• Title/Summary/Keyword: Digital X-ray mammographic images

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Microcalcification Extraction by Wavelet Transform and Automatic Thresholding (웨이브렛 변환과 자동적인 임계치 설정에 의한 미세 석회화 검출)

  • Won, Chul-Ho;Seo, Yong-Su;Cho, Jin-Ho
    • Journal of Korea Multimedia Society
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    • v.8 no.4
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    • pp.482-491
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    • 2005
  • In this paper, we proposed the microcalcification detection algorithm which is based on wavelet transform and automatic thresholding method in the X-ray mammographic images. Digital X-ray imaging system is essential equipment in the field diagnosis and is widely used in the various fields such as chest, fracture of a bone, and dental correction. Especially, digital X-ray mammographic imaging is known as the most important method to diagnose the breast cancer, many researches to develop the imaging system are processing in country. In this paper, we proposed a microcalcifications detection algorithm necessary in the early phase of breast cancer diagnosis and showed that a algorithm could effectively detect microcalfication and could aid diagnosis-radiologist.

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Microcalcification Detection Based on Region Growing Method with Contrast and Edge Sharpness in Digital X-ray Mammographic Images (명암 대비와 에지 선예도를 이용하는 영역 성장법에 의한 디지털 X선 맘모그램 영상에서의 미세 석회화 검출)

  • Won, C.H.;Kang, S.W.;Cho, J.H.
    • 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.

Technical Advances, Image Quality and Quality Control Regulations in Mammography

  • Ng, Kwan-Hoong
    • 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.

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Microcalcification Extraction by Using Automatic Thredholding Based on Region Growing (영역 성장법을 기반으로 자동적인 임계치 설정을 이용한 미세 석회화 추출)

  • 원철호;권용준;이정현;박희준;임성운;김명남;조진호
    • Journal of Biomedical Engineering Research
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    • v.25 no.4
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    • pp.235-242
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    • 2004
  • In this paper, we proposed the algorithm for detection of microtalcification by automatic threshold decision based on region growing method. The region for optimal threshold is grown from local maximum pixel by increasing repeatedly threshold in microralcification candidate region. Then, the optimal threshold is automatically decided at the maximum value of the contrast and edge sharpness in this region. Microcalcifications could be efficiently detected as satisfied result that true positive ratio is 81.5% and average false positive numbers are 1.1 about total 299 microcalcifirations in real image. In a result, we showed that this algorithm can be used to aid diagnostic-radiologist for the diagnosis of the early phase of breast cancer.