scholarly journals Medical Diagnostic Systems for Breast Cancer

2020 ◽  
Vol 9 (6) ◽  
pp. 945-949
Keyword(s):  
Breast Cancer ◽  
Mortality Rate ◽  
Early Detection ◽  
Low Energy ◽  
Computer Aided Detection ◽  
Human Breast ◽  
Diagnostic Systems ◽  
Cad Systems ◽  
Computer Aided ◽  
Medical Diagnostic

Breast Cancer is one of the diseases where females have the highest mortality rate. Early detection is the way to diminishing the rate and helps increase the lifespan of suffering patients. Mammography is the method of using low energy Xrays for examination and screening the human breast. A team of radiologists required for the analysis of mammograms, but even experienced experts can misjudge in their evaluation.so Computer-Aided Detection (CAD) systems are having more pervasive for the purpose. There are various abnormalities, including micro-calcifications, are identified from mammograms. This study takes a look at all techniques that are helpful in detecting calcification. Several works of literature have been reviewed to explore and learn the outstanding way in different cases and situations for the sensing of classification in cancer of breast.

scholarly journals Article Commentary: Computer-Aided Detection of Breast Cancer — Have All Bases Been Covered?

2008 ◽  
Vol 2 ◽  
pp. BCBCR.S785
Author(s):  
Gautam S. Muralidhar ◽  
Tamara Miner Haygood ◽  
Tanya W. Stephens ◽  
Gary J. Whitman ◽  
Alan C. Bovik ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Full Potential ◽  
Computer Aided Detection ◽  
Cad Systems ◽  
Computer Aided ◽  
Recent Debate ◽  
The Subject ◽  
Intense Research

The use of computer-aided detection (CAD) systems in mammography has been the subject of intense research for many years. These systems have been developed with the aim of helping radiologists to detect signs of breast cancer. However, the effectiveness of CAD systems in practice has sparked recent debate. In this commentary, we argue that computer-aided detection will become an increasingly important tool for radiologists in the early detection of breast cancer, but there are some important issues that need to be given greater focus in designing CAD systems if they are to reach their full potential.

scholarly journals A Research on Computer Aided Detection System for Women Breast Cancer Diagnosis from Digital Mammographic Images

2019 ◽  
Vol 8 (2S11) ◽  
pp. 1008-1014
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Death Rate ◽  
Computational Cost ◽  
Breast Cancer Diagnosis ◽  
Computer Aided Detection ◽  
Cad Systems ◽  
Cad System ◽  
Mammographic Images ◽  
Computer Aided

The Women breast cancer is the most critical cancer that are found in women. Its the second important cause of death in the world. Breast cancer has been ranked number one cancer in Indian females with rates occurrence of 25.8 per 1,00,000 females and death rate 12.7 among 1,00,000. Generally breast cancer is a malignant tumor that begins in the cells of the breast and eventually it spreads to the surrounding tissues. Early detection and diagnosis can reduce the mortality rate. Radiologist misdiagnosis the disease due to technical issues such as imaging quality and human error. Radiologists can improve the performance of Computer Aided Detection/Diagnosis (CAD) systems to finding and discriminating between the normal and abnormal tissues. Breast cancer diagnosis can applied are applied recent CAD systems on imaging modalities such as mammogram, ultrasound, MRI and biopsy histopathological images. CAD system have four stages for diagnosis which are pre-processing, segmentation, Feature Extraction and Classification. CAD system are developed to reduce the time taken to diagnose the breast cancer and reduce the death rate. This paper focus on the survey of CAD system to detect women breast cancer disease from the digital mammographic images to achieve high accuracy and low computational cost.

scholarly journals The efficacy of using computer-aided detection (CAD) for detection of breast cancer in mammography screening: a systematic review

2018 ◽  
Vol 60 (1) ◽  
pp. 13-18 ◽  
Author(s):  
Emilie L Henriksen ◽  
Jonathan F Carlsen ◽  
Ilse MM Vejborg ◽  
Michael B Nielsen ◽  
Carsten A Lauridsen
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
High Volume ◽  
Population Based ◽  
Screening Mammography ◽  
Computer Aided Detection ◽  
Screening Programs ◽  
Significant Difference ◽  
Computer Aided ◽  
Screening Population

Background Early detection of breast cancer (BC) is crucial in lowering the mortality. Purpose To present an overview of studies concerning computer-aided detection (CAD) in screening mammography for early detection of BC and compare diagnostic accuracy and recall rates (RR) of single reading (SR) with SR + CAD and double reading (DR) with SR + CAD. Material and Methods PRISMA guidelines were used as a review protocol. Articles on clinical trials concerning CAD for detection of BC in a screening population were included. The literature search resulted in 1522 records. A total of 1491 records were excluded by abstract and 18 were excluded by full text reading. A total of 13 articles were included. Results All but two studies from the SR vs. SR + CAD group showed an increased sensitivity and/or cancer detection rate (CDR) when adding CAD. The DR vs. SR + CAD group showed no significant differences in sensitivity and CDR. Adding CAD to SR increased the RR and decreased the specificity in all but one study. For the DR vs. SR + CAD group only one study reported a significant difference in RR. Conclusion All but two studies showed an increase in RR, sensitivity and CDR when adding CAD to SR. Compared to DR no statistically significant differences in sensitivity or CDR were reported. Additional studies based on organized population-based screening programs, with longer follow-up time, high-volume readers, and digital mammography are needed to evaluate the efficacy of CAD.

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.

Comparison of two software versions of a commercially available computer-aided detection (CAD) system for detecting breast cancer

2010 ◽  
Vol 51 (5) ◽  
pp. 482-490 ◽  
Author(s):  
Seung Ja Kim ◽  
Woo Kyung Moon ◽  
Soo-Yeon Kim ◽  
Jung Min Chang ◽  
Sun Mi Kim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
False Positive ◽  
Ductal Carcinoma ◽  
Breast Cancers ◽  
Computer Aided Detection ◽  
Full Field ◽  
Cad Systems ◽  
Cad System ◽  
Computer Aided ◽  
Age Range

Background: The performance of the computer-aided detection (CAD) system can be determined by the sensitivity and false-positive marks rate, therefore these factors should be improved by upgrading the software version of the CAD system. Purpose: To compare retrospectively the performances of two software versions of a commercially available CAD system when applied to full-field digital mammograms for the detection of breast cancers in a screening group. Material and Methods: Versions 3.1 and 8.3 of a CAD software system (ImageChecker, R2 Technology) were applied to the full-field digital mammograms of 130 women (age range 36–80, mean age 53 years) with 130 breast cancers detected by screening. Results: The overall sensitivities of the version 3.1 and 8.3 CAD systems were 92.3% (120 of 130) and 96.2% (125 of 130) ( P=0.025), respectively, and sensitivities for masses were 78.3% (36 of 46) and 89.1% (41 of 46) ( P=0.024) and for microcalcifications 100% (84 of 84) and 100% (84 of 84), respectively. Version 8.3 correctly marked five lesions of invasive ductal carcinoma that were missed by version 3.1. Average numbers of false-positive marks per image were 0.38 (0.15 for calcifications, 0.23 for masses) for version 3.1 and 0.46 (0.13 for calcifications, 0.33 for masses) for version 8.3 ( P=0.1420). Conclusion: The newer version 8.3 of the CAD system showed better overall sensitivity for the detection of breast cancer than version 3.1 due to its improved sensitivity for masses when applied to full-field digital mammograms.

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