• Korean Journal of Digital Imaging in Medicine
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• v.16 no.2
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• pp.25-29
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• 2014

The full-field digital mammography (FFDM), which has been known as a digital breast imaging system, carries out more outstanding performance than the screen-film mammography in overall image quality, skin & nipple, description of pectoral muscle and expression of micro-calcification. Thus, in this thesis, I perform experiments for both the enhancement of image quality and accurate estimation of the result in question, when detecting the very tiny-sized lesions in mammography. The image of digital breast X-rays is the important diagnostic tool for detecting early breast cancer and micro calcification lesion. The experiment of how much compression rate has an effect on the result of diagnosis in the case of microcalcification lesion, with JPEG2000 40:1 compression and over 50% enlargement led to obscure or definitely unacceptable diagnostic results is performed. And in another study of assessment of PSNR degree. I recognized the importance of standardized management system in mammography, where not to mention the accurate reading of the image has the most crucial role in diagnosis

• Journal of the Korean Society of Radiology
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• v.9 no.1
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• pp.61-65
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• 2015

Mammography equipment is an essential detector for making an early diagnosis of female's breast lesion. Recently, in most hospitals, a digital mammography detector is used due to the wide and consistent supply of digital mammography equipment. However, the average effective radiation is increasing due to the indiscreet use of CR or DR mammography. The purpose of this study is to recognize the possible indirect radiation damage, which can be occurred due to an excessive effective exposure of radiation, by evaluating spacial radiation rate of the digital mammography detector used for female patient. Consequently, the high mount of spacial radiation showed digital mammography equipment on the horizontal direction. Considering the result, digital mammography equipment should be installed by avoiding along the horizontal direction.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6177-6186
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• 2015

Sensitivity and specificity are the two most important indicators in selection of medical imaging devices for cancer screening. Breast images taken by conventional or digital mammography, ultrasound, MRI and optical mammography were collected from 2,143,852 patients. They were then studied and compared for sensitivity and specificity results. Optical mammography had the highest sensitivity (p<0.001 and p<0.006) except with MRI. Digital mammography had the highest specificity for breast cancer imaging. A comparison of specificity between digital mammography and optical mammography was significant (p<0.021). If two or more breast diagnostic imaging tests are requested the overall sensitivity and specificity will increase. In this literature review study patients at high-risk of breast cancer were studied beside normal or sensitive women. The image modality performance of each breast test was compared for each.

• Journal of radiological science and technology
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• v.30 no.1
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• pp.13-23
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• 2007

In recent years, mammography system is changed rapidly from conventional screen-film system to digital system for application to screening and diagnosis. Digital mammography system provides several advantages over screen-film mammography system. According to the information provided by the manufacturer, digital mammography system offers radiation dose reduction in comparison with screen-film mammography system, because of digital detector, particularly direct digital detector has higher x-ray absorption efficiency than screen-film combination or imaging plate(IP). We measured average glandular doses(AGD) in screen-film mammography(SFM) system with slow screen-film combination, computed mammography(CM) system, indirect digital mammography(IDM) system and direct digital mammography(DDM) system using brest tissue-equivalent phantom(glandularity 30%, 50% and 70%). The results were shown as follows : AGD values for DDM system were highest than those for other systems. Although automatic exposure control(AEC) mode was selected, the curve of the AGD values against thickness or glandularity increased significantly for the SFM system with the uniform target/filter(Mo/Mo) combination. Therefore, the AGD values for the high energy examinations were highest in the SFM system, and those for the low energy examinations were highest in the DDM system. But the curve of the AGD values against thickness and glandularity increased gently for CM system with the automatic selection of the target/filter combination (from Mo/Mo to Mo/Rh or from Mo/Rh to Rh/Rh), and the AGD values were lowest. Consequently, the parameters in mammography for each exposure besides detection efficiency play an important role in oder to estimate a patient radiation dose.

