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PubMed2004

Maximum likelihood principal components regression on wavelet-compressed data.

Maximum likelihood principal component regression (MLPCR) is an errors-in-variables method used to accommodate measurement error information when building multivariate calibration models. A hindrance of MLPCR has been the substantial demand on computational resources sometimes made by the algorithm, especially for certain types of error structures. Operations on these large matrices are memory intensive and time consuming, especially when techniques such as cross-validation are used. This work describes the use of wavelet transforms (WT) as a data compression method for MLPCR. It is shown that the error covariance matrix in the wavelet and spectral domains are related through a two-dimensional WT. This allows the user to account for any effects of the wavelet transform on spectral and error structures. The wavelet transform can be applied to MLPCR when using either the full error covariance matrix or the smaller pooled error covariance matrix. Simulated and experimental near-infrared data sets are used to demonstrate the benefits of using wavelets with the MLPCR algorithm. In all cases, significant compression can be obtained while maintaining favorable predictive ability. Considerable time savings were also attained, with improvements ranging from a factor of 2 to a factor of 720. Using the WT-compressed data in MLPCR gave a reduction in prediction errors compared to using the raw data in MLPCR. An analogous reduction in prediction errors was not always seen when using PCR.

Journal Article↗

PubMed2000

American College of Cardiology/European Society of Cardiology International Study of Angiographic Data Compression Phase I: The effect of lossy data compression on recognition of diagnostic features in digital coronary angiography.

OBJECTIVES: This study intended to determine the effect of varying degrees of lossy Joint Photographic Experts Group (JPEG) compression on detection of coronary angiographic features. BACKGROUND: Compression of digital coronary angiograms facilitates playback of images and decreases cost. There are little data on the effect of compression on the accuracy of coronary angiography. METHODS: At six centers, 71 angiographers each reviewed a set of 100 angiographic sequences. The 100 sequences were divided into four, 25-sequence subsets. Each subset of 25 was displayed either as original images or at one of three compression ratios (CRs) (6:1, 10:1 or 16:1). The effect of lossy compression on the sensitivity and specificity for detection of diagnostic features was determined. The effect of compression on subjective measures of image quality graded by the angiographers was also examined. RESULTS: Lossy compression at a ratio of 16:1 decreased the sensitivity for the detection of diagnostic features (76% vs. 80% p = 0.004). The largest effect was in the detection of calcification (52% vs. 63% at 16:1 compression vs. original images, p < 0.001). Subjective indicators of image quality indicated a reduction in confidence in interpretation at CRs of 10:1 and 16:1. CONCLUSIONS: With increased ratios of lossy compression, a degradation of digital coronary angiograms occurs that results in decreased diagnostic accuracy. The sensitivity for detection of common diagnostic features was decreased, and subjective assessment of image quality was impaired. Caution is warranted in the interpretation of coronary angiograms that have been subjected to lossy JPEG compression beyond a ratio of 6:1.

Adult↗

PubMed2000

American College of Cardiology/ European Society of Cardiology international study of angiographic data compression phase I. The effects of lossy data compression on recognition of diagnostic features in digital coronary angiography.

OBJECTIVES: This study intended to determine the effect of varying degrees of lossy Joint Photographic Experts Group (JPEG) compression on detection of coronary angiographic features. Background Compression of digital coronary angiograms facilitates playback of images and decreases cost. There are little data on the effect of compression on the accuracy of coronary angiography. METHODS: At six centers, 71 angiographers each reviewed a set of 100 angiographic sequences. The 100 sequences were divided into four, 25-sequence subsets. Each subset of 25 was displayed either as original images or at one of three compression ratios (CRs) (6:1, 10:1 or 16:1). The effect of lossy compression on the sensitivity and specificity for detection of diagnostic features was determined. The effect of compression on subjective measures of image quality graded by the angiographers was also examined. RESULTS: Lossy compression at a ratio of 16:1 decreased the sensitivity for the detection of diagnostic features (76% vs. 80%P=0.004). The largest effect was in the detection of calcification (52% vs. 63% at 16:1 compression vs. original images, P<0.001). Subjective indicators of image quality indicated a reduction in confidence in interpretation at CRs of 10:1 and 16:1. CONCLUSIONS: With increased ratios of lossy compression, a degradation of digital coronary angiograms occurs that results in decreased diagnostic accuracy. The sensitivity for detection of common diagnostic features was decreased, and subjective assessment of image quality was impaired. Caution is warranted in the interpretation of coronary angiograms that have been subjected to lossy JPEG compression beyond a ratio of 6:1.

Adult↗

PubMed1998

[Study on EEG signals data compression and spikes recognition with wavelet neural network].

