Displaying publications 21 - 38 of 38 in total

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  1. Jalalian A, Mashohor SB, Mahmud HR, Saripan MI, Ramli AR, Karasfi B
    Clin Imaging, 2013 May-Jun;37(3):420-6.
    PMID: 23153689 DOI: 10.1016/j.clinimag.2012.09.024
    Breast cancer is the most common form of cancer among women worldwide. Early detection of breast cancer can increase treatment options and patients' survivability. Mammography is the gold standard for breast imaging and cancer detection. However, due to some limitations of this modality such as low sensitivity especially in dense breasts, other modalities like ultrasound and magnetic resonance imaging are often suggested to achieve additional information. Recently, computer-aided detection or diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) preprocessing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. This paper presents the approaches which are applied to develop CAD systems on mammography and ultrasound images. The performance evaluation metrics of CAD systems are also reviewed.
    Matched MeSH terms: Mammography/methods*
  2. Sanmugasiva VV, Ramli Hamid MT, Fadzli F, Rozalli FI, Yeong CH, Ab Mumin N, et al.
    Sci Rep, 2020 11 26;10(1):20628.
    PMID: 33244075 DOI: 10.1038/s41598-020-77456-6
    This study aims to assess the diagnostic accuracy of digital breast tomosynthesis in combination with full field digital mammography (DBT + FFDM) in the charaterisation of Breast Imaging-reporting and Data System (BI-RADS) category 3, 4 and 5 lesions. Retrospective cross-sectional study of 390 patients with BI-RADS 3, 4 and 5 mammography with available histopathology examination results were recruited from in a single center of a multi-ethnic Asian population. 2 readers independently reported the FFDM and DBT images and classified lesions detected (mass, calcifications, asymmetric density and architectural distortion) based on American College of Radiology-BI-RADS lexicon. Of the 390 patients recruited, 182 malignancies were reported. Positive predictive value (PPV) of cancer was 46.7%. The PPV in BI-RADS 4a, 4b, 4c and 5 were 6.0%, 38.3%, 68.9%, and 93.1%, respectively. Among all the cancers, 76% presented as masses, 4% as calcifications and 20% as asymmetry. An additional of 4% of cancers were detected on ultrasound. The sensitivity, specificity, PPV and NPV of mass lesions detected on DBT + FFDM were 93.8%, 85.1%, 88.8% and 91.5%, respectively. The PPV for calcification is 61.6% and asymmetry is 60.7%. 81.6% of cancer detected were invasive and 13.3% were in-situ type. Our study showed that DBT is proven to be an effective tool in the diagnosis and characterization of breast lesions and supports the current body of literature that states that integrating DBT to FFDM allows good characterization of breast lesions and accurate diagnosis of cancer.
    Matched MeSH terms: Mammography/methods*
  3. Lo CH, Chai XY, Ting SSW, Ang SC, Chin X, Tan LT, et al.
    Cancer Med, 2020 05;9(9):3244-3251.
    PMID: 32130790 DOI: 10.1002/cam4.2821
    BACKGROUND: Breast cancer is the leading cause of death among women worldwide. Studies have identified breast density as a controversial risk factor of breast cancer. Moreover, studies found that breast density reduction through Tamoxifen could reduce risk of breast cancer significantly. To date, no study on the association between breast density and breast cancer has been carried out in Malaysia. If breast density is proven to be a risk factor of breast cancer, intervention could be carried out to reduce breast cancer risk through breast density reduction.

    PURPOSE: To determine if density of breast is an independent risk factor which will contribute to development of breast cancer.

    MATERIALS AND METHODS: A prospective cohort study is carried out in two hospitals targeting adult female patients who presented to the Breast Clinic with symptoms suspicious of breast cancer. Participants recruited were investigated for breast cancer based on their symptoms. Breast density assessed from mammogram was correlated with tissue biopsy results and final diagnosis of benign or malignant breast disease.

    RESULTS: Participants with dense breasts showed 29% increased risk of breast cancer when compared to those with almost entirely fatty breasts (odds ratio [OR] 1.29, 95% CI 0.38-4.44, P = .683). Among the postmenopausal women, those with dense breasts were 3.1 times more likely to develop breast cancer compared with those with fatty breasts (OR 3.125, 95% CI 0.72-13.64, P = .13). Moreover, the chance of developing breast cancer increases with age (OR 1.046, 95% CI 1.003-1.090, P 

    Matched MeSH terms: Mammography/methods*
  4. Lau S, Abdul Aziz YF, Ng KH
    PLoS One, 2017;12(4):e0175781.
    PMID: 28419125 DOI: 10.1371/journal.pone.0175781
    OBJECTIVES: To investigate: (1) the variability of mammographic compression parameters amongst Asian women; and (2) the effects of reducing compression force on image quality and mean glandular dose (MGD) in Asian women based on phantom study.

