• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.229-232
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• 2003

In this paper, we present an efficient algorithm to detect microcalcifications ROI (Regions of Interest) in digital mammograms using Linear filters. To efficiently detect microcalcifications ROI, we used three sequential processes; preprocessing for breast area detection, modified multilevel thresholding, ROI selection using mean filter and linear filters.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.729-738
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• 2023

Objective: When multiple surveillance mammograms are performed within an annual interval, the current guidance for oneyear follow-up to determine breast cancer status results in shared follow-up periods in which a single breast cancer diagnosis can be attributed to multiple preceding examinations, posing a challenge for standardized performance assessment. We assessed the impact of using follow-up periods that eliminate the artifactual inflation of second breast cancer diagnoses. Materials and Methods: We evaluated surveillance mammograms from 2007-2016 in women with treated breast cancer linked with tumor registry and pathology outcomes. Second breast cancers included ductal carcinoma in situ or invasive breast cancer diagnosed during one-year follow-up. The cancer detection rate, interval cancer rate, sensitivity, and specificity were compared using different follow-up periods: standard one-year follow-up per the American College of Radiology versus follow-up that was shortened at the next surveillance mammogram if less than one year (truncated follow-up). Performance measures were calculated overall and by indication (screening, evaluation for breast problem, and short interval follow-up). Results: Of 117971 surveillance mammograms, 20% (n = 23533) were followed by another surveillance mammogram within one year. Standard follow-up identified 1597 mammograms that were associated with second breast cancers. With truncated follow-up, the breast cancer status of 179 mammograms (11.2%) was revised, resulting in 1418 mammograms associated with unique second breast cancers. The interval cancer rate decreased with truncated versus standard follow-up (3.6 versus 4.9 per 1000 mammograms, respectively), with a difference (95% confidence interval [CI]) of -1.3 (-1.6, -1.1). The overall sensitivity increased to 70.4% from 63.7%, for the truncated versus standard follow-up, with a difference (95% CI) of 6.6% (5.6%, 7.7%). The specificity remained stable at 98.1%. Conclusion: Truncated follow-up, if less than one year to the next surveillance mammogram, enabled second breast cancers to be associated with a single preceding mammogram and resulted in more accurate estimates of diagnostic performance for national benchmarks.

• Journal of Biomedical Engineering Research
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• v.21 no.2
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• pp.137-144
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• 2000

Clustered microcalcifications in X-ray mammograms are an important sign for the diagnosis of breast cancer. A shape-based method, which is based on the morphological features of clustered microcalcifications, is proposed for classifying clustered microcalcifications into benign or malignant categories. To verify the effectiveness of the proposed shape features, clinical mammograms were used to compare the classification performance of the proposed shape features with those of conventional textural features, such as the spatial gray-leve dependence method and the wavelet-based method. Image features extracted from these methods were used as inputs to a three-layer backpropagation neural network classifier. The classification performance of features extracted by each method was studied by using receiver operating-characteristics analysis. The proposed shape features were shown to be superior to the conventional textural features with respect to classification accuracy.

• Journal of The Korean Radiological Technologist Association
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• v.30 no.1
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• pp.117-123
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• 2004

Purpose : To assess the mammographic findings of male breast disease. Materials and methods : Between Jan 1997 and May 2004, mammograms were obtained in 89 patients with male breast disease. Mammograms were retrospectively reviewed and correlated with med

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.495-508
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• 2015

In this paper, a novel robust medical images watermarking scheme is proposed. In traditional methods, the added watermark may alter the host medical image in an irreversible manner and may mask subtle details. Consequently, we propose a method for medical image copyright protection that may remedy this problem by embedding the watermark without modifying the original host image. The proposed method is based on the visual cryptography concept and the dominant blocks of wavelet coefficients. The logic in using the blocks dominants map is that local features, such as contours or edges, are unique to each image. The experimental results show that the proposed method can withstand several image processing attacks such as cropping, filtering, compression, etc.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.1-8
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• 1998

