• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.600-603
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• 2003

Energy spectrum modulation of X-ray source in digital mammography has been studied. In this study, we calculated various filtered spectra using the scattering data. Primary spectra were generated by Molybdenum (Mo) and Tungsten (W) targets. The materials of added filters are Molybdenum and Rhodium (Rh) for 40 kVp Mo. primary spectrum, the amounts of photons over whole energy ranges are attenuated to 0.43 with 0.03 mm Mo filter and 0.38 with 0.06 mm Mo filter while the photons of energy ranged from 17 keV to 20 keV. The photons of low energy ranged below 17 keV are considerably attenuated. This effect brings out reducing the scattered radiation and dose to the patient, and enhancing subject contrast in the image. The results show that filtered spectra are not seriously affected by X-ray tube loadability. Because the energy range from 17 keV to 20 keV is directly transmitted although low and high energies are mainly filtered.

• Journal of radiological science and technology
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• v.26 no.2
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• pp.29-35
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• 2003

The purpose of this study was to compare the compression force and thickness of the compressed breast between mediolateral oblique and craniocaudal mammography. This population consisted of 204 paired mediolateral oblique and craniocaudal mammography obtained on one mammographic unit by certified mammography technologists during 2 month period. The women examined were $30{\sim}59$ years old with breast implants, the patients were classified into 3 groups according to age, $30{\sim}39$, $40{\sim}49$, and $50{\sim}59$, prior breast cancer, mastectomy or breast deformity were excluded. The digital readout of compressed breast compression force and thickness was recorded. Mammographic positioning was assessed using standard criteria. The mean compression force of the compressed breast on the craniocaudal projection was less than the mean compression force on the mediolateral projection(14 versus 13.88 daN, p<0.05). The mean thickness of the compressed breast for mediolateral projection was 41.46 mm and that for the craniocaudal projection was 39.50 mm(p<0.05). The compressed breast is higher or thicker on mediolateral oblique than on craniocaudal mammography.

• Journal of the Korean Society of Radiology
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• v.8 no.1
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• pp.27-33
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• 2014

Medical imaging has increased rapidly in the increase of interest in health, with the development of computer technology, digitization of medical imaging is rapidly advancing, PACS has been introduced to the medical field. Increase in the production of medical images by these phenomena made increased the workload of radiologist who must read a medical image. in response to the need for secondary diagnosis using a computer, The term of CAD in medical radiology field was introduced. In this study, we have proposed a CAD algorithm for the interpretation of the image obtained by the digital X-ray mammography equipment. The experiments were performed by programmed in Visual C++ for the proposed algorithm. A result of the execution of the CAD algorithm seven sample images, the results of five samples was confirmed in breast cancer and benign tumors, both the images sample was error processing. If you use a program that implements this with the algorithm proposed in this study it is helpful to reading breast images, and it is considered to contribute significantly to the early detection of breast cancer.

• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.283-294
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• 2005

The Center for Imaging Human Structures (CIH) was established in December 2002 to develop new diagnostic imaging techniques and to make them available to the greater community of biomedical and clinical researchers at Sungkyunkwan University. CIH has been involved in 5 specific activities to provide solutions for early diagnosis and improved treatment of human diseases. The five area goals include: 1) development of a digital mammography system with computer aided diagnosis (CAD); 2) development of digital radiological imaging techniques; 3) development of unified medical solutions using 3D image fusion; 4) development of multi-purpose digital endoscopy; and, 5) evaluation of new imaging systems for clinical application

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.291-299
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• 2006

A Computer-Aided Diagnosis system has been examined to reduce the effort of radiologist. In this paper, we propose the algorithm using Support Vector Machine(SVM) classifier to discriminate whether microcalcifications are malignant or benign tumors. The proposed method to detect microcalcifications is composed of two detection steps each of which uses SVM classifier. The coarse detection step finds out pixels considered high contrasts comparing with neighboring pixels. Then, Region of Interest(ROI) is generated based on microcalcification characteristics. The fine detection step determines whether the found ROIs are microcalcifications or not by merging potential regions using obtained ROIs and SVM classifier. The proposed method is specified on Korean mammogram database. The experimental result of the proposed algorithm presents robustness in detecting microcalcifications than the previous method using Artificial Neural Network as classifier even when using small training data.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.33-40
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• 2002

In this paper, we proposed a lossless compression algorithm of medical images which is essential technique in picture archive and communication system. Mammographic image and magnetic resonance image in among medical images used in this study, proposed a region growing segmentation algorithm for compression of these images. A proposed algorithm was partition by three sub region which error image, discontinuity index map, high order bit data from original image. And generated discontinuity index image data and error image which apply to a region growing algorithm are compressed using JBIG(Joint Bi-level Image experts Group) algorithm that is international hi-level image compression standard and proper image compression technique of gray code digital Images. The proposed lossless compression method resulted in, on the average, lossless compression to about 73.14% with a database of high-resolution digital mammography images. In comparison with direct coding by JBIG, JPEG, and Lempel-Ziv coding methods, the proposed method performed better by 3.7%, 7.9% and 23.6% on the database used.

