Irreversible compression of medical images.
The volume of data from medical imaging is growing at exponential rates, matching or exceeding the decline in the costs of digital data storage. While methods to reversibly compress image data do exist, current methods only achieve modest reductions in storage requirements. Irreversible compression can achieve substantially higher compression ratios without perceptible image degradation. These techniques are routinely applied in teleradiology, and often in Picture Archiving and Communications Systems. The practicing radiologist needs to understand how these compression techniques work and the nature of the degradation that occurs in order to optimize their medical practice. This paper describes the technology and artifacts commonly used in irreversible compression of medical images. (+info)
Evaluation of irreversible JPEG compression for a clinical ultrasound practice.
A prior ultrasound study indicated that images with low to moderate levels of JPEG and wavelet compression were acceptable for diagnostic purposes. The purpose of this study is to validate this prior finding using the Joint Photographic Experts Group (JPEG) baseline compression algorithm, at a compression ratio of approximately 10:1, on a sufficiently large number of grayscale and color ultrasound images to attain a statistically significant result. The practical goal of this study is to determine if it is feasible for radiologists to use irreversibly compressed images as an integral part of the day to day ultrasound practice (ie, perform primary diagnosis with, and store irreversibly compressed images in the ultrasound PACS archive). In this study, 5 Radiologists were asked to review 300 grayscale and color static ultrasound images selected from 4 major anatomic groups. Each image was compressed and decompressed using the JPEG baseline compression algorithm at a fixed quality factor resulting in an average compression ratio of approximately 9:1. The images were presented in pairs (original and compressed) in a blinded fashion on a PACS workstation in the ultrasound reading areas, and radiologists were asked to pick which image they preferred in terms of diagnostic utility and their degree of certainty (on a scale from 1 to 4). Of the 1499 total readings, 50.17% (95% confidence intervals at 47.6%, and 52.7%) indicated a preference for the original image in the pair, and 49.83% (95% confidence intervals at 47.3%, and 52.0%) indicated a preference for the compressed image. These findings led the authors to conclude that static color and gray-scale ultrasound images compressed with JPEG at approximately 9:1 are statistically indistinguishable from the originals for primary diagnostic purposes. Based on the authors laboratory experience with compression and the results of this and other prior studies, JPEG compression is now being applied to all ultrasound images in the authors' radiology practice before reading. No image quality-related issues have been encountered after 12 months of operation (approximately 48000 examinations). (+info)
Multi-purpose HealthCare Telemedicine Systems with mobile communication link support.
The provision of effective emergency telemedicine and home monitoring solutions are the major fields of interest discussed in this study. Ambulances, Rural Health Centers (RHC) or other remote health location such as Ships navigating in wide seas are common examples of possible emergency sites, while critical care telemetry and telemedicine home follow-ups are important issues of telemonitoring. In order to support the above different growing application fields we created a combined real-time and store and forward facility that consists of a base unit and a telemedicine (mobile) unit. This integrated system: can be used when handling emergency cases in ambulances, RHC or ships by using a mobile telemedicine unit at the emergency site and a base unit at the hospital-expert's site, enhances intensive health care provision by giving a mobile base unit to the ICU doctor while the telemedicine unit remains at the ICU patient site and enables home telemonitoring, by installing the telemedicine unit at the patient's home while the base unit remains at the physician's office or hospital. The system allows the transmission of vital biosignals (3-12 lead ECG, SPO2, NIBP, IBP, Temp) and still images of the patient. The transmission is performed through GSM mobile telecommunication network, through satellite links (where GSM is not available) or through Plain Old Telephony Systems (POTS) where available. Using this device a specialist doctor can telematically "move" to the patient's site and instruct unspecialized personnel when handling an emergency or telemonitoring case. Due to the need of storing and archiving of all data interchanged during the telemedicine sessions, we have equipped the consultation site with a multimedia database able to store and manage the data collected by the system. The performance of the system has been technically tested over several telecommunication means; in addition the system has been clinically validated in three different countries using a standardized medical protocol. (+info)
Optimizing spectral power compression with respect to inference performance for recognition of tumor patterns in ultrasound images.
Imaging modalities are widely used to explore and diagnose diseases. Feature extraction methods are used to quantitatively describe and identify objects of interest in acquired images, typically involving data compression. The extracted features are subject to clinical inference, whereby the compression ratio used for feature extraction can affect the inference performance. In this paper, a new method is introduced which allows for optimal data compression with respect to performance maximization of uncertain inference. The model introduced herein identifies objects of interest using selective data compression in the frequency domain. It quantifies the amount of information provided by the inference involving these objects, calculates the inference efficiency, and estimates its cost. By analyzing the effect of data compression on inference efficiency and cost, the method allows for the optimal selection of the compression ratio. The method is applied to prostate cancer diagnosis in ultrasound images. (+info)
Automatic learning of the morphology of medical language using information compression.
Conversion of free-text strings in a natural language to a standard representation (codes) is an important reoccurring problem in biomedical informatics. Determining the content of a string involves identifying its meaningful constituents (morphemes). One current method of identifying these constituents is to look them up in a preexisting table (lexicon). Manual construction of lexicons and grammars in complex domains such as biomedicine is extremely laborious. As an alternative to the lexico-grammatical approach, we introduce a segmentation algorithm that automatically learns lexical and structural preferences from corpora via information compression. The method is based on the Minimum Description Length (MDL) principle from classic information theory. (+info)
Development of a biomedical imaging informatics system for diagnosis and treatment planning.
The medical imaging technologies have been used for detecting tumors through the years. Tumors that can be viewed in imaging are usually big enough to contain billion tumor cells. Some patients may be cured if detected earlier and the surgery is performed well. Those lead to molecular imaging and image-guided surgery research activities, which post new challenges on large scale imaging data management and 3-D visualization. The goal of this project is to develop 3-D imaging informatics system that can interactively navigate large scale of organ and molecular levels imaging data for early diagnosis and treatment planning. (+info)
Simultaneous storage of medical images in the spatial and frequency domain: a comparative study.
BACKGROUND: Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. METHODS: The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. RESULTS: It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. CONCLUSION: The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient. (+info)
Image compression in morphometry studies requiring 21 CFR Part 11 compliance: procedure is key with TIFFs and various JPEG compression strengths.
This study aims to compare the integrity and reproducibility of measurements created from uncompressed and compressed digital images in order to implement compliance with 21 CFR Part 11 for image analysis studies executed using 21 CFR Part 58 compliant capture systems. Images of a 400-mesh electron microscope grid and H&E stained rat liver tissue were captured on an upright microscope with digital camera using commercially available analysis software. Digital images were stored as either uncompressed TIFFs or in one of five different levels of JPEG compression. The grid images were analyzed with automatic detection of bright objects while the liver images were segmented using color cube-based morphometry techniques, respectively, using commercially-available image analysis software. When comparing the feature-extracted measurements from the TIFF uncompressed to the JPEG compressed images, the data suggest that JPEG compression does not alter the accuracy or reliability to reproduce individual data point measurements in all but the highest compression levels. There is, however, discordance if the initial measure was obtained with a TIFF format and subsequently saved as one of the JPEG levels, suggesting that the use of compression must precede feature extraction. It is a common practice in software packages to work with TIFF uncompressed images. However, this study suggests that the use of JPEG compression as part of the analysis work flow was an acceptable practice for these images and features. Investigators applying image file compression to other organ images will need to validate the utility of image compression in their work flow. A procedure to digitally acquire and JPEG compress images prior to image analysis has the potential to reduce file archiving demands without compromising reproducibility of data. (+info)