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented in this paper. Wavelet network not only can compress data effectively but also can recover original signal. In addition the characteristics of the spikes and the spike-slow rhythm are detected automatically from the time-frequency isoline of EEG signal. This method can be generalized in the field of the electrophysiological signal processing and time-frequency analyzing.

Electroencephalography↗

PubMed1999

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Adult↗

PubMed2000

American College of Cardiology/European Society of Cardiology International Study of Angiographic Data Compression Phase III: measurement of image quality differences at varying levels of data compression.

OBJECTIVES: We sought to investigate up to which level of Joint Photographic Experts Group JPEG) data compression the perceived image quality and the detection of diagnostic features remain equivalent to the quality and detectability found in uncompressed coronary angiograms. BACKGROUND: Digital coronary angiograms represent an enormous amount of data and therefore require costly computerized communication and archiving systems. Earlier studies on the viability of medical image compression were not fully conclusive. METHODS: Twenty-one raters evaluated sets of 91 cine runs. Uncompressed and compressed versions of the images were presented side by side on one monitor, and image quality differences were assessed on a scale featuring six scores. In addition, the raters had to detect pre-defined clinical features. Compression ratios (CR) were 6:1, 10:1 and 16:1. Statistical evaluation was based on descriptive statistics and on the equivalence t-test. RESULTS: At the lowest CR (CR 6:1), there was already a small (15%) increase in assigning the aesthetic quality score indicating "quality difference is barely discernible-the images are equivalent." At CR 10:1 and CR 16:1, close to 10% and 55%, respectively, of the compressed images were rated to be "clearly degraded, but still adequate for clinical use" or worse. Concerning diagnostic features, at CR 10:1 and CR 16:1 the error rate was 9.6% and 13.1%, respectively, compared with 9% for the baseline error rate in uncompressed images. CONCLUSIONS: Compression at CR 6:1 provides equivalence with the original cine runs. If CR 16:1 were used, one would have to tolerate a significant increase in the diagnostic error rate over the baseline error rate. At CR 10:1, intermediate results were obtained.

Adult↗

PubMed2000

American College of Cardiology/ European Society of Cardiology international study of angiographic data compression phase III. Measurement Of image quality differences at varying levels of data compression.

OBJECTIVES: We sought to investigate up to which level of Joint Photographic Experts Group (JPEG) data compression the perceived image quality and the detection of diagnostic features remain equivalent to the quality and detectability found in uncompressed coronary angiograms. BACKGROUND: Digital coronary angiograms represent an enormous amount of data and therefore require costly computerized communication and archiving systems. Earlier studies on the viability of medical image compression were not fully conclusive. METHODS: Twenty-one raters evaluated sets of 91 cine runs. Uncompressed and compressed versions of the images were presented side by side on one monitor, and image quality differences were assessed on a scale featuring six scores. In addition, the raters had to detect pre-defined clinical features. Compression ratios (CR) were 6:1, 10:1 and 16:1. Statistical evaluation was based on descriptive statistics and on the equivalence t -test. Results At the lowest CR (CR 6:1), there was already a small (15%) increase in assigning the aesthetic quality score indicating "quality difference is barely discernible-the images are equivalent.' At CR 10:1 and CR 16:1, close to 10% and 55%, respectively, of the compressed images were rated to be "clearly degraded, but still adequate for clinical use' or worse. Concerning diagnostic features, at CR 10:1 and CR 16:1 the error rate was 9.6% and 13.1%, respectively, compared with 9% for the baseline error rate in uncompressed images. CONCLUSIONS: Compression at CR 6:1 provides equivalence with the original cine runs. If CR 16:1 were used, one would have to tolerate a significant increase in the diagnostic error rate over the baseline error rate. At CR 10:1, intermediate results were obtained.

Adult↗

PubMed2000

American College of Cardiology/European Society of Cardiolgoy International Study of Angiographic Data Compression Phase II: the effects of varying JPEG data compression levels on the quantitative assessment of the degree of stenosis in digital coronary angiography. Joint Photographic Experts Group.