• Journal of radiological science and technology
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• v.35 no.4
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• pp.293-298
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• 2012

In digital mammography, Exposure factor were automatically chosen using by measurement breast thickness and the density of mammary gland. It may cause a increase glandular dose. The purpose of this study was to investigate optimal image quality in digital magnification mammography to decrease radiation exposure of patient dose. Auto mode gives the best image quality however, AGD showed better image quality. Image quality of manual mode passed phantom test and SNR at 55% mAs of auto mode commonly used in the digital magnification mammography. Also it could reduce AGD. According to result, manual mode may reduce the unnecessary radiation exposure in digital magnification mammography.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.38-41
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• 2002

Mammography is considered the single most important diagnostic tool in the early detection of breast cancer. Today's dedicated mammographic equipment, specially designed x-ray screen/film combinations, coupled with controlled film processing, produces excellent image quality and can detect very low contrast small lesions. In mammography, it is most important to produce consistent high-contrast, high-resolution images at the lowest radiation dose consistent with high image quality. Some of the major technical development milestones that have let to today's high quality in mammographic imaging are reviewed. Both the American College of Radiology Mammography Accreditation Program and the Mammography Quality Standards Act have significant impact on the improvement of the technical quality of mammographic images in the United States and worldwide. A most recent development in digital mammography has opened up avenues for improving diagnosis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4578-4589
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• 2011

The technologies of image acquisition, display, and storage of the breast have been developed in their specialized fields in recent years. The image acquisition system is a device that absorbs and stores images after examining breast tissue using X-ray. Due to the specificity and sensitivity of imaging, the early detection of breast cancer is feasible. In this paper, the current technologies for digital mammography are reviewed, and we propose a digital mammography and evaluate the performance of the implemented system.

• Journal of the Korean Society of Radiology
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• v.8 no.4
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• pp.147-153
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• 2014

We tried to assessment about characteristics of image through quantitative evaluation method and qualitative evaluation method in Full Field Digital Mammography. It satisfied an approval standard of ten score regardless of compression ratio measuring detection score after compressing and appling an algorithm of JPEG2000 orJPEG compression targeting ACR accreditation phantom. Also, it was apparent that when we selected and compressed the image of real fine lesion and measured a change of diagnosis ability magnifing over 50 percent after compressing over 20:1 ratio, it had a strong influence on diagnosis ability. We realized that the difference between the original image according to compression ratio measuring a quantitative evaluation which is PSNR,RMSE,MAE and SSIM was relatively allowable.

• Korean Journal of Digital Imaging in Medicine
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• v.12 no.2
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• pp.133-138
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• 2010

The purpose of this study was to survey and test quality control of mammography system. The conclusion of this study is as follows ; First, The rate of pass for phantom image test shows that Film-Screen mammography system(F/S) and computed mammography system(CR) is 80%, Indirect digital mammography system(DR) is 100%. Second, The test of exposure dose shows that F/S is 921 mR. CR is 1,140 mR, DR is 474 mR. The grade of this testament is CR > F/S > DR. Third, The test of average glandular dose shows that F/S is 1,336 mGy, CR is 1,635 mGy, DR is 1,26 mGy. The grade of this testament is CR > F/S > DR. Fourth, The testament of resolution shows as follows F/S is 11~13 Lp/mm, CR is 4~5 Lp/mm, and DR is 5~7 Lp/mm(F/S > DR > CR) Fifth, The survey of projection, cassette, development and reading shows that user are indifference.

• Journal of radiological science and technology
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• v.42 no.1
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• pp.9-17
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• 2019

Although digital mammography is a representative method for breast cancer detection. It has a limitation in detecting and classifying breast tumor due to superimposed structures. Machine learning, which is a part of artificial intelligence fields, is a method for analysing a large amount of data using complex algorithms, recognizing patterns and making prediction. In this study, we proposed a technique to improve the diagnostic accuracy of energy-selective mammography by training data using the machine learning algorithm and using dual-energy measurements. A dual-energy images obtained from a photon-counting detector were used for the input data of machine learning algorithms, and we analyzed the accuracy of predicted tumor thickness for verifying the machine learning algorithms. The results showed that the classification accuracy of tumor thickness was above 95% and was improved with an increase of imput data. Therefore, we expect that the diagnostic accuracy of energy-selective mammography can be improved by using machine learning.