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PubMed2004

Spatially adaptive high-resolution image reconstruction of DCT-based compressed images.

The problem of recovering a high-resolution image from a sequence of low-resolution DCT-based compressed observations is considered in this paper. The introduction of compression complicates the recovery problem. We analyze the DCT quantization noise and propose to model it in the spatial domain as a colored Gaussian process. This allows us to estimate the quantization noise at low bit-rates without explicit knowledge of the original image frame, and we propose a method that simultaneously estimates the quantization noise along with the high-resolution data. We also incorporate a nonstationary image prior model to address blocking and ringing artifacts while still preserving edges. To facilitate the simultaneous estimate, we employ a regularization functional to determine the regularization parameter without any prior knowledge of the reconstruction procedure. The smoothing functional to be minimized is then formulated to have a global minimizer in spite of its nonlinearity by enforcing convergence and convexity requirements. Experiments illustrate the benefit of the proposed method when compared to traditional high-resolution image reconstruction methods. Quantitative and qualitative comparisons are provided.

Algorithms↗
PubMed2003

Optimization of wavelet decomposition for image compression and feature preservation.

A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

Algorithms↗
PubMed2006

An ultra-low-power image compressor for capsule endoscope.

BACKGROUND: Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam. METHODS: We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture. CONCLUSION: As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.

Algorithms↗
PubMed2004

Probabilistic design analysis of the influence of material property on the human cervical spine.

Studies reported previously in the literature have described the importance of material variation on the cervical responses and have examined some effects by varying the material properties, but there is no systematic approach using statistical methods to understand the influence of material variation on a cervical spine model under a full range of loading conditions, especially under compression and anterior and posterior shear. A probabilistic design system based on Monte Carlo simulation methods using Latin hypercube sampling techniques is used to analyze the material sensitivity of a C4-C6 cervical spine model involving 13 uncertain input parameters on the biomechanical responses and disc annulus stresses under compression, anterior shear, posterior shear, flexion, extension, lateral bending, and axial rotation. The loading types and range of values were as follows: compression, 0-1 mm; anterior shear, 0-2 mm; posterior shear, 0-3.5 mm; flexion, extension, lateral bending, and axial rotation. 0-1.8 Nm with 73.6-N preload. For each case, the load-deflection and key stress values at various spinal components were captured after each load step. The model was also validated under the same conditions. The minimum and maximum predicted responses were within the range of the experimental data. Ignoring compression loading, the combined effects on the biomechanical responses of the cervical ligaments under the remaining loads are enormous. Their total impacts are almost equal to or slightly less than the influence of disc annulus. Results show that the fiber mechanical properties did not have a significant effect on the compressive stiffness. This study reveals important features that help us identify the critical input parameters and enable us to reduce the development time of a patient-specific biomechanical model.

Biomechanical Phenomena↗
PubMed2003

Wavelet compression of low-dose chest CT data: effect on lung nodule detection.

PURPOSE: To assess the effect of using a lossy Joint Photographic Experts Group standard for wavelet image compression, JPEG2000, on pulmonary nodule detection at low-dose computed tomography (CT). MATERIALS AND METHODS: One hundred sets of lung CT data ("cases") were compressed to 30:1, 20:1, and 10:1 levels by using a wavelet-based JPEG2000 method, resulting in 400 test cases. Each case consisted of nine 1.25-mm sections that had been obtained with 20-40 mAs. Four thoracic radiologists independently interpreted the test case images. Performance was measured by using area under the receiver operating characteristic (ROC) curve (Az) and conventional sensitivity and specificity analyses. RESULTS: There were 51 cases with and 49 without lung nodules. Az values were 0.984, 0.988, 0.972, 0.921, respectively, for original and 10:1, 20:1, and 30:1 compressed images. Az values decreased significantly at 30:1 (P =.014) but not at 10:1 compression, with a trend toward significant decrease at 20:1 (P =.051). Specificity values were unaffected by compression (>98.0% at all compression levels). Sensitivity values were 86.3% (176 of 204 test cases with nodules), 77.9% (159 of 204 cases), 76.5% (156 of 204 cases), and 70.1% (143 of 204 cases), respectively, for original and 10:1, 20:1, and 30:1 compressed images. Results of logistic regression model analysis confirmed the significant effects of compression rate and nodule attenuation, size, and location on sensitivity (P <.05). CONCLUSION: While no reduction in nodule detection at 10:1 compression levels was demonstrated by using ROC analysis, a significant decrease in sensitivity was identified. Further investigation is needed before widespread use of image compression technology in low-dose chest CT can be recommended.

