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The effects of gray scale image processing on digital mammography interpretation performance
Authors:Cole Elodia B  Pisano Etta D  Zeng Donglin  Muller Keith  Aylward Stephen R  Park Sungwook  Kuzmiak Cherie  Koomen Marcia  Pavic Dag  Walsh Ruth  Baker Jay  Gimenez Edgardo I  Freimanis Rita
Institution:Department of Radiology and Lineberger Comprehensive Cancer Center, University of North Carolina, CB#7515, Radiology Research Labs, 106 Mason Farm Road, Chapel Hill, NC 27599, USA.
Abstract:RATIONALE AND OBJECTIVES: To determine the effects of three image-processing algorithms on diagnostic accuracy of digital mammography in comparison with conventional screen-film mammography. MATERIALS AND METHODS: A total of 201 cases consisting of nonprocessed soft copy versions of the digital mammograms acquired from GE, Fischer, and Trex digital mammography systems (1997-1999) and conventional screen-film mammograms of the same patients were interpreted by nine radiologists. The raw digital data were processed with each of three different image-processing algorithms creating three presentations-manufacturer's default (applied and laser printed to film by each of the manufacturers), MUSICA, and PLAHE-were presented in soft copy display. There were three radiologists per presentation. RESULTS: Area under the receiver operating characteristic curve for GE digital mass cases was worse than screen-film for all digital presentations. The area under the receiver operating characteristic for Trex digital mass cases was better, but only with images processed with the manufacturer's default algorithm. Sensitivity for GE digital mass cases was worse than screen film for all digital presentations. Specificity for Fischer digital calcifications cases was worse than screen film for images processed in default and PLAHE algorithms. Specificity for Trex digital calcifications cases was worse than screen film for images processed with MUSICA. CONCLUSION: Specific image-processing algorithms may be necessary for optimal presentation for interpretation based on machine and lesion type.
Keywords:Digital mammography  ROC curve  image processing
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