Paper
22 May 2003 Detection in compressed digital mammograms using numerical observers
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Abstract
The objective of this study was to evaluate an image compression technique for digital mammography using a nonprewhitening matched filter with an eye filter (NPWE) and channelized Hotelling numerical observer models. A total of 1024 images were cropped from clinical digital mammograms and used as backgrounds. The images were acquired using a clinical full-field digital mammography (FFDM) system and masses of sizes 30, 40, and 60 pixels (100 μm pixel size) were simulated. In addition, microcalcifications were synthetically extracted from clinical digital mammograms and used in the study. Image compression was achieved using a compression software (JPEG 2000, Aware Inc., Bedford, MA) at compression ratios 1:1, 15:1 and 30:1. The channelized Hotelling observer model was investigated only for the mass type lesions by transforming the images to channel space and computing the Hotelling trace for each compression condition. The NPWE model was investigated for both lesions and micocalcifications at all compression conditions and the detection indices were computed by assuming Gaussian statistics and by the 'percent correct’ detection method. The results of the study indicated a reduction in detection with increased compression for microcalcifications at 30:1 compression while almost no variation in detection index was observed for the simulated masses.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sankararaman Suryanarayanan, Andrew Karellas, Srinivasan Vedantham, Hetal Ved, and Carl J. D'Orsi "Detection in compressed digital mammograms using numerical observers", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); https://doi.org/10.1117/12.480363
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Cited by 8 scholarly publications.
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KEYWORDS
Image compression

Mammography

Digital mammography

Eye

Image filtering

Digital imaging

Medical imaging

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