• Journal of Breast Cancer
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• v.21 no.4
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• pp.453-462
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• 2018

Purpose: This study aimed to compare the diagnostic performance of contrast-enhanced digital mammography (CEDM) and contrast-enhanced magnetic resonance imaging (CEMRI) in preoperative evaluations, and to evaluate the effect of each modality on the surgical management of women with breast cancer. Methods: This single-center, prospective study was approved by the Institutional Review Board, and informed consent was obtained from all patients. From November 2016 to October 2017, 84 patients who were diagnosed with invasive carcinoma (69/84) and ductal carcinoma in situ (15/84), and underwent both CEDM and CEMRI, were enrolled. Imaging findings and surgical management were correlated with pathological results and compared. The diagnostic performance of both modalities in the detection of index and secondary cancers (multifocality and multicentricity), and occult cancer in the contralateral breast, was compared. The authors also evaluated whether CEDM or CEMRI resulted in changes in the surgical management of the affected breast due to imaging-detected findings. Results: Eighty-four women were included in the analysis. Compared with CEMRI, CEDM demonstrated a similar sensitivity (92.9% [78/84] vs. 95.2% [80/84]) in detecting index cancer (p=0.563). For the detection of secondary cancers in the ipsilateral breast and occult cancer in the contralateral breast, no significant differences were found between CEDM and CEMRI (p=0.999 and p=0.999, respectively). Regarding changes in surgical management, CEDM resulted in similar changes compared with CEMRI (30.9% [26/84] vs. 29.7% [25/84], p=0.610). Regarding changes in surgical management due to false-positive findings, no significant differences were found between CEDM and CEMRI (34.6% [9/26] vs. 44.0% [11/25], p=0.782). Conclusion: CEDM demonstrated a diagnostic performance comparable with CEMRI in depicting index cancers, secondary cancers, and occult cancer in the contralateral breast. CEDM demonstrated similar changes in surgical management compared with CEMRI.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.483-491
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• 2016

The conditions after exposure to digital mammography and digital breast tomosynthesis were analyzed. The examinations for the ACR phantom were done using manual exposure, not auto exposure, to examine image discrimination and patient dose. As a result, the following results were derived: In the CC exposure, the kVp was 2kVp higher while mAs decreased to 58.6% for the 3D tomography. Such result showed an approximate decrease of 60mAs. At that time, the patients' Average Glandular Dose (AGD) was 1.65mGy in 2D and 1.87mGy in 3D; thus, AGD of 3D was shown to have about 1.13times higher. The result of the manual exposure revealed a reduced mAs of up to 80%; there was no effect in the assessment standard in terms of image discrimination, resulting in more than 10 points. When mAs was reduced to 80% in the manual exposure for ACR phantom, AGD was decreased to 0.66mGy. The diagnostic values of images were maintained and patients dose was reduced in the manual exposure in the AEC condition for 3D. Since the use of 3D has recently increased, using the manual exposure has been recommended in this study to improve the diagnostic value, while, simultaneously reducing patients dose.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.165-172
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• 2009

According to the American Cancer Society, breast cancer is the second largest cause of cancer deaths and most frequently diagnosed cancer in women. The currently most popular method for early detection of breast cancer is the digital mammography. A mass or calcification lesion has been known as the most important clue for the diagnosis. In this paper, we propose a diagnosis approach based on fuzzy cluster knowledge base. We combine different two sources of feature data in duel OFUN-NET and produce the diagnosis result with possibility degree. We also present the experimental results on the dataset of mass and calcification lesions extracted from the public real world mammogram database DDSM. These results show higher classification accuracy than conventional methods and the feasibility as a decision supporting tool for diagnosis of digital mammogram.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.13-17
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• 2016

In this study, standard model of medical radiation dosage quality control system will be suggested and the useful of this system in clinical field will be reviewed. Radiation dosage information of modalities are gathered from digital imaging and communications in medicine(DICOM) standard data(such as DICOM dose SR and DICOM header) and stored in database. One CT scan, two digital radiography modalities and two mammography modalities in one health promotion center in Seoul are used to derive clinical data for one month. After 1 months research with 703 CT scans, the study shows CT $357.9mGy{\cdot}cm$ in abdomen and pelvic CT, $572.4mGy{\cdot}cm$ in brain without CT, $55.9mGy{\cdot}cm$ in calcium score/heart CT, screening CT at $54mGy{\cdot}cm$ in chest screening CT(low dose screening CT scan), $284.99mGy{\cdot}cm$ in C-spine CT and $341.85mGy{\cdot}cm$ in L-spine CT as health promotion center reference level of each exam. And with 1955 digital radiography cases, it shows $274.0mGy{\cdot}cm2$ and for mammography 6.09 mGy is shown based on 536 cases. The use of medical radiation shall comply with the principles of justification and optimization. This quality management of medical radiation exposure must be performed in order to follow the principle. And the procedure to reduce the radiation exposure of patients and staff can be achieved through this. The results of this study can be applied as a useful tool to perform the quality control of medical radiation exposure.