• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.367-369
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• 2005

In this paper, we present a new method for the detection of spiculation on digital mammograms. Traditional methods have defects; sensitive to noise, fixed size processing, and long processing time, however, the proposed method has merits; not sensitive to noise, adaptive size processing, and fast processing time. Experimental results show that the spiculation detection performance of the proposed method is improved much compared to the other methods.

• 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.83 no.5
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• pp.1090-1103
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• 2022

Purpose To evaluate the diagnostic performance of digital breast tomosynthesis (DBT) with the two-dimensional synthesized mammogram (2DSM), compared to full-field digital mammography (FFDM), for suspicious microcalcifications in the breast ahead of stereotactic biopsy and to assess the diagnostic image visibility of the images. Materials and Methods This retrospective study involved 189 patients with microcalcifications, which were histopathologically verified by stereotactic breast biopsy, who underwent DBT with 2DSM and FFDM between January 8, 2015, and January 20, 2020. Two radiologists assessed all cases of microcalcifications based on Breast Imaging Reporting and Data System (BI-RADS) independently. They were blinded to the histopathologic outcome and additionally evaluated lesion visibility using a fivepoint scoring scale. Results Overall, the inter-observer agreement was excellent (0.9559). Under the setting of category 4A as negative due to the low possibility of malignancy and to avoid the dilution of malignancy criteria in our study, McNemar tests confirmed no significant difference between the performances of the two modalities in detecting microcalcifications with a high potential for malignancy (4B, 4C, or 5; p = 0.1573); however, the tests showed a significant difference between their performances in detecting microcalcifications with a high potential for benignancy (4A; p = 0.0009). DBT with 2DSM demonstrated superior visibility and diagnostic performance than FFDM in dense breasts. Conclusion DBT with 2DSM is superior to FFDM in terms of total diagnostic accuracy and lesion visibility for benign microcalcifications in dense breasts. This study suggests a promising role for DBT with 2DSM as an accommodating tool for stereotactic biopsy in female with dense breasts and suspicious breast microcalcifications.

• Journal of Sensor Science and Technology
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• v.13 no.1
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• pp.56-65
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• 2004

In this paper, we proposed the detection algorithm of microcalcification based on region growing method with contrast and edge sharpness in digital X-ray mammographic images. We extracted the local maximum pixel and watershed regions by using watershed algorithm. Then, we used the mean slope between local maximum and neighborhood pixels to extract microcalcification candidate pixels among local maximum pixels. During increasing threshold value to grow microcalcification region, at the maximum threshold value of the contrast and edge sharpness, the microcalcification area is decided. The regions of which area of grown candidate microcalfication region is larger than that of watershed region are excluded from microcalcifications. We showed the diagnosis algorithm can be used to aid diagnostic-radiologist in the early detection breast cancer.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.5 s.311
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• pp.80-88
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• 2006

In this paper we developed a novel system for automatic detection of mass type breast cancer on dense digital mammogram images. The new approaches presented in this paper are as follows: 1) we presented a method that stably decides the mass center and radius without being affected by image signal irregularity. 2) We developed a radial directional filter that is suitable to process mass image signal. 3) And we developed the multiple feature function based on mass shape spiculation, mass center homogeneity, and mass eccentricity, so as to determine mass-type breast cancer. When the proposed system is applied to dense mammographic images, the true 기arm rate is improved by 10% over a conventional system while the false alarm is increased by 1 per image.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.142-145
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• 1995

스크린-필름 X선 유방조영술(Screen-film X-ray mammography)은 유방암 진단을 위한 기준이 되는 방법으로 독보적인 위치를 차지하고 있다. 그러나 현재 사용되는 스크린-필름 방식 유방조영술은 여러 가지 한계점들이 인식되어 왔으며, 만약 유방 X선 사진(mammogram)이 디지탈 형식으로 곧 바로 얻어진다면 영상의 질(image quality)과 방사선량의 감소 가능성 관점에서 향상될 수 있다는 증거가 있다. 본 논문에서는, 디지탈 유방조영술에 대한 논리적 근거가 제시되고, 스크린 대용으로 개발되고 있는 X-선 검출기들과 이들을 사용한 여러가지 디지탈 유방조영술 시스템들을 분석 전망한다. 디지털 유방조영술을 실용화하기 위해 해결되어야 할 문제점들이 논의된다.

• 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 Korea Multimedia Society
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• v.13 no.5
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• pp.702-709
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• 2010

The performance of mass segmentation is greatly influenced by an initial position of a mass. Some researchers performed mass segmentation with the initial position of a mass given by radiologists. The purpose of our research is to find the initial position for mass segmentation and to notify the segmented mass to radiologists without any additional information on mammograms. The proposed system consists of breast segmentation by region growing and opening operations, decision of an initial seed with characteristics of masses, and mass segmentation by a level set segmentation. A seed for mass segmentation is set based on mass scoring measure calculated by block-based variances and masked information in a sub-sampled mammogram. We used a DDSM database to evaluate the system. The accuracy of mass detection is 78% sensitivity at 4 FP/image, and it reached 92% if multiple views for masses were considered.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1273-1284
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• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.