Cardiac angiography without cine film: Erecting a “Tower of Babel” in the cardiac catheterization laboratory

Nissen, Steven E.; Pepine, Carl J.; Bashore, Thomas M.; Block, Peter C.; Bonchek, Lawrence I.; Brinker, Jeffrey A.; Carabello, Blasé A.; Douglas, John S.; Elion, J; Hirshfeld, John W.; Holmes, David R.; Johnson, Warren L.; Klinke, W. Peter; Levin, David C.; Mancini, G.B. John; Mullins, Charles E.; Thomas, James D.; Topol, Eric J.; Vogel, John H.K.; Wondrow, Merrill A.

doi:10.1016/0735-1097(94)90037-x

Cited by 41 publications

(7 citation statements)

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“…This includes the cost of two cine cameras at about $80,000 each, construction costs for building a dark room and equipping it with an automatic film developer, and the costs of nonrenewable supplies including cine film, storage supplies, and processing chemicals at about $100 per patient [2]. With funds saved from not purchasing this cine film technology, a completely computer-driven multimedia conference room can be fully equipped.…”

Section: Conference Room and Equipment Financingmentioning

confidence: 99%

“…The estimated additional cost of equipping a new digital biplane cardiac catheterization laboratory with 35-mm cine film is about $150,000-200,000 [2,18]. This includes the cost of two cine cameras at about $80,000 each, construction costs for building a dark room and equipping it with an automatic film developer, and the costs of nonrenewable supplies including cine film, storage supplies, and processing chemicals at about $100 per patient [2].…”

Section: Conference Room and Equipment Financingmentioning

confidence: 99%

“…The cineless laboratory is well-established in Europe and is rapidly becoming accepted in the United States [1,2]. Digital angiograms as well as other forms of digital and analog cardiac data can now be shown to a large audience using high-resolution multisync color monitors with diagonal viewing surfaces of 5 ft or larger.…”

Section: Introductionmentioning

confidence: 99%

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Filmless multimedia display following cardiac catheterization

Mathewson

1997

Cathet. Cardiovasc. Diagn.

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Section: Conference Room and Equipment Financingmentioning

confidence: 99%

Section: Conference Room and Equipment Financingmentioning

confidence: 99%

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Filmless multimedia display following cardiac catheterization

Mathewson

1997

Cathet. Cardiovasc. Diagn.

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“…The correlation is then computed as follows: 14,21 N2 2=wflgfl=wg (2) where w and g are vectors and the superscript t refers to the transpose.…”

Section: Description Of Modelsmentioning

confidence: 99%

<title>Effect of image compression in model and human performance</title>

et al. 1999

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We applied three different model observers (non-prewhitening matched filter with an eye filter, Hotelling and channelized Hotelling) to predict the effect ofJPEG image compression on human visual detection of a simulated lesion (clinically known as thrombus) in single fmme digital x-ray coronary angiograms. Since the model observers' absolute performance is better than human, model performance was degraded to match human performance by injecting internal noise proportional to the external noise. All three modelobservers predicted reasonably well the degradation in human performance as a function of JPEG image compression, although the NPWEW and the channelized Hotelling models (with internal noise proportional to the external noise) were better predictors than the Hotelling model.

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“…Mean Square Error (MSE): Most investigators use the Mean Square Error defined as the average square difference between corresponding pixels of the original and processed image as a measure of image quality.5'6'7'8'9 iN MSE=-(Ui-Ci)2 (1) N where U is the grey value of th pixel in the uncompressed image, C is the grey value of the th pixel in the compressed image and N is the total number of pixels in the image. Compression resulting in lower MSE is assumed to result in an image with higher image quality.…”

Section: Introductionmentioning

confidence: 99%

<title>Psychophysical evaluation of the effect of JPEG, full-frame discrete cosine transform (DCT) and wavelet image compression on signal detection in medical image noise</title>

et al. 1995

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Image quality associated with image compression has been either arbitrarily evaluated through visual inspection, loosely defined in terms of some subjective criteria such as image sharpness or blockiness, or measured by arbitrary measures such as the Mean Square Error between the uncompressed and compressed images. The present paper psychophysically evaluated the effect of three different compression algorithms (JPEG, Full-frame and Wavelet) on human visual detection of computer simulated low contrast lesions embedded in real medical image noise from patient coronary angiogram. Performance identifying the signal present location as measured by d' index of detectability decreased for all three algorithms by approximately 30 % and 62 % for the 16: 1 and 30: 1 compression ratios respectively. We evaluated the ability of two previously proposed measures of image quality, Mean Square Error (MSE) and Normalized Nearest Neighbor Difference (NNND), to determine the best compression algorithm. The MSE predicted significant higher image quality for the JPEG algorithm in the 16: 1 compression ratio and for both JPEG and Full-frame for the 30: 1 compression ratio. The NNND predicted significant higher image quality for the Full-frame algorithm for both compression ratios. These findings suggest that these two measures of image quality may lead to erroneous conclusions in evaluations and/or optimizations of image compression algorithms.

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Cardiac angiography without cine film: Erecting a “Tower of Babel” in the cardiac catheterization laboratory

Cited by 41 publications

References 0 publications

Filmless multimedia display following cardiac catheterization

Filmless multimedia display following cardiac catheterization

<title>Effect of image compression in model and human performance</title>

<title>Psychophysical evaluation of the effect of JPEG, full-frame discrete cosine transform (DCT) and wavelet image compression on signal detection in medical image noise</title>

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