OBJECTIVES: This report describes whether lossy Joint Photographic Experts Group (UPEG) image compression/decompression has an effect on the quantitative assessment of vessel sizes by state-of-the-art quantitative coronary arteriography (QCA). BACKGROUND: The Digital Imaging and Communications in Medicine (DICOM) digital exchange standard for angiocardiography prescribes that images must be stored loss free, thereby limiting JPEG compression to a maximum ratio of 2:1. For practical purposes it would be desirable to increase the compression ratio (CR), which would lead to lossy image compression. METHODS: A series of 48 obstructed coronary segments were compressed/decompressed at CR 1:1 (uncompressed), 6:1, 10:1 and 16:1 and analyzed blindly and in random order using the QCA-CMS analytical software. Similar catheter and vessel start- and end-points were used within each image quartet, respectively. All measurements were repeated after several weeks using newly selected start- and end-points. Three different sub-analyses were carried out: the intra-observer, fixed inter-compression and variable inter-compression analyses, with increasing potential error sources, respectively. RESULTS: The intra-observer analysis showed significant systematic and random errors in the calibration factor at JPEG CR 10:1. The fixed inter-compression analysis demonstrated systematic errors in the calibration factor and recalculated vessel parameter results at CR 16:1 and for the random errors at CR 10:1 and 16:1. The variable inter-compression analysis presented systematic and random errors in the calibration factor and recalculated parameter results at CR 10:1 and 16:1. Any negative effect at CR 6:1 was found only for the calibration factor of the variable inter-compression analysis, which did not show up in the final vessel measurements. CONCLUSIONS: Compression ratios of 10:1 and 16:1 affected the QCA results negatively and therefore should not be used in clinical research studies.

Adult↗

PubMed2000

American College of Cardiology/ European Society of Cardiology international study of angiographic data compression phase II. The effects of varying JPEG data compression levels on the quantitative assessment of the degree of stenosis in digital coronary angiography.

OBJECTIVES: This report describes whether lossy Joint Photographic Experts Group (JPEG) image compression/decompression has an effect on the quantitative assessment of vessel sizes by state-of-the-art quantitative coronary arteriography (QCA). BACKGROUND: The Digital Imaging and Communications in Medicine (DICOM) digital exchange standard for angiocardiography prescribes that images must be stored loss free, thereby limiting JPEG compression to a maximum ratio of 2:1. For practical purposes it would be desirable to increase the compression ratio (CR), which would lead to lossy image compression. METHODS: A series of 48 obstructed coronary segments were compressed/decompressed at CR 1:1 (uncompressed), 6:1, 10:1 and 16:1 and analyzed blindly and in random order using the QCA-CMS analytical software. Similar catheter and vessel start- and end-points were used within each image quartet, respectively. All measurements were repeated after several weeks using newly selected start- and end-points. Three different sub-analyses were carried out: the intra-observer, fixed inter-compression and variable inter-compression analyses, with increasing potential error sources, respectively. RESULTS: The intra-observer analysis showed significant systematic and random errors in the calibration factor at JPEG CR 10:1. The fixed inter-compression analysis demonstrated systematic errors in the calibration factor and recalculated vessel parameter results at CR 16:1 and for the random errors at CR 10:1 and 16:1. The variable inter-compression analysis presented systematic and random errors in the calibration factor and recalculated parameter results at CR 10:1 and 16:1. Any negative effect at CR 6:1 was found only for the calibration factor of the variable inter-compression analysis, which did not show up in the final vessel measurements. CONCLUSIONS: Compression ratios of 10:1 and 16:1 affected the QCA results negatively and therefore should not be used in clinical research studies.

Cardiology↗

PubMed1994

A simple data compression scheme for binary images of bacteria compared with commonly used image data compression schemes.

A run length code compression scheme of extreme simplicity, used for image storage in an automated bacterial morphometry system, is compared with more common compression schemes, such as are used in the tag image file format. These schemes are Lempel-Ziv and Welch (LZW), Macintosh Packbits, and CCITT Group 3 Facsimile 1-dimensional modified Huffman run length code. In a set of 25 images consisting of full microscopic fields of view of bacterial slides, the method gave a 10.3-fold compression: 1.074 times better than LZW. In a second set of images of single areas of interest within each field of view, compression ratios of over 600 were obtained, 12.8 times that of LZW. The drawback of the system is its bad worst case performance. The method could be used in any application requiring storage of binary images of relatively small objects with fairly large spaces in between.

Bacteria↗

PubMed1975

Data compression of large document data bases.

Consideration is given to a document data base that is structured for information retrieval purposes by means of an inverted index and term dictionary. Vocabulary characteristics of various fields are described, and it is shown how the data base may be stored in a compressed form by use of restricted variable length codes that produce a compression not greatly in excess of the optimum that could be achieved through use of Huffman codes. The coding is word oriented. An alternative scheme of word fragment coding is described. It has the advantage that it allows the use of a small dictionary, but is less efficient with respect to compression of the data base.

Computers↗

PubMed2001

ECG data compression using truncated singular value decomposition.

The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal informations are mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that truncated SVD method can provide an efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission. Index Terms-Data compression, electrocardiogram, feature extraction, quasi-periodic signal, singular value decomposition.

Algorithms↗

PubMed1996

Clinical evaluation of irreversible data compression for computed radiography in excretory urography.

