Interpretation of Digital Mammograms: Comparison of Speed and Accuracy of Soft-Copy versus Printed-Film Display

Pisano, Etta D.; Cole, Elodia B.; Kistner, Emily O.; Muller, Keith E.; Hemminger, Bradley M.; Brown, Mary Louise; Johnston, Richard; Kuzmiak, Cherie M.; Braeuning, M. Patricia; Freimanis, Rita I.; Soo, Mary Scott; Baker, Jay A.; Walsh, Ruth

doi:10.1148/radiol.2232010704

Cited by 85 publications

(59 citation statements)

References 9 publications

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“…In addition, these results are in agreement with our previous evaluation of displays (also including a medical-grade grayscale display) using images obtained with CR [17], as well as the evaluation of capture devices (including standard CR) visualized using a medical-grade grayscale display. Previous studies have compared film-screen mammography to digitized films [9][10][11], and similar to the present study, these reports found no significant differences in diagnostic accuracy. In our study, we obtained AUC mean values that were similar to the values reported by Powell [9], Gitlin et al [10], and Pisano et al [11].…”

Section: Discussionsupporting

confidence: 89%

“…Previous studies have compared film-screen mammography to digitized films [9][10][11], and similar to the present study, these reports found no significant differences in diagnostic accuracy. In our study, we obtained AUC mean values that were similar to the values reported by Powell [9], Gitlin et al [10], and Pisano et al [11]. However, these previous studies did not evaluate digital cameras and low-cost displays.…”

Section: Discussionsupporting

confidence: 89%

“…Specialized equipment is available for digitizing mammogram films, and several studies have confirmed their clinical equivalence to film-screen mammography [9][10][11]. However, similar to CR, these specialized digitizers also remain unaffordable for rural areas in developing countries, and digital cameras are therefore being utilized for teleradiology services.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Low-Cost Telemammography Screening Configurations: A Comparison with Film-Screen Readings in Vulnerable Areas

et al. 2014

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The aim of this study was to evaluate the diagnostic accuracy for detecting breast cancer using different telemammography configurations, including combinations of both low-cost capture devices and consumer-grade color displays. At the same time, we compared each of these configurations to film-screen readings. This study used a treatment-by-reader-by-case factorial design. The sample included 70 mammograms with 34 malignant cases. The readers consisted of four radiologists who classified all of the cases according to the categories defined by the Breast Imaging Reporting and Data System (BI-RADS). The evaluated capture devices included a specialized film digitizer and a digital camera, and the evaluated displays included liquid crystal display (LCD) and light-emitting diode (LED) consumer-grade color displays. Receiver operating characteristic curves, diagnostic accuracy (measured as the area under these curves), accuracy of the composition classification, sensitivity, specificity, and the degree of agreement between readers in the detection of malignant cases were also evaluated. Comparisons of diagnostic accuracy between film-screen and the different combinations of digital configurations showed no significant differences for nodules, calcifications, and asymmetries. In addition, no differences were observed in terms of sensibility or specificity when the degree of malignancy using the film-screen method was compared to that provided with digital configurations. Similar results were observed for the classification of breast composition. Furthermore, all observed reader agreements of malignant detection between film-screen and digital configurations were substantial. These findings indicate that the evaluated digital devices showed comparable diagnostic accuracy to the reference treatment (film-screen).

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Section: Discussionsupporting

confidence: 89%

Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

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Evaluation of Low-Cost Telemammography Screening Configurations: A Comparison with Film-Screen Readings in Vulnerable Areas

et al. 2014

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“…Both hard-and software of mammography review stations has improved significantly over the last few years. Dedicated mammography review stations now allow to switch almost instantaneously between different image layouts including a sequential magnified quadrant zoom, with softcopy reading speed approaching or even surpassing that of batch film reading [56,57]. Viewing the entire image piece by piece in full resolution may be tedious, but necessary to ensure that no microcalcifications are overlooked.…”

Section: Impact On Workflowmentioning

confidence: 99%

Digital mammography: what do we and what don’t we know?

Bick

Diekmann

2007

Eur Radiol

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“…In breast imaging, resolution is an important factor for diagnosing lesions on digital or digitized mammograms [9] [10] [11] [12]. In recent years, 4 K or 8 K diagnostic displays have come to be implemented; in particular, high-resolution displays are currently favored for mammography [13].…”

Section: Introductionmentioning

confidence: 99%

Super-Resolution Imaging of Mammograms Based on the Super-Resolution Convolutional Neural Network

Umehara¹,

Ota²,

Ishida³

2017

OJMI

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Purpose: To apply and evaluate a super-resolution scheme based on the super-resolution convolutional neural network (SRCNN) for enhancing image resolution in digital mammograms. Materials and Methods: A total of 711 mediolateral oblique (MLO) images including breast lesions were sampled from the Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM). We first trained the super-resolution convolutional neural network (SRCNN), which is a deep-learning based super-resolution method. Using this trained SRCNN, high-resolution images were reconstructed from low-resolution images. We compared the image quality of the super-resolution method and that obtained using the linear interpolation methods (nearest neighbor and bilinear interpolations). To investigate the relationship between the image quality of the SRCNN-processed images and the clinical features of the mammographic lesions, we compared the image quality yielded by implementing the SRCNN, in terms of the breast density, the Breast Imaging-Reporting and Data System (BI-RADS) assessment, and the verified pathology information. For quantitative evaluation, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were measured to assess the image restoration quality and the perceived image quality. Results: The super-resolution image quality yielded by the SRCNN was significantly higher than that obtained using linear interpolation methods (p < 0.001). The SRCNN-processed image quality in dense breasts, high-risk BI-RADS assessment groups, and pathology-verified malignant cases were significantly higher than that in low-density breasts, low-risk BI-RADS assessment groups, and benign cases, respectively (p < 0.01). Conclusion: SRCNN can significantly outperform conventional interpolation methods for enhancing image resolution in digital mammography. SRCNN can significantly improve the image quality of magnified mammograms, especially in dense breasts, high-risk How to cite this paper:

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Interpretation of Digital Mammograms: Comparison of Speed and Accuracy of Soft-Copy versus Printed-Film Display

Abstract: Interpretation with soft-copy display is likely to be useful with digital mammography and is unlikely to significantly change accuracy or speed.

Cited by 85 publications

References 9 publications

Evaluation of Low-Cost Telemammography Screening Configurations: A Comparison with Film-Screen Readings in Vulnerable Areas

Evaluation of Low-Cost Telemammography Screening Configurations: A Comparison with Film-Screen Readings in Vulnerable Areas

Digital mammography: what do we and what don’t we know?

Super-Resolution Imaging of Mammograms Based on the Super-Resolution Convolutional Neural Network

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