Clustered microcalcifications on X-ray mammograms are an important sign for early detection of breast cancer. This paper proposes a computer-aided diagnosis method for the detection of clustered microcalcifications and marking their locations on digitized mammograms. The proposed detection method consists of the region of interest (ROI) selection, the film-artifact removal, the surrounding texture analysis method for the detection of clustered microcalcifications, which is based on the second-order histogram in two nested surrounding regions on the current pixel. This paper also describes the effectiveness of the proposed film-artifact removal filter in terms of the classification performance with the receiver operating-characteristics(ROC) analysis. A three-layer backpropagation neural network is employed as a classifier. The appropriate marking for the locations of clustered microcalcifications can be used to alert radiologists to locations of suspicious lesions.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9471-9473
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• 2014

Background: Since 2002, from October till December of each year, the Lebanese Ministry of Public Health conducts a mammogram based breast cancer screening campaign in the whole country for women over 40 years of age. These mammograms are performed free of charge in governmental hospitals or for reduced fees in private hospitals. The aim of this study is to analyze the direct impact of this campaign on cancer detection and subsequent treatment. Materials and Methods: Radiologic records of women screened with a mammogram during the campaign period from October till December 2012 at Saint Joseph Hospital, Baouchrieh, Beirut, were reviewed. Results of mammograms were reported using the ACR score. Women with ACR score ${\geq}4$ were tracked and investigated. Results: 900 screening mammograms were performed; median age was 55.2 years (range:31-81 years). Some 826 (91.8%) had an ACR score of ${\leq}2$; 66 (7.3%) an ACR =3 and only 8 (0.89%) an ACR=4. Thus, less than 1% (8/900) of all screened women were considered at high risk and needed a close follow-up. Among these 8 women, 4 underwent surgery for an early breast cancer, one had synchronous metastatic breast cancer and two were lost to follow-up. Conclusions: To coclude, Among 900-screened women for BC, less than 1 % (8 out of 900) were at high risk of hiding a BC (ACR=4), half of them benefited from early therapy (4 women out of 900) and one was a false positive. Larger studies on national level should be accomplished to have a complete data on breast cancer screening in Lebanon. The results of these studies can affect the Lebanese health policy regarding BC.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2259-2263
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• 2016

Background: Mammographic density determined according paranchymal patterns is a risk factor for breast cancer and its relationships with body and other breast characteristics of women is important. The purpose of the present study was to correlate breast parenchymal patterns and mammography abnormality findings with women's BMI, compressed breast thickness (CBT) and age in Tabriz city, Iran. Materials and Methods: From 1,100 mammograms interpreted by radiologists, breast parenchymal was classified into four categories from Types 1 (mostly fatty) through 4 (mostly fibroglandular tissue). Age, BMI, and CBT were recorded and their relation with risk for the development of breast abnormalities in mammograms was analyzed. Results: In women with a mean age of $45.8{\pm}8.63years$ 17.7% were in the high density group (Type 3 and 4). A comparison of four types of breast paranchymal with BMI, CBT and age showed inverse relations to breast density. Abnormal mammographic findings were 25.8% of all reported mammograms with a circular mass (12.7%) as the most common abnormality. About 21% abnormal cases were in less than 40 years. Increasing of BMI had significant relation with breast abnormality but in CBT was not observed. Conclusions: Measurement of women's body characteristics is useful for assistance in mammography diagnosis as well as selection of imaging instrument by high sensitivity for following patient in future. The effects of age, CBT and BMI groups on the breast paranchymal were significant.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.141-146
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• 2002

This paper proposed the automated methods for th detection of mass. We analysed characteristic of mass by using the features on mammograms. In first step, the homogeneity was used to distinguish mass from the normal tissue. In second step, we examined the dualistic circularity and pixel distribution of candidates from the dualistic images of each candidates in which we regards the gray value as topographic height information. The final decision was done with the method in which each candidates is compared with the hemispheric template. Template matching method was used in comparing the priority of candidates with the spacial circularity which is the characteristic of the mass, We applied the algorithm to the 180 mammograms. The detection resulted that the sensitivity of the proposed methods was 95.51% in which we detected 85 from the 89 mammograms.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.