Literature DB >> 14534807

Visually lossless threshold determination for microcalcification detection in wavelet compressed mammograms.

O Kocsis1, L Costaridou, L Varaki, E Likaki, C Kalogeropoulou, S Skiadopoulos, G Panayiotakis.   

Abstract

The aim of this study was to determine the visually lossless threshold of a wavelet-based compression algorithm in case of microcalcification cluster detection in mammography. The threshold was determined by means of observer performance using a set of digitized mammograms. In addition, the transfer characteristics of the compression algorithm were assessed by means of image-quality parameters using computer-generated test images. The observer performance study was based on rating performed by four independent radiologists, who reviewed 68 mammograms, from the Digital Database for Screening Mammography (DDSM), at six different compression ratios. Receiver operating characteristics (ROC) analysis was performed on observers' responses and the area under ROC curve (A(z)) was calculated at each compression ratio for each observer. The parameters used for assessment of transfer characteristics of the compression algorithm were input/output response, noise, high-contrast response, and low-contrast-detail response. The computer-generated test image, used for this assessment, mimicked mammographic image characteristics (pixel size, pixel depth, and noise) as well as microcalcification characteristics (size and contrast). The ROC analysis for microcalcification cluster detection indicated a threshold at compression ratio 40:1, as Student's t-test shows statistically significant differences in A(z) values (p<0.05) for compression ratios 70:1 and 100:1. Observers' grading of mammogram quality lowers this threshold at 25:1. Low-contrast-detail detectability in the transfer characteristics study indicate a threshold of 35:1, whereas non-perceptibility of image-quality-parameters degradation lowers this threshold to 30:1. The ROC and transfer characteristics analysis provided comparable thresholds, indicating the potential use of the latter in limiting the target range of compression ratios for subsequent observer studies.

Mesh:

Year:  2003        PMID: 14534807     DOI: 10.1007/s00330-003-1826-7

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  22 in total

1.  Medical image compression based on a morphological representation of wavelet coefficients.

Authors:  N C Phelan; J T Ennis
Journal:  Med Phys       Date:  1999-08       Impact factor: 4.071

2.  Performance analysis of a new semiorthogonal spline wavelet compression algorithm for tonal medical images.

Authors:  S K Thompson; J D Hazle; D F Schomer; A A Elekes; D A Johnston; J Huffman; C K Chui
Journal:  Med Phys       Date:  2000-02       Impact factor: 4.071

3.  Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation.

Authors:  R M Slone; D H Foos; B R Whiting; E Muka; D A Rubin; T K Pilgram; K S Kohm; S S Young; P Ho; D D Hendrickson
Journal:  Radiology       Date:  2000-05       Impact factor: 11.105

4.  A tool for designing digital test objects for module performance evaluation in medical digital imaging.

Authors:  O Kocsis; L Costaridou; E P Efstathopoulos; D Lymberopoulos; G Panayiotakis
Journal:  Med Inform Internet Med       Date:  1999 Oct-Dec

5.  Using component technologies for web based wavelet enhanced mammographic image visualization.

Authors:  P Sakellaropoulos; L Costaridou; G Panayiotakis
Journal:  Med Inform Internet Med       Date:  2000 Jul-Sep

6.  A protocol-based evaluation of medical image digitizers.

Authors:  E P Efstathopoulos; L Costaridou; O Kocsis; G Panayiotakis
Journal:  Br J Radiol       Date:  2001-09       Impact factor: 3.039

7.  Receiver operating characteristic (ROC) analysis: basic principles and applications in radiology.

Authors:  A R van Erkel; P M Pattynama
Journal:  Eur J Radiol       Date:  1998-05       Impact factor: 3.528

8.  A review of mammography test objects for the calibration of resolution, contrast, and exposure.

Authors:  C Kimme-Smith; L W Bassett; R H Gold
Journal:  Med Phys       Date:  1989 Sep-Oct       Impact factor: 4.071

9.  Clinical evaluation of irreversible data compression for computed radiography of the chest.

Authors:  K Egashira; H Nakata; H Watanabe; K Uchida; K Nakamura; Y Ishino; K Horino; R Yoshikawa
Journal:  J Digit Imaging       Date:  1998-11       Impact factor: 4.056

10.  Screen film vs full-field digital mammography: image quality, detectability and characterization of lesions.

Authors:  S Obenauer; S Luftner-Nagel; D von Heyden; U Munzel; F Baum; E Grabbe
Journal:  Eur Radiol       Date:  2002-03-19       Impact factor: 5.315

View more
  3 in total

1.  ACR-AAPM-SIIM practice guideline for determinants of image quality in digital mammography.

Authors:  Kalpana M Kanal; Elizabeth Krupinski; Eric A Berns; William R Geiser; Andrew Karellas; Martha B Mainiero; Melissa C Martin; Samir B Patel; Daniel L Rubin; Jon D Shepard; Eliot L Siegel; Judith A Wolfman; Tariq A Mian; Mary C Mahoney
Journal:  J Digit Imaging       Date:  2013-02       Impact factor: 4.056

2.  Full-field digital mammography image data storage reduction using a crop tool.

Authors:  Bong Joo Kang; Sung Hun Kim; Yeong Yi An; Byung Gil Choi
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-06-10       Impact factor: 2.924

3.  Quantitative visually lossless compression ratio determination of JPEG2000 in digitized mammograms.

Authors:  Verislav T Georgiev; Anna N Karahaliou; Spyros G Skiadopoulos; Nikos S Arikidis; Alexandra D Kazantzi; George S Panayiotakis; Lena I Costaridou
Journal:  J Digit Imaging       Date:  2013-06       Impact factor: 4.056

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.