Humans↗
PubMed1988

The pathogenesis of spinal epidural abscess: microangiographic studies in an experimental model.

An experimental model of spinal epidural abscess was developed in rabbits by injecting Staphylococcus aureus into the posterior thoracolumbar epidural space. This model has been shown to reproduce the neurological, bacteriological, and radiological aspects of the human disease. In this study, the effect of the infectious epidural mass on the vasculature of the spinal cord in paraplegic rabbits was studied using microangiographic techniques. The normal vascular anatomy of the rabbit spinal cord was defined in control experiments. Vascular proliferation was demonstrated in the epidural space surrounding the abscesses. Anterior and paired posterior spinal arteries remained patent in paraplegic rabbits with mild or moderate spinal cord compression and in some cases of severe compression. In animals with severe compression, the anterior epidural venous plexus remained patent, but the dorsal spinal vein was occluded. Occlusion of perforating arteries occurred only with extreme spinal cord compression. These data indicate that the initial neurological deficit associated with experimental spinal epidural abscess is not due to vascular thrombosis.

Abscess↗
PubMed2000

Wavelet compression on detection of brain lesions with magnetic resonance imaging.

The purpose of this report is to assess clinically acceptable compression ratios on the detection of brain lesions at magnetic resonance imaging (MRI). Four consecutive T2-weighted and the corresponding T1-weighted images obtained in 20 patients were studied for 109 anatomic sites including 50 with lesions and 59 without lesions. The images were obtained on a 1.5-T MR unit with a pixel size of 0.9 to 1.2 x 0.47 mm and a section thickness of 5 mm. The image data were compressed by wavelet-based algorithm at ratios of 20:1, 40:1, and 60:1. Three radiologists reviewed these images on an interactive workstation and rated the presence or absence of a lesion with a 50 point scale for each anatomic site. The authors also evaluated the influence of pixel size on the quality of image compression. At receiver operating characteristic (ROC) analysis, no statistically significant difference was detected at a compression ratio of 20:1. A significant difference was observed with 40:1 compressed images for one reader (P = .023), and with 60:1 for all readers (P = .001 to .012). A root mean squared error (RMSE) was higher in 0.94- x 0.94-mm pixel size images than in 0.94- x 0.47-mm pixel size images at any compression ratio, indicating compression tolerance is lower for the larger pixel size images. The RMSE, subjective image quality, and error images of 10:1 compressed 0.94- x 0.94-mm pixel size images were comparable with those of 20:1 compressed 0.94- x 0.47-mm pixel size images. Wavelet compression can be acceptable clinically at ratios as high as 20:1 for brain MR images when a pixel size at image acquisition is around 1.0 x 0.5 mm, and as high as 10:1 for those with a pixel size around 1.0 x 1.0 mm.

Algorithms↗
PubMed2003

Upload capacity and time-to-display of an image Web system during simultaneous up- and download processes.

The aim of this study was to assess the up- and download performance of an image Web system (IWS) during simultaneous up- and download procedures. Following preparatory tests, the upload capacity (UC) with and without simultaneous download and the time-to-display (TTD) with and without simultaneous upload were determined for different image, server and compression types, and with up to 16 concurrent clients. The UC varied between 1.7-5.5 Gigabyte per hour (GB/h) and was slightly influenced by a simultaneous download; however, the TTDs were substantially prolonged during an upload and only below 5 s with up to four to six concurrent clients. The choice of image and server type had a strong impact on UC and TTD. Lossy primary compression proved slightly superior. An effective UC of approximately 4.0 GB/h or 96 Gigabyte per day (GB/day) can be achieved, which appears suitable even for large institutions. Because of its substantial influence on UC and TTD during simultaneous up- and download, the server hardware should be equipped with two processors and 1 GB RAM. Lossy primary compression may be used with slight performance benefits when full-resolution images are not required. The upload is a time-demanding process, and it is possible that during peak hours the waiting times are unacceptable for clinicians.

Data Compression↗
PubMed2006

Enhanced real-time ECG coder for packetized telecardiology applications.

A new real-time compression method for electrocardiogram (ECG) signals has been developed based on the wavelet transform approach. The method is specifically adaptable for packetized telecardiology applications. The signal is segmented into beats and a beat template is subtracted from them, producing a residual signal. Beat templates and residual signals are coded with a wavelet expansion. Compression is achieved by selecting a subset of wavelet coefficients. The number of selected coefficients depends on a threshold which has different definitions depending on the operational mode of the coder. Compression performance has been tested using a subset of ECG records from MIT-BIH Arrhythmia database. This method has been designed for real-time packetized telecardiology scenarios both in wired and wireless environments.

