Effect of image quality on calcification detection in digital mammography

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind; Wallis, Matthew; Chakraborty, Dev P.; Dance, David R.; Bosmans, Hilde; Young, Kenneth C.

doi:10.1118/1.4718571

Cited by 83 publications

(75 citation statements)

References 38 publications

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“…This finding is in accordance with previous observer performance study results [1,11]. However, with the use of a higher energy X-ray spectrum obtained with a W/Ag combination, depiction of microcalcifications improved, due to the increase in detector dose level and associated lower quantum noise level.…”

Section: Discussionsupporting

confidence: 82%

Alternative Exposure Parameters and Post Process Noise Reduction Expect Considerable Dose Reduction in Single Mammography Views—Initial Experience on Mastectomy Specimens

Bluekens¹,

Engen²,

Karssemeijer³

et al. 2013

ABCR

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Objective: To experimentally indicate a lower limit of dose in mammographic imaging yielding adequate image quality for complementary diagnostic views, by evaluation of image series with different exposure parameters and additional image processing on mastectomy specimens with diverse pathology. Methods: Image series were obtained on seven specimens with different target-filter combinations at different exposure values. Three experienced radiologists assessed the lowest acceptable dose level per specimen using a relative grading technique. With the standard image as reference, fibroglandular tissue and pathological structures, including microcalcifications, were evaluated. Subsequently, a series of pixel binning processes was tested and subjectively assessed on the selected images. Results: The lowest dose level at which image quality was acceptable, and achieved with a W/Ag target-filter combination at 32 kV and 4 mAs. These images can be acquired with 10.4% to 22.4% of the average glandular dose in standard images. Post process pixel binning added to the interpretability of such low dose images. Conclusion: This specimen study suggests that dose level of mammography images might be reduced substantially by general application of a W/Ag spectrum, particularly when combined with post process noise reduction. Future studies should focus on the feasibility of this technique in clinical mammography.

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Section: Discussionsupporting

confidence: 82%

Alternative Exposure Parameters and Post Process Noise Reduction Expect Considerable Dose Reduction in Single Mammography Views—Initial Experience on Mastectomy Specimens

Bluekens¹,

Engen²,

Karssemeijer³

et al. 2013

ABCR

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“…It was proposed by Visser et al 7 that premium view increased the suspiciousness of normal and benign structures as well as malignant structures leading to no significant difference in diagnostic accuracy. Also, in the study by Warren et al 10 no significant difference in detection of calcification clusters was found between different image processing algorithms. On the other hand, this result differs from previous work by Zanca et al 6 which had a similar study design.…”

Section: Discussionmentioning

confidence: 90%

“…There have been a number of previous studies investigating the effect of image processing on cancer detection, including both preference studies 2,3 and objective studies. [4][5][6][7][8][9][10] However, the effect of the difference in image appearance resulting from using different image processing algorithms on the detection of the various radiological features of breast cancer is still unclear. The purpose of this work was to perform an observer study to investigate whether the application of different image processing to digital mammograms has a significant impact on the detection of non-calcification cancers.…”

Section: Introductionmentioning

confidence: 99%

Effect of image processing version on detection of non-calcification cancers in 2D digital mammography imaging

Warren

Cooke²,

Given-Wilson

et al. 2013

Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment

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Image processing (IP) is the last step in the digital mammography imaging chain before interpretation by a radiologist. Each manufacturer has their own IP algorithm(s) and the appearance of an image after IP can vary greatly depending upon the algorithm and version used. It is unclear whether these differences can affect cancer detection. This work investigates the effect of IP on the detection of non-calcification cancers by expert observers. Digital mammography images for 190 patients were collected from two screening sites using Hologic amorphous selenium detectors. Eighty of these cases contained non-calcification cancers. The images were processed using three versions of IP from Hologicdefault (full enhancement), low contrast (intermediate enhancement) and pseudo screen-film (no enhancement). Seven experienced observers inspected the images and marked the location of regions suspected to be non-calcification cancers assigning a score for likelihood of malignancy. This data was analysed using JAFROC analysis. The observers also scored the clinical interpretation of the entire case using the BSBR classification scale. This was analysed using ROC analysis. The breast density in the region surrounding each cancer and the number of times each cancer was detected were calculated. IP did not have a significant effect on the radiologists' judgment of the likelihood of malignancy of individual lesions or their clinical interpretation of the entire case. No correlation was found between number of times each cancer was detected and the density of breast tissue surrounding that cancer.

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“…The threshold gold thickness is compared to European Standards [8] to determine if a system meets the minimum and achievable image quality standards. It has been shown that the threshold gold thickness measured with the CDMAM phantom is predictive of calcification detection [7,8], and, to a lesser extent, mass detection [8]. Studies have investigated if the CDMAM curves from raw images can be predicted from CDMAM curves with processed images [9].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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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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Effect of image quality on calcification detection in digital mammography

Abstract: Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection.

Cited by 83 publications

References 38 publications

Alternative Exposure Parameters and Post Process Noise Reduction Expect Considerable Dose Reduction in Single Mammography Views—Initial Experience on Mastectomy Specimens

Alternative Exposure Parameters and Post Process Noise Reduction Expect Considerable Dose Reduction in Single Mammography Views—Initial Experience on Mastectomy Specimens

Effect of image processing version on detection of non-calcification cancers in 2D digital mammography imaging

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

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