The ClariSIGMAM is an innovative breast cancer prediction marker. It is a breast density assessment solution that provides accurate and consistent density estimates from standard digital mammograms. Quantitative breast density is the main indicator in breast cancer screening and diagnosis. The powerful pre-trained deep learning model ensures to make consistent clinical decision marking in an objective and convenient way. Novel Deep Learning Technology provides a fully automated quantification for breast and mammary area and proportion density measurements. With the world’s highest accuracy rate, ClariSIGMAM is convenient with a smart workflow at an affordable cost.
- More than 45% of mammography age women have dense breasts1.
- Mammography, is less than 60% sensitive in dense breasts2.
- Risk of developing breast cancer is 4-6 times greater in extremely dense breasts than fatty breasts3.
- Cancer recurrence is more likely in women with dense breasts4.
- Radiologists overestimate breast density 7-37%5.
 Diagnostic Performance of Digital versus Film mammography for Breast-Cancer Screening, Pisano ED., et al, NEJM, 353;17, October 27, 2005
 Individual and Combined Effects of Age, Breast Density, and Hormone Replacement Therapy Use on the Accuracy of Screening Mammography Ann Intern Med. 2003;138(3):168-175
 Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. McCormack, Valerie A. and dos Santos Silva, Isabel, 6, Jun 2006, Cancer Epidemial Biomarkers Prev, Vol. 15, pp. 1157-1169
 Mammographic density as a predictor of breast cancer outcome. Gertraud Maskarinec, MD, PhD, Christy G. Woolcott, PhD, and Laurence N. Kolonel, MD, PhD, Future Oncol, 2010 Mar; 6(3): 351–354
 Mammographic density measured with quantitative computer-aided method: comparison with radiologists’ estimates and BI-RADS categories. Katherine E. Martin, et al, 2006 Sep;240(3):656-65. doi: 10.1148/radiol.2402041947. Epub 2006 Jul 20.
Precision Analysis of Breast Tissue Composition
- Precisely analyzes fat and glandular tissue composition in mammography with deep learning technology.
- Achieves the world’s highest accuracy rate of 97%
- Confirmed reliability in published papers
Collaboration Between AI and Expert Reader
- Deep learning presents its confidence with color overlay on mammogram
- Readers accept or adjust the density recommendation intuitively and conveniently
- Unique color overlaid report allows easy verification of AI-predicted tissue types
- Assessment available in BI-RADS 5th edition breast density category
Novel Deep Learning Technology Provides
- Fully automated quantification
- Breast Area/Glandular Area/Percent Density
- World’s highest accuracy (97%)
Product Integration and User Convenience
- Fully compliant with DICOM: Compatible with all digital mammography and PACS systems. Fully automated operation requires no separate operator
- Simple Installation and fast operation via GPU computer
- Compatible with multi-vendor FFDM scanners
- Simplifies compliance with breast density notification laws
- Convenient & smart workflow
How It Works
Fully compliant with DICOM standards, ClariSIGMAM allows easy and seamless integration with digital mammography and PACS systems.