Impact of two types of image processing on cancer detection in mammography

Lucy M. Warren; Mark D. Halling-Brown; Padraig T. Looney; David R. Dance; Louise Wilkinson; Matthew G. Wallis; Rosalind M. Given-Wilson; Julie Cooke; Rita McAvinchey; Kenneth C. Young

doi:10.1117/12.2216384

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24 March 2016 Impact of two types of image processing on cancer detection in mammography

Lucy M. Warren, Mark D. Halling-Brown, Padraig T. Looney, David R. Dance, Louise Wilkinson, Matthew G. Wallis, Rosalind M. Given-Wilson, Julie Cooke, Rita McAvinchey, Kenneth C. Young

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Proceedings Volume 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment; 978704 (2016) https://doi.org/10.1117/12.2216384
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

The impact of image processing on cancer detection is still a concern to radiologists and physicists. This work aims to evaluate the effect of two types of image processing on cancer detection in mammography. An observer study was performed in which six radiologists inspected 349 cases (a mixture of normal cases, benign lesions and cancers) processed with two types of image processing. The observers marked areas they were suspicious were cancers. JAFROC analysis was performed to determine if there was a significant difference in cancer detection between the two types of image processing. Cancer detection was significantly better with the standard setting image processing (flavor A) compared with one that provides enhanced image contrast (flavor B), p = 0.036. The image processing was applied to images of the CDMAM test object, which were then analysed using CDCOM. The threshold gold thickness measured with the CDMAM test object was thinner using flavor A than flavor B image processing. Since Flavor A was found to be superior in both the observer study and the measurements using the CDMAM phantom, this may indicate that measurements using the CDMAM correlate with change in cancer detection with different types of image processing.

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Lucy M. Warren, Mark D. Halling-Brown, Padraig T. Looney, David R. Dance, Louise Wilkinson, Matthew G. Wallis, Rosalind M. Given-Wilson, Julie Cooke, Rita McAvinchey, and Kenneth C. Young "Impact of two types of image processing on cancer detection in mammography", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 978704 (24 March 2016); https://doi.org/10.1117/12.2216384

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