    METHODS: We retrospectively collected 15818 raw digital mammograms from 3772 Asian women aged 35-80 years who underwent screening or diagnostic mammography between Jan 2012 and Dec 2014 at our center. The mammograms were processed using a volumetric breast density (VBD) measurement software (Volpara) to assess compression force, compression pressure, compressed breast thickness (CBT), breast volume, VBD and MGD against breast contact area. The effects of reducing compression force on image quality and MGD were also evaluated based on measurement obtained from 105 Asian women, as well as using the RMI156 Mammographic Accreditation Phantom and polymethyl methacrylate (PMMA) slabs.

    RESULTS: Compression force, compression pressure, CBT, breast volume, VBD and MGD correlated significantly with breast contact area (p<0.0001). Compression parameters including compression force, compression pressure, CBT and breast contact area were widely variable between [relative standard deviation (RSD)≥21.0%] and within (p<0.0001) Asian women. The median compression force should be about 8.1 daN compared to the current 12.0 daN. Decreasing compression force from 12.0 daN to 9.0 daN increased CBT by 3.3±1.4 mm, MGD by 6.2-11.0%, and caused no significant effects on image quality (p>0.05).

    CONCLUSIONS: Force-standardized protocol led to widely variable compression parameters in Asian women. Based on phantom study, it is feasible to reduce compression force up to 32.5% with minimal effects on image quality and MGD.

    Matched MeSH terms: Mammography/methods*
  5. Jalalian A, Mashohor S, Mahmud R, Karasfi B, Iqbal Saripan M, Ramli AR
    J Digit Imaging, 2017 Dec;30(6):796-811.
    PMID: 28429195 DOI: 10.1007/s10278-017-9958-5
    Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633-643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images. The proposed CAD system contains three main stages including segmentation of volume of interest (VOI), feature extraction and classification. A 3D Fuzzy segmentation technique has been implemented to extract the VOI. The shape and texture of angiogenesis in CTLM images are significant characteristics to differentiate malignancy or benign lesions. The 3D compactness features and 3D Grey Level Co-occurrence matrix (GLCM) have been extracted from VOIs. Multilayer perceptron neural network (MLPNN) pattern recognition has developed for classification of the normal and abnormal lesion in CTLM images. The performance of the proposed CAD system has been measured with different metrics including accuracy, sensitivity, and specificity and area under receiver operative characteristics (AROC), which are 95.2, 92.4, 98.1, and 0.98%, respectively.
    Matched MeSH terms: Mammography/methods*
  6. Tan M, Aghaei F, Wang Y, Zheng B
    Phys Med Biol, 2017 01 21;62(2):358-376.
    PMID: 27997380 DOI: 10.1088/1361-6560/aa5081
    The purpose of this study is to evaluate a new method to improve performance of computer-aided detection (CAD) schemes of screening mammograms with two approaches. In the first approach, we developed a new case based CAD scheme using a set of optimally selected global mammographic density, texture, spiculation, and structural similarity features computed from all four full-field digital mammography images of the craniocaudal (CC) and mediolateral oblique (MLO) views by using a modified fast and accurate sequential floating forward selection feature selection algorithm. Selected features were then applied to a 'scoring fusion' artificial neural network classification scheme to produce a final case based risk score. In the second approach, we combined the case based risk score with the conventional lesion based scores of a conventional lesion based CAD scheme using a new adaptive cueing method that is integrated with the case based risk scores. We evaluated our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative), whereby each case had all four images from the CC and MLO views. The area under the receiver operating characteristic curve was AUC  =  0.793  ±  0.015 and the odds ratio monotonically increased from 1 to 37.21 as CAD-generated case based detection scores increased. Using the new adaptive cueing method, the region based and case based sensitivities of the conventional CAD scheme at a false positive rate of 0.71 per image increased by 2.4% and 0.8%, respectively. The study demonstrated that supplementary information can be derived by computing global mammographic density image features to improve CAD-cueing performance on the suspicious mammographic lesions.
    Matched MeSH terms: Mammography/methods*
  7. Rahmat K, Ab Mumin N, Ng WL, Mohd Taib NA, Chan WY, Ramli Hamid MT
    Ultrasound Med Biol, 2024 Jan;50(1):112-118.
    PMID: 37839984 DOI: 10.1016/j.ultrasmedbio.2023.09.011
    OBJECTIVE: The aim of the work described here was to assess the performance of automated breast ultrasound (ABUS) as an adjunct to digital breast tomosynthesis (DBT) in the screening and diagnostic setting.

    METHODS: This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.

    RESULTS: A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.

    CONCLUSION: ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.

    Matched MeSH terms: Mammography/methods
  8. Burton A, Byrnes G, Stone J, Tamimi RM, Heine J, Vachon C, et al.
    Breast Cancer Res, 2016 12 19;18(1):130.
    PMID: 27993168
    BACKGROUND: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types.

    METHODS: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences.

