&lt;title&gt;Effect of data compression on diagnostic accuracy in digital hand and chest radiography&lt;/title&gt;

Sayre, James W.; Aberle, Denise R.; Boechat, M. Ines; Hall, Theodore R.; Huang, H. K.; Ho, Bruce Kuo Ting; Kashfian, Payam; Rahbar, Guita

doi:10.1117/12.59528

Cited by 22 publications

(7 citation statements)

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“…5 This system has been used in studies detecting several diseases (such as subperiosteal resorption, interstitial lung disease, and pulmonary nodules). [6][7][8] For example, in detecting subtle pulmonary nodules, observer performance was equivalent for compressed and uncompressed images for a compression ratio up to 44. 9 The FDCT scheme apparently does not exhibit the blocking artifacts associated with JPEG because the transformation occurs on the full frame rather than on small, repeated square regions in the frame.…”

Section: Compressionmentioning

confidence: 98%

Compressing and transmitting visible human images

Thoma

Long

1997

IEEE Multimedia

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challenging conventional storage, retrieval, and transmission methods. Here we discuss lossless and lossy methods to compress the images. We also consider advanced transmission-control protocol approaches plus a multisocket technique we developed for transmitting images over wide-area networks.T he National Library of Medicine's Visible Human Project acquired computerized tomography (CT), magnetic resonance imaging (MRI), and color cryosection images of a representative male and female cadaver to start building a digital image library of volumetric data. 1,2 These data sets serve as a common reference point for studying human anatomy, as a set of common public domain data for developing and testing medical imaging algorithms, and as a testbed and model for constructing image libraries accessible through networks. Researchers anticipate that this collection, particularly the color images, will become a data source for many multimedia applications. Examples include "fly through" instructional tutorials for human anatomy, biomechanical modeling software, visualization of lungs and bronchial tree anatomy, vascular anatomy visualization for realtime computation of catheter navigation and model-based surgery guidance, photorealistic volume-rendered anatomical atlases, interactive virtual dissection packages such as the Dissectable Human CD-ROM, an interactive 3D anatomic atlas published by the international health science publisher, Mosby, and many others. 3 More than 700 licensees in 26 countries already use the data sets for these purposes.The cryosection color images were taken by a charge-coupled device (CCD) scanner and captured as 70-mm photographs. In the male data set, 1,871 cross-sectional images exist for each modality, which amounts to about 15 Gbytes. The female data set, consisting of cross-sectional images taken at one-third the interval of the male, amounts to about 40 Gbytes, the total equaling 55 Gbytes. If we digitized the photographs at a resolution (4,096 by 2,700 pixels) exceeding that of the CCD scanner (2,048 by 1,216 pixels), this could deliver additional data to about 62 Gbytes total for the male and 173 Gbytes total for the female, for a combined total of 235 Gbytes.These 24-bits-per-pixel red, green, and blue (RGB) color image data offer the greatest challenges in storage and transmission. Their large sizes preclude rapid transfer over the Internet and distribution by CD-ROM or other optical media. (For example, even the CCD-captured set of 55 Gbytes requires 110 conventional CD-ROMs.) To alleviate this problem, we are investigating different compression techniques and communications methods.Specific research objectives include 1. Studying both lossy and lossless compression to reduce redundancy in the Visible Human color cryosection slice images and to select the most promising combination of parameters for each.2. Developing two compression methods, one lossy and the other lossless, using a combination of approaches. The development will include both compression and expansion software.3. St...

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Section: Compressionmentioning

confidence: 98%

Compressing and transmitting visible human images

Thoma

Long

1997

IEEE Multimedia

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“…This modest compression is often inadequate. Lossy coding does not permit perfect reconstruction of the original image but can provide excellent quality at a fraction of the bit rate [9,26,29,31,40].…”

Section: Zusammenfassungmentioning

confidence: 99%

Image quality in lossy compressed digital mammograms

et al. 1997

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“…Types of processing that have been evaluated include compression [22,21,65,30,6,9,35,56,14], and enhancement (unsharp masking, histogram equalization, and noise reduction).…”

Section: ¥ ¤ ¢mentioning

confidence: 99%

Quality Evaluation for Compressed Medical Images: Fundamentals

Cosman

1994

Handbook of Medical Image Processing and Analysis

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<title>Effect of data compression on diagnostic accuracy in digital hand and chest radiography</title>

Cited by 22 publications

References 0 publications

Compressing and transmitting visible human images

Compressing and transmitting visible human images

Image quality in lossy compressed digital mammograms

Quality Evaluation for Compressed Medical Images: Fundamentals

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