Literature DB >> 8988206

Focal hepatic lesions: effect of three-dimensional wavelet compression on detection at CT.

M A Goldberg1, G S Gazelle, G W Boland, P F Hahn, W W Mayo-Smith, M Pivovarov, E F Halpern, J Wittenberg.   

Abstract

PURPOSE: To evaluate the effect of three-dimensional, wavelet-based compression on the detection of focal hepatic lesions at computed tomography (CT).
MATERIALS AND METHODS: CT images obtained in 69 patients with focal hepatic lesions were studied (35 consecutive cases and 34 cases selected to be difficult on the basis of lesion size or contrast). Image data were compressed by means of a three-dimensional, wavelet-based algorIthm at ratios of 10:1, 15:1, and 20:1. Normal and abnormal sections (on original and compressed images) were reviewed by using an interactive workstation. Four readers rated the presence or absence of a lesion with a five-point scale.
RESULTS: At receiver operating characteristic analysis, no statistically significant difference was detected for all cases considered together. Differences approached but did not reach statistical significance for the diagnostic performance of one reader with compressed images (15:1, P = .054; 20:1, P = .051). For the subset of difficult cases, a significant difference was observed with 20:1 compressed images for one reader (P = .026). Diagnostic performance of readers was less certain in normal than in abnormal cases with both original and compressed images (difference was significant for 15:1 [P = .035] and 20:1 [P < .0001] compressed images).
CONCLUSION: Three-dimensional wavelet compression is satisfactory at ratios of at least 10:1. Additional studies with a larger sample would help confirm findings with higher ratios.

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Year:  1997        PMID: 8988206     DOI: 10.1148/radiology.202.1.8988206

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  10 in total

1.  Diagnostic accuracy of film-based, TIFF, and wavelet compressed digital temporomandibular joint images.

Authors:  C J Trapnell; W C Scarfe; J H Cook; A M Silvejra; F J Regennitter; B S Haskell
Journal:  J Digit Imaging       Date:  2000-02       Impact factor: 4.056

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

Authors:  S Terae; K Miyasaka; K Kudoh; T Nambu; T Shimizu; K Kaneko; H Yoshikawa; R Kishimoto; T Omatsu; N Fujita
Journal:  J Digit Imaging       Date:  2000-11       Impact factor: 4.056

3.  Irreversible compression of medical images.

Authors:  Bradley J Erickson
Journal:  J Digit Imaging       Date:  2002-04-30       Impact factor: 4.056

4.  Emergency radiology coverage: technical and clinical feasibility of an international teleradiology model.

Authors:  Arjun Kalyanpur; Joy Weinberg; Vladimir Neklesa; James A Brink; Howard P Forman
Journal:  Emerg Radiol       Date:  2003-07-22

5.  Improved pediatric MR imaging with compressed sensing.

Authors:  Shreyas S Vasanawala; Marcus T Alley; Brian A Hargreaves; Richard A Barth; John M Pauly; Michael Lustig
Journal:  Radiology       Date:  2010-06-07       Impact factor: 11.105

6.  Irreversible JPEG 2000 compression of abdominal CT for primary interpretation: assessment of visually lossless threshold.

Authors:  Kyoung Ho Lee; Young Hoon Kim; Bo Hyoung Kim; Kil Joong Kim; Tae Jung Kim; Hyuk Jung Kim; Seokyung Hahn
Journal:  Eur Radiol       Date:  2006-11-22       Impact factor: 5.315

7.  Image data compression.

Authors:  M A Goldberg
Journal:  J Digit Imaging       Date:  1997-08       Impact factor: 4.056

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

Authors:  Jane P Ko; Jeffrey Chang; Elan Bomsztyk; James S Babb; David P Naidich; Henry Rusinek
Journal:  Radiology       Date:  2005-08-26       Impact factor: 11.105

9.  User interface of a teleradiology system for the MR assessment of multiple sclerosis.

Authors:  G Luccichenti; F Cademartiri; A Pichiecchio; E Bontempi; U Sabatini; S Bastianello
Journal:  J Digit Imaging       Date:  2009-07-15       Impact factor: 4.056

10.  Development of an algorithm to automatically compress a CT image to visually lossless threshold.

Authors:  Chang-Mo Nam; Kyong Joon Lee; Yousun Ko; Kil Joong Kim; Bohyoung Kim; Kyoung Ho Lee
Journal:  BMC Med Imaging       Date:  2018-12-17       Impact factor: 1.930

  10 in total

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