Digital Mammography: Development of an Advanced Computer-Aided System for Breast Cancer Detection

2004 ◽  
Author(s):  
Heang P. Chan
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Digital Mammography ◽  
Breast Cancer Detection ◽  
Computer Aided ◽  
Advanced Computer

IMAGE PROCESSING AND COMPUTER AIDED DIAGNOSIS IN DIGITAL MAMMOGRAPHY: A CLINICAL PERSPECTIVE

1993 ◽  
Vol 07 (06) ◽  
pp. 1493-1503 ◽  
Author(s):  
ETTA D. PISANO ◽  
FAINA SHTERN
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Digital Mammography ◽  
Computer Aided Diagnosis ◽  
Breast Cancer Detection ◽  
Digital Systems ◽  
Computer Assisted ◽  
Computer Aided ◽  
Aided Diagnosis

Mammographic technology has improved dramatically in the last two decades. The advent of digitally acquired mammograms offers the possibility of further improvements in early breast cancer detection. Specifically, digital acquisition systems decouple the process of X-ray photon detection from image display by using a primary detector that directly quantifies transmitted photons. Digital systems also allow a wide dynamic range so that a wider range of tissue contrast can be appreciated. Digital systems have the capacity to bring revolutionary advantages to breast cancer detection and management (1) image processing for increased lesion conspicuity; (2) computer-aided diagnosis for enhanced radiologic interpretation; (3) teleradiology, or image transmission, as a means of bringing world-class expertise to community hospitals and remote areas; (4) improved image access and communication through digital image archiving and transmission; and (5) dynamic, or “real time” imaging for use during biopsy and localization procedures. In this article, the authors review the literature 011 the use of image processing and computer assisted diagnosis for digital mammography. Future research goals in the development of digital mammography are also discussed.

scholarly journals Methods Used in Computer-Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review

2020 ◽  
Vol 2020 ◽  
pp. 1-21 ◽  
Author(s):  
Saleem Z. Ramadan
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
The United States ◽  
Computer Aided Diagnosis ◽  
Current Level ◽  
Breast Cancer Detection ◽  
Cad Systems ◽  
Computer Aided ◽  
Detection And Diagnosis ◽  
Aided Diagnosis

According to the American Cancer Society’s forecasts for 2019, there will be about 268,600 new cases in the United States with invasive breast cancer in women, about 62,930 new noninvasive cases, and about 41,760 death cases from breast cancer. As a result, there is a high demand for breast imaging specialists as indicated in a recent report for the Institute of Medicine and National Research Council. One way to meet this demand is through developing Computer-Aided Diagnosis (CAD) systems for breast cancer detection and diagnosis using mammograms. This study aims to review recent advancements and developments in CAD systems for breast cancer detection and diagnosis using mammograms and to give an overview of the methods used in its steps starting from preprocessing and enhancement step and ending in classification step. The current level of performance for the CAD systems is encouraging but not enough to make CAD systems standalone detection and diagnose clinical systems. Unless the performance of CAD systems enhanced dramatically from its current level by enhancing the existing methods, exploiting new promising methods in pattern recognition like data augmentation in deep learning and exploiting the advances in computational power of computers, CAD systems will continue to be a second opinion clinical procedure.

scholarly journals Diagnostic accuracy of contrast-enhanced digital mammography in breast cancer detection in comparison to tomosynthesis, synthetic 2D mammography and tomosynthesis combined with ultrasound in women with dense breast

2020 ◽  
pp. 20201046
Author(s):  
Rashmi Sudhir ◽  
Kamala Sannapareddy ◽  
Alekya Potlapalli ◽  
Pooja Boggaram Krishnamurthy ◽  
Suryakala Buddha ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Digital Mammography ◽  
Characteristic Curve ◽  
Breast Cancer Detection ◽  
Dense Breast ◽  
Breast Clinic ◽  
Data Set ◽  
Iodinated Contrast ◽  
Contrast Enhanced

Objective: To assess the diagnostic efficacy of contrast-enhanced digital mammography (CEDM) in breast cancer detection in comparison to synthetic two-dimensional mammography (s2D MG), digital breast tomosynthesis (DBT) alone and DBT supplemented with ultrasound examination in females with dense breast with histopathology as the gold-standard. Methods: It was a prospective study, where consecutive females presenting to symptomatic breast clinic between April 2019 and June 2020 were evaluated with DBT. Females who were found to have heterogeneously dense (ACR type C) or extremely dense (ACR type D) breast composition detected on s2D MG were further evaluated with high-resolution breast ultrasound and thereafter with CEDM, but before the core biopsy or surgical excision, were included in the study. s2D MG was derived from post-processing reconstruction of DBT data set. Females with pregnancy, renal insufficiency or prior allergic reaction to iodinated contrast agent were excluded from the study. Image interpretation was done by two experienced breast radiologists and both were blinded to histological diagnosis. Results: This study included 166 breast lesions in130 patients with mean age of 45 ± 12 years (age range 24–72 years). There were 87 (52.4%) malignant and 79 (47.6%) benign lesions. The sensitivity of CEDM was 96.5%, significantly higher than synthetic 2D MG (75.6%, p < 0.0001), DBT alone (82.8%, p < 0.0001) and DBT + ultrasound (88.5%, p = 0.0057); specificity of CEDM was 81%, significantly higher than s2D MG (63.3%, p = 0.0002) and comparable to DBT alone (84.4%, p = 0.3586) and DBT + ultrasound (79.7%, p = 0.4135). In receiver operating characteristic curve analysis, the area under the curve was of 0.896 for CEDM, 0.841 for DBT + ultrasound, 0.769 for DBT alone and 0.729 for s2D MG. Conclusion: CEDM is an accurate diagnostic technique for cancer detection in dense breast. CEDM allowed a significantly higher number of breast cancer detection than the s2D MG, DBT alone and DBT supplemented with ultrasonography in females with dense breast. Advances in knowledge: CEDM is a promising novel technology with higher sensitivity and negative predictive value for breast cancer detection in females with dense breast in comparison to DBT alone or DBT supplemented with ultrasound.

Derivative-based feature saliency for computer-aided breast cancer detection and diagnosis

1996 ◽  
Author(s):  
William E. Polakowski ◽  
Steven K. Rogers ◽  
Dennis W. Ruck ◽  
Richard A. Raines ◽  
Jeffrey W. Hoffmeister
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Cancer Detection ◽  
Feature Saliency ◽  
Computer Aided ◽  
Detection And Diagnosis
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