas tornou-se uma tarefa crítica. Neste trabalho, apresentamos um protótipo, com base em tecnologias worldwide web (www), que realiza essa função. Ele contempla um servidor de IMs que possibilita a pesquisa e a recuperação dessas imagens armazenadas como arquivos digital imaging and communications in medicine (Dicom), além de receber requisições de serviços de equipamento sem aplicações compatíveis com esse padrão. As IMs podem ser visualizadas e manipuladas dentro de um navegador web (o cliente da aplicação) por meio de uma aplicação Java (applet). Tal abordagem oferece algumas vantagens em relação aos tradicionais sistemas de arquivamento e comunicação de imagens (picture archiving and communication systems [Pacs]), entre as quais a independência de plataformas e facilidade de instalação e de manutenção, a distribuição de dados e a integração com outros sistemas, dentro ou fora da instituição. Basta que se utilize a implementação de políticas de segurança. A simplicidade e a flexibilidade das tecnologias web viabilizam o uso dessa aplicação que provê recursos tanto para o gerenciamento quanto para a manipulação de IMs.

Srini Raghavan has over 25 years of experience in design, simulation and analysis of satellite communication systems, spread spectrum systems, and signal processing. Currently, he is supporting several communication systems and Global Positioning System (GPS)-related activities at The Aerospace Corporation, where he is a Senior Engineering Specialist. He has a B.S. and M.Tech. from India, and an M.S. and Ph.D. in Electrical Engineering from the University of MissouriRolla, and is a Senior Member of IEEE and a member of ION, Eta Kappa Nu and Sigma Xi. Jack K. Holmes is a Distinguished Engineer at The Aerospace Corporation in the Communication Systems Subdivision. He has over 40 year’s of experience in analysis, simulation, and design of communication and spread spectrum systems. He is author of the book entitled “Coherent Spread Spectrum Systems” and has published approximately 45 papers in the area of communications, synchronization, and GPS-related subjects. He has been heavily involved in the military side of the GPS Modernization effort since February 1997. He is currently the GPS Code Acquisition design risk assessment subteam leader for the GPS Modernization risk assessment team. Jack received his B.S., M.S., and Ph.D. degrees at UCLA in Electrical Engineering, and is a senior member of the IEEE and a member of ION, Tau Beta Pi, and Sigma Xi.

Medical images must be compressed before transmission due to bandwidth and storage limitations. The set partitioning in hierar- chical trees (SPIHT) algorithm is an efficient method for lossy and loss- less coding of medical images. We propose some modifications to the SPIHT algorithm. It is based on the idea of the insignificant correlation of wavelet coefficients among medium- and high-frequency subbands. In this scheme, insignificant wavelet coefficients that correspond to the same spatial location in the medium subbands can be used to reduce the redundancy by a combined function proposed in associated with the modified SPIHT. In high-frequency subbands, the modified SPIHT pro- poses a dictator to reduce the interband redundancy. Experimental re- sults indicate that the proposed technique improves the quality of the reconstructed medical image in terms of both the peak signal-to-noise ratio (PSNR) and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate. © 2003 Society of Photo-Optical Instrumentation Engi- neers. (DOI: 10.1117/1.1578645)

The recent introduction of the High Efficiency Video Coding (HEVC) standard provides opportunities to improve medical image compression in picture archiving and communications systems. In this paper, we propose improvements to the HEVC intra coding process for lossless compression of grayscale anatomical medical images, which are characterized by their large amount of edges. Specifically, we propose alternative angular and planar prediction modes that are based on sample-wise differential pulse code modulation (DPCM) with an increased range of directionalities. We also propose an implementation of the DPCM decoding process that maintains the block-wise coding structure of HEVC. Evaluation results on various medical images show that the proposed DPCM modes efficiently predict the large amount of edges in these images achieving bit-rate savings of up to 15%.

Digital medical images are becoming even more widespread and used in a large variety of applications. Such images are often stored in local repositories and need to be transmitted/ received over the network. Therefore, data compression is an essential mechanism to adopt for improving the transmission time, as well as to optimize the required storage space. However, due to the clinical relevance of such data, lossless techniques are almost ever preferred, given that in such context it is not tolerated any loss of data. In this work, starting from the Medical Images Lossless Compression (MILC) algorithm, which enables the efficient coding of three-dimensional medical images achieving results comparable with the other state-of-art algorithms, we propose Parallel MILC, a fully parallelized version of that algorithm, which provides some attractive features with respect to MILC, especially in terms of execution speedup and scalability. In detail, we propose a novel design and implementation for the MILC algorithm, which is able to exploit the power and the capabilities of the parallel computing paradigm. It is important to point out that Parallel MILC can be executed on several heterogeneous device types supporting OpenCL (i.e. CPU, GPU, FPGA, etc.). The preliminary test results show a significant performance speedup of Parallel MILC compared to MILC. Consequently, the novel algorithm we propose provides MILC with strong scalability properties and complete transparency with respect the underlying hardware.