    RESULTS: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean √dense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in √dense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p 

    Matched MeSH terms: Mammography/methods*
  9. McCormack VA, Burton A, dos-Santos-Silva I, Hipwell JH, Dickens C, Salem D, et al.
    Cancer Epidemiol, 2016 Feb;40:141-51.
    PMID: 26724463 DOI: 10.1016/j.canep.2015.11.015
    Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.
    Matched MeSH terms: Mammography/methods*
  10. Zain NM, Chelliah KK
    Asian Pac J Cancer Prev, 2014;15(3):1327-31.
    PMID: 24606460
    BACKGROUND: Electrical impedance tomography (EIT) is a new non-invasive, mobile screening method which does not use ionizing radiation to the human breast; allows conducting quantitative assessment of the images besides the visual interpretation. The aim of this study was to correlate the quantitative assessment and visual interpretation of breast electrical impedance tomographs and associated factors.

    MATERIALS AND METHODS: One hundred and fifty mammography patients above 40 years and undergoing EIT were chosen using convenient sampling. Visual interpretation of the images was carried out by a radiologist with minimum of three years experience using the breast imaging - electrical impedance (BI-EIM) classification for detection of abnormalities. A set of thirty blinded EIT images were reinterpreted to determine the intra-rater reliability using kappa. Quantitative assessment was by comparison of the breast average electric conductivity with the norm and correlations with visual interpretation of the images were determined using Chi-square. One-way ANOVA was used to compare the mean electrical conductivity between groups and t-test was used for comparisons with pre-existing Caucasians statistics. Independent t-tests were applied to compare the mean electrical conductivity of women with factors like exogenous hormone use and family history of breast cancer.

    RESULTS: The mean electrical conductivity of Malaysian women was significantly lower than that of Caucasians (p<0.05). Quantitative assessment of electrical impedance tomography was significantly related with visual interpretation of images of the breast (p<0.05).

    CONCLUSIONS: Quantitative assessment of electrical impedance tomography images was significantly related with visual interpretation.

    Matched MeSH terms: Mammography/methods*
  11. Dahlui M, Gan DE, Taib NA, Pritam R, Lim J
    Asian Pac J Cancer Prev, 2012;13(7):3443-9.
    PMID: 22994775
    INTRODUCTION: Despite health education efforts to educate women on breast cancer and breast cancer screening modalities, the incidence of breast cancer and presentation at an advanced stage are still a problem in Malaysia.

    OBJECTIVES: To determine factors associated with the uptake of breast cancer screening among women in the general population.

    METHODS: This pre-intervention survey was conducted in a suburban district. All households were approached and women aged 20 to 60 years old were interviewed with pre-tested guided questionnaires. Variables collected included socio-demographic characteristics, knowledge on breast cancer and screening practice of breast cancer. Univariate and multivariate analysis were performed.

    RESULTS: 41.5% of a total of 381 respondents scored above average; the mean knowledge score on causes and risks factors of breast cancer was 3.41 out of 5 (SD1.609). 58.5% had ever practiced BSE with 32.5% performing it at regular monthly intervals. Uptake of CBE by nurses and by doctors was 40.7% and 37.3%, respectively. Mammogram uptake was 14.6%. Significant predictors of BSE were good knowledge of breast cancer (OR=2.654, 95% CI: 1.033-6.816), being married (OR=2.213, 95% CI: 1.201-4.076) and attending CBE (OR=1.729, 95% CI: 1.122-2.665). Significant predictors for CBE included being married (OR=2.161, 95% CI: 1.174-3.979), good knowledge of breast cancer (OR=2.286, 95% CI: 1.012-5.161), and social support for breast cancer screening (OR=2.312, 95% CI: 1.245-4.293). Women who had CBE were more likely to undergo mammographic screening of the breast (OR=5.744, 95% CI: 2.112-15.623), p<0.005.

    CONCLUSION: CBE attendance is a strong factor in promoting BSE and mammography, educating women on the importance of breast cancer screening and on how to conduct BSE. The currently opportunistic conduct of CBE should be extended to active calling of women for CBE.
    Matched MeSH terms: Mammography/methods
  12. Jamal N, Ng KH, Looi LM, McLean D, Zulfiqar A, Tan SP, et al.
    Phys Med Biol, 2006 Nov 21;51(22):5843-57.
    PMID: 17068368
    We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r2 = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
    Matched MeSH terms: Mammography/methods*
  13. Dinesh BJ, Hayati F, Azizan N, Abdul Rashid NF
    BMJ Case Rep, 2019 Sep 18;12(9).
    PMID: 31537599 DOI: 10.1136/bcr-2019-231516
    Florid papillomatosis (FP) of the nipple, or nipple adenoma, is a rare breast tumour, affecting middle-aged group population. A 46-year-old woman presented to us with a cauliflower-like FP of the right nipple with no blood stained discharge or breast lump. FP can be mistaken clinically for Paget's disease and occasionally misinterpreted as