Algorithms↗
PubMed2005

Motion-JPEG2000 codec compensated for interlaced scanning videos.

This paper presents an implementation scheme of Motion-JPEG2000 (MJP2) integrated with invertible deinterlacing. In previous work, we developed an invertible deinterlacing technique that suppresses the comb-tooth artifacts which are caused by field interleaving for interlaced scanning videos, and affect the quality of scalable frame-based codecs, such as MJP2. Our technique has two features, where sampling density is preserved and image quality is recovered by an inverse process. When no codec is placed between the deinterlacer and inverse process, the original video is perfectly reconstructed. Otherwise, it is almost completely recovered. We suggest an application scenario of this invertible deinterlacer for enhancing the sophisticated signal-to-noise ratio scalability in the frame-based MJP2 coding. The proposed system suppresses the comb-tooth artifacts at low bitrates, while enabling the quality recovery through its inverse process at high bitrates within the standard bitstream format. The main purpose of this paper is to present a system that yields high quality recovery for an MJP2 codec. We demonstrate that our invertible deinterlacer can be embedded into the discrete.wavelet transform employed in MJP2. As a result, the energy gain factor to control rate-distortion characteristics can be compensated for optimal compression. Simulation results show that the recovery of quality is improved by, for example, more than 2.0 dB in peak signal-to-noise ratio by applying our proposed gain compensation when decoding 8-bit grayscale Football sequence at 2.0 bpp.

Algorithms↗
PubMed2005

Wavelet-based compression of M-FISH images.

Multiplex fluorescence in situ hybridization (M-FISH) is a recently developed technology that enables multi-color chromosome karyotyping for molecular cytogenetic analysis. Each M-FISH image set consists of a number of aligned images of the same chromosome specimen captured at different optical wavelength. This paper presents embedded M-FISH image coding (EMIC), where the foreground objects/chromosomes and the background objects/images are coded separately. We first apply critically sampled integer wavelet transforms to both the foreground and the background. We then use object-based bit-plane coding to compress each object and generate separate embedded bitstreams that allow continuous lossy-to-lossless compression of the foreground and the background. For efficient arithmetic coding of bit planes, we propose a method of designing an optimal context model that specifically exploits the statistical characteristics of M-FISH images in the wavelet domain. Our experiments show that EMIC achieves nearly twice as much compression as Lempel-Ziv-Welch coding. EMIC also performs much better than JPEG-LS and JPEG-2000 for lossless coding. The lossy performance of EMIC is significantly better than that of coding each M-FISH image with JPEG-2000.

Algorithms↗
PubMed2004

Super-resolution reconstruction of compressed video using transform-domain statistics.

Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video may not be effective when applied to compressed video because they do not incorporate the compression process into their models. The compression process introduces quantization error, which is the dominant source of error in some cases. In this paper, we propose a stochastic framework where quantization information as well as other statistical information about additive noise and image prior can be utilized effectively.

Algorithms↗
PubMed2005

Effect of water storage, thermocycling, the incorporation and site of placement of glass-fibers on the flexural strength of veneering composite.

OBJECTIVES: To evaluate the effects of water storage, thermocycling, and the incorporation of glass-fibers, on the flexural strength of veneering composites. METHODS: Veneering composites with different fillers, matrices and polymerization methods (Belleglass Kerr Inc., Orange, CA, USA; Sculpture, Pentron Inc. Wallingford CT, USA; Sinfony, 3M Espe, Seefeld, Germany; SR Adoro LC and HP, Targis, Ivoclar Vivadent, Schaan, Liechtenstein), a glass-fiber framework material (Vectris Pontic VP, Ivoclar Vivadent) and a direct restorative composite control (Tetric Ceram, Ivoclar Vivadent) were selected. For the first part of the study, 30 bar specimens (25 x 2 x 2 mm3) per material were fabricated. Ten were stored for 24 h and 10 for 14 days in water at 37 degrees C. Ten were thermocycled (3000 x; 5-50-5 degrees C). Three-point bending tests (crosshead speed: 0.5 mm/min) were performed. For the second part of the study, all veneering materials were combined with a glass-fiber framework (VP). Sixty specimens were produced for each material (25 x 4 x 2 mm3) and treated as in the first part. Three-point bend tests were performed with the reinforcing glass-fiber framework either on the tension or the compression side. Data was evaluated by ANOVA and Weibull analysis. RESULTS: A decrease in flexural strength was observed after water storage or thermocycling for all veneering materials tested. None of the tested materials exhibited significant advantages compared to the control. The flexural strength of glass-fiber reinforced frameworks was ten times higher and not influenced by water storage or thermocycling. A significant reinforcing effect from glass fibers was observed when they were placed on the tension but not when placed on the compression side. SIGNIFICANCE: A glass-fiber framework on the tension side significantly improved the flexural strength of veneering composites. There was less deterioration due to water storage and thermocycling with the glass-fiber reinforced veneering composite compared to the non-reinforced materials.