Digital templating is a standard preoperative planning method in THA. Unfortunately, many hospitals cannot afford the software or have accessibility barriers owing to a limited number of installed computer workstations. We created a templating method using a picture archiving and communication system and the Keynote program on a mobile phone. The method's accuracy and reliability have not been compared with those of commercial digital templating software. (1) How accurate is this novel method on iPhone and iPad mobile devices compared with a commercially available digital templating software program? (2) Is the method reproducible among users with different levels of experience? (3) Are the results similar for different types of femoral prostheses? Between January 2017 and May 2020, we treated 209 patients for hip disease or trauma with primary cementless THA. We considered patients with a normal contralateral hip as potentially eligible for this retrospective study. Thus, 91% (191 of 209 hips) were eligible; a further 13% (27 hips) were excluded because of postoperative leg length discrepancy > 5 mm, femoral offset discrepancy > 5 mm (9% [18 hips]), intraoperative periprosthetic fracture (4% [eight hips]), and proximal femoral deformity (0.5% [one hip]), leaving 78% (164 hips) for analysis here. Their preoperative radiographs were evaluated by three independent assessors, including one senior orthopaedic surgeon, one senior resident, and one junior resident, using three methods. The first was digital templating using OrthoView software, which is a commercially available digital templating software program used worldwide and known to possess high accuracy. The other two methods were technically similar to one another, with the only difference being the interface: iPhone versus iPad. In both of those approaches, using the picture archiving and communication system measurement tool, we drew a circle on an acetabular radiograph to depict the cup. We took a photograph of the computer display and imported the photograph into slides of the Keynote program, a presentation software application for Mac computers, on both devices. It was then underlaid on transparent digital templates of the femoral stem, which were scanned from plastic templates and positioned at the center of each slide. We scaled the image to the template by adjusting the image size until a 15-cm straight line on the hip photograph was equal to the 15-cm scale markers of the template. All templating results were compared with the actual implanted cementless THA components to assess accuracy. All assessors were blinded to the information about the actual implants, and they were not involved in performing the surgical procedures. The intrarater and interrater reliabilities were analyzed using intraclass correlation coefficients and kappa values. The accuracy for predicting stem size for each type of the four stem designs was compared among the three methods. We were able to predict the acetabular cup size within one size in 92% of hips (151 of 164) using OrthoView and in 92% (150 of 164) using the novel method (p > 0.99). The accuracies of the three methods were comparable for predicting a femoral stem size within one size (OrthoView: 90% [148 hips], iPhone: 93% [152 hips], and iPad: 91% [149 hips]; p = 0.78), and neck length (OrthoView: 96% [157 hips], iPhone: 96% [158 hips], and iPad: 97% [159 hips]; p = 0.95). Using OrthoView, the neck offset was correctly predicted in 80% (132 hips), compared to 85% (139 hips) when using the iPhone and 82% (134 hips) when using the iPad (p = 0.57). All methods showed substantial or excellent agreement regarding intrarater and interrater reliability. There was no difference in accuracy regarding any of the four femoral stem designs we evaluated (Avenir, Excia, ML taper, and Metha). The digital templating technique for THA using an iPhone or iPad combined with a picture archiving and communication system demonstrated high accuracy, comparable to that of commercial digital templating software. This technique is reliable and reproducible for predicting a cementless prosthesis size, neck length, and offset in different types of femoral stems. It may be useful as an alternative in resource-constrained centers where commercial software programs are too expensive to be used in practice. Level IV, diagnostic study.

Since May 2002, temporal subtraction and nodule detection systems for digital chest radiographs have been integrated into our hospital's picture archiving and communication systems (PACS). Image data of digital chest radiographs were stored in PACS with the digital image and communication in medicine (DICOM) protocol. Temporal subtraction and nodule detection images were produced automatically in an exclusive server and delivered with current and previous images to the work stations. The problems that we faced and the solutions that we arrived at were analyzed. We encountered four major problems. The first problem, as a result of the storage of the original images' data with the upside-down, reverse, or lying-down positioning on portable chest radiographs, was solved by postponing the original data storage for 30 min. The second problem, the variable matrix sizes of chest radiographs obtained with flat-panel detectors (FPDs), was solved by improving the computer algorithm to produce consistent temporal subtraction images. The third problem, the production of temporal subtraction images of low quality, could not be solved fundamentally when the original images were obtained with different modalities. The fourth problem, an excessive false-positive rate on the nodule detection system, was solved by adjusting this system to chest radiographs obtained in our hospital. Integration of the temporal subtraction and nodule detection system into our hospital's PACS was customized successfully; this experience may be helpful to other hospitals.

With the Continuous Improvement of Medical Information, the Continuous Development of Image Processing Technology and the Continuous Upgrading of Hospital Image Acquisition Equipment, Medical Image Detection Has Become More and More Reliable and Effective, Becoming an Important Basis for Doctors’ Diagnosis. Now Large Hospitals Use the Combination of Radiology Information Management System and Image Archiving and Communication System to Store and Access Patients’ Images. with the Establishment of Regional Image Sharing and Cooperation Platform, the Online - Near Line - Offline Storage Strategy Adopted by the Traditional Image Archiving and Communication System Can No Longer Meet the Needs of Mass Image Data Storage. in the Retrieval of Mass Image Data, the Relational Database Used by the Image Archiving and Communication System is Inefficient in Reading the Image on the Scale of Mass Data, and the Existing Image the Archive and Communication System Lacks Complete Data Backup and Disaster Recovery Scheme. This Paper Analyses the Feasibility, Advantages and Problems to Be Solved of Using Hdfs to Store Massive Medical Image Files, and Studies How to Realize the Function of Precise Access and Range Access Provided by Pacs Efficiently in Hadoop.