Computer-Aided Detection/Diagnosis in Breast Imaging: A Focus on the Evolving FDA Regulations for Using Software as a Medical Device

2020 ◽  
Vol 8 (6) ◽  
Author(s):  
Tara A. Retson ◽  
Mohammad Eghtedari
Keyword(s):  
Medical Device ◽  
Breast Imaging ◽  
Computer Aided Detection ◽  
Computer Aided ◽  
Fda Regulations

Computer-Aided Detection and Diagnosis for 3D X-Ray Based Breast Imaging

2012 ◽  
pp. 66-85
Author(s):  
Gautam S. Muralidhar ◽  
Alan C. Bovik ◽  
Mia K. Markey
Keyword(s):  
Breast Imaging ◽  
Digital Breast Tomosynthesis ◽  
Future Research ◽  
Computer Aided Detection ◽  
Breast Tomosynthesis ◽  
X Ray ◽  
Computer Aided ◽  
Recent Developments ◽  
Initial Work ◽  
Detection And Diagnosis

The last 15 years has seen the advent of a variety of powerful 3D x-ray based breast imaging modalities such as digital breast tomosynthesis, digital breast computed tomography, and stereo mammography. These modalities promise to herald a new and exciting future for early detection and diagnosis of breast cancer. In this chapter, the authors review some of the recent developments in 3D x-ray based breast imaging. They also review some of the initial work in the area of computer-aided detection and diagnosis for 3D x-ray based breast imaging. The chapter concludes by discussing future research directions in 3D computer-aided detection.

scholarly journals Image processing and machine learning techniques used in computer-aided detection system for mammogram screening - a review

2020 ◽  
Vol 10 (3) ◽  
pp. 2336 ◽  
Author(s):  
Susama Bagchi ◽  
Kim Gaik Tay ◽  
Audrey Huong ◽  
Sanjoy Kumar Debnath
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Imaging ◽  
Breast Cancer Diagnosis ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Computer Aided Detection ◽  
Cad Systems ◽  
Cad System ◽  
Computer Aided

This paper aims to review the previously developed Computer-aided detection (CAD) systems for mammogram screening because increasing death rate in women due to breast cancer is a global medical issue and it can be controlled only by early detection with regular screening. Till now mammography is the widely used breast imaging modality. CAD systems have been adopted by the radiologists to increase the accuracy of the breast cancer diagnosis by avoiding human errors and experience related issues. This study reveals that in spite of the higher accuracy obtained by the earlier proposed CAD systems for breast cancer diagnosis, they are not fully automated. Moreover, the false-positive mammogram screening cases are high in number and over-diagnosis of breast cancer exposes a patient towards harmful overtreatment for which a huge amount of money is being wasted. In addition, it is also reported that the mammogram screening result with and without CAD systems does not have noticeable difference, whereas the undetected cancer cases by CAD system are increasing. Thus, future research is required to improve the performance of CAD system for mammogram screening and make it completely automated.

Sensitivity of a Direct Computer-aided Detection System in Full-field Digital Mammography for Detection of Microcalcifications Not Associated with Mass or Architectural Distortion

2010 ◽  
Vol 61 (3) ◽  
pp. 162-169 ◽  
Author(s):  
Anabel M. Scaranelo ◽  
Pavel Crystal ◽  
Karina Bukhanov ◽  
Thomas H. Helbich
Keyword(s):  
Digital Mammography ◽  
Breast Imaging ◽  
Detection System ◽  
Architectural Distortion ◽  
Computer Aided Detection ◽  
Full Field ◽  
Cad System ◽  
Full Field Digital Mammography ◽  
Significant Difference ◽  
Computer Aided

Purpose The purpose of this study was to evaluate the sensitivity of a direct computer-aided detection (CAD) system (d-CAD) in full-field digital mammography (FFDM) for the detection of microcalcifications not associated with mass or architectural distortion. Materials and Methods A database search of 1063 consecutive stereotactic core biopsies performed between 2002 and 2005 identified 196 patients with Breast Imaging-Reporting and Data System (BI-RADS) 4 and 5 microcalcifications not associated with mass or distortion detected exclusively by bilateral FFDM. A commercially available CAD system (Second Look, version 7.2) was retrospectively applied to the craniocaudal and mediolateral oblique views in these patients (mean age, 59 years; range, 35–84 years). Breast density, location and mammographic size of the lesion, distribution, and tumour histology were recorded and analysed by using χ2, Fisher exact, or McNemar tests, when applicable. Results When using d-CAD, 71 of 74 malignant microcalcification cases (96%) and 101 of 122 benign microcalcifications (83%) were identified. There was a significant difference ( P < .05) between CAD sensitivity on the craniocaudal view, 91% (68 of 75), vs CAD sensitivity on the mediolateral oblique view, 80% (60 of 75). The d-CAD sensitivity for dense breast tissue (American College of Radiology [ACR] density 3 and 4) was higher (97%) than d-CAD sensitivity (95%) for nondense tissue (ACR density 1 and 2), but the difference was not statically significant. All 28 malignant calcifications larger than 10 mm were detected by CAD, whereas the sensitivity for lesions small than or equal to 10 mm was 94%. Conclusions D-CAD had a high sensitivity in the depiction of asymptomatic breast cancers, which were seen as microcalcifications on FFDM screening, with a sensitivity of d-CAD on the craniocaudal view being significantly better. All malignant microcalcifications larger than 10 mm were detected by d-CAD.

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