Bisphenol A-Glycidyl Methacrylate↗
PubMed2005

A compressed domain scheme for classifying block edge patterns.

Detecting and classifying edge components in images find a wide range of applications from perceptually improved coding schemes to content-based searches. In this paper, a fast and systematic scheme is proposed to classify the edge orientation of each block in discrete cosine transform (DCT)-compressed images. Derived from a simple, but acceptable, pixel-domain algorithm, the proposed scheme performs directly on DCT coefficient domain and, thus, saves the arithmetic operations by a considerable amount. The performance of the proposed method is validated by the experiments against various natural images.

Algorithms↗
PubMedDate not supplied

Joint thresholding and quantizer selection for compression of medical ultrasound images in the wavelet domain.

This paper introduces a simple and efficient technique for compression of medical ultrasound (US) images in the wavelet domain. The statistics of subband wavelet coefficients are modelled using the generalized Gaussian distribution (GGD). By exploiting these statistics, a uniform scalar quantizer is designed which adapts very well to the changing statistics of the signal across various subbands and scales. To increase the quantization performance, a threshold is chosen adaptively to zero-out the insignificant wavelet coefficients in the detail subbands before quantization. A distinctive feature of the proposed technique is that it unifies the two approaches to image adaptive coding: rate-distortion (R-D) optimized quantizer selection and R-D optimal thresholding, in order to increase the compression performance of the coder. The operational R-D criterion used for joint optimization is derived in the minimum description length (MDL) framework. The experimental results show that the joint R-D optimization leads to significant improvement in the compression performance of the proposed coder, named JTQ-WV, over the best state-of-the-art image coder, SPIHT. For example, the coding of US images at 0.25 bpp by JTQ-WV yields a PSNR gain of 1.0 dB over the benchmark SPIHT.

Algorithms↗
PubMed2002

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).

Algorithms↗
PubMed2005

Effect of CT image compression on computer-assisted lung nodule volume measurement.

PURPOSE: To evaluate the effect of two-dimensional wavelet-based computed tomographic (CT) image compression according to the Joint Photographic Experts Group (JPEG) 2000 standard on computer-assisted assessment of nodule volume. MATERIALS AND METHODS: This HIPAA-compliant study was approved by the research board at the authors' institution; patients' informed consent was not required. Fifty-one nodules in 23 patients (seven men, 16 women; mean age, 59 years; age range, 39-75 years) were selected on low-dose CT scans that were compressed to levels of 10:1, 20:1, 30:1, and 40:1 by using a two-dimensional JPEG 2000 wavelet-based image compression method. Nodules were classified according to size (< or = 5 mm or > 5 mm in diameter), location (central, peripheral, or abutting pleura or fissures), and attenuation (solid, calcified, or subsolid). Regions of interest were placed on the original images and transposed onto compressed images. Nodule volumes on original (noncompressed) and compressed images were measured by using a computer-assisted method. A mixed-model analysis of variance was conducted for statistical evaluation. RESULTS: Nodule volumes averaged 388.1 mm3 (range, 34-3474 mm3). There were three calcified, 33 solid noncalcified, and 15 subsolid nodules (13 with ground-glass attenuation). Average volume decreased with increasing compression level, to 383 mm3 (10:1), 370 mm3 (20:1), 360 mm3 (30:1), and 354 mm3 (40:1). No significant difference was identified between measurements obtained on original images and those compressed to a level of 10:1. Significant differences were noted, however, between original images and those compressed to a level of 20:1 or greater (P < .05). Compression level significantly interacted with nodule size, location, and attenuation (P < .001). The effect of compression was greater for nodules with ground-glass attenuation than for those with higher attenuation values. The difference in mean volumes between original images and those compressed to a level of 20:1 was 34.9 mm3 for nodules with ground-glass attenuation, compared with 8.3 mm3 for higher-attenuation nodules, a 4.2-fold difference. CONCLUSION: Nodule volumes measured on images compressed to a level of 20:1 differed significantly from those measured on noncompressed images, especially for nodules with ground-glass attenuation. This difference could affect the assessment of nodule change in size as measured with computer-assisted methods.

Adult↗