Efficient data compression is required for practical daily use of digital images in computed radiography (CR). This study investigated the clinical utility of data compression in excretory urography using the FCR 9000 system (Fuji Photo Film, Tokyo, Japan). Type III data compression technique was used, which can achieve a 20:1 to 25:1 compression ratio. To evaluate the degradation of image quality, we compared paired original and compressed CR images. Although a slight deterioration of image quality was noted in the renal calyx including collecting tubules among various anatomical structures, the difference was not significant. Receiver operating characteristics analysis revealed no significant difference among the original and compressed images. We conclude that compressed CR images using Type III data compression technique in excretory urography appear to be clinically applicable and acceptable.

Adolescent↗

PubMed1989

Comparison of information-preserving and information-losing data-compression algorithms for CT images.

Data compression increases the number of images that can be stored on magnetic disks or tape and reduces the time required for transmission of images between stations. Two algorithms for data compression are compared in application to computed tomographic (CT) images. The first, an information-preserving algorithm combining differential and Huffman encoding, allows reconstruction of the original image. A second algorithm alters the image in a clinically acceptable manner. This second algorithm combines two processes: the suppression of data outside of the head or body and the combination of differential and Huffman encoding. Because the final image is not an exact copy, the second algorithm is information losing. Application of the information-preserving algorithm can double or triple the number of CT images that can be stored on hard disk or magnetic tape. This algorithm may also double or triple the speed with which images may be transmitted. The information-losing algorithm can increase storage or transmission speed by a factor of five. The computation time on this system is excessive, but dedicated hardware is available to allow efficient implementation.

Algorithms↗

PubMed2000

Detection of masses and clustered microcalcifications on data compressed mammograms: an observer performance study.

OBJECTIVE: To evaluate observers' ability to detect breast masses and clustered microcalcifications depicted on data compressed mammograms, an observer performance study was performed. MATERIALS AND METHODS: Eight observers assessed 60 mammographic images obtained in six modes, ranging from noncompressed to a maximum data compression level of 101:1. Observers were asked to rate the images on a scale of 0 to 100 for the likelihood of the presence of a mass and also independently for the likelihood of the presence of clustered microcalcifications. In addition, observers were asked to rate their subjective assessment of the quality of each image for the detection of a mass and separately for the detection of microcalcifications. Receiver operating characteristic analyses were performed. RESULTS: The average area under the receiver operating characteristic curve, A(z), for the detection of clustered microcalcifications decreases significantly at the highest data compression level when compared with the noncompressed and two lowest levels of data compression (p < 0.01), and a trend test of the average area under the receiver operating characteristic curve for all observers is statistically significant (p < 0.05). No statistically significant differences among or between any of the data compression level modes for the detection of masses were detected. CONCLUSION: At a high level of mammogram data compression, observer performance was degraded for the detection of clustered microcalcifications. Detection of masses was not affected by the data compression methods and levels used in this study.

Breast Neoplasms↗

PubMedDate not supplied

Implementation and evaluation of data compression of MR images.

A full-frame bit-allocation technique of data compression has been implemented using the existing computer facilities of an MR imager. Images reconstructed from compressed data files have been compared with the original image and changes in noise and pixel value measured to evaluate any image degradation introduced by the compression process. A 256 x 256 x 8 bit brain image can be compressed in 20 seconds with a compression ratio of greater than 4:1 without significant loss of information.

Head↗

PubMed1995

Classmode: a new data format for real-time multiparameter data analysis and data compression.

A new data acquisition and analysis format (classmode) was developed that allows real-time data classification in a flow cytometer. In our cytometer, detected events were classified in real time by their presence or absence in a set of look-up tables (LUT). A modification of the cytometer hardware allows the exclusive transfer of the LUT data to the acquisition/storage computer. Using a combination of 8 LUTs, the analyzed events can be classified into 256 subpopulations. Real-time data classification results in an increased data transfer rate and a significant compression of the data.

Cells, Cultured↗

PubMed1992

Fast ECG data compression algorithms suitable for microprocessor systems.

ECG data compression techniques have received extensive attention in ECG analysis. Numerous data compression algorithms for ECG signals have been proposed during the last three decades. We describe two algorithms based on the scan-along polygonal approximation algorithm (SAPA) that are suitable for multichannel ECG data reduction on a microprocessor-based system. One represents a modification of SAPA (MSAPA) which adopts the method of integer division table searching to speed up data reduction; the other (CSAPA) combines MSAPA and TP, a turning-point algorithm, to preserve ST segment signals. Results show that our algorithms achieve a compression ratio of more than 5:1 and a percent rms difference (PRD) to the original signal of less than 3.5%. In addition, the maximum execution time of MSAPA for processing one data point is about 50 microseconds. Moreover, the CSAPA algorithm retains all of the details of the ST segment, which are important in ischaemia diagnosis, by employing the TP algorithm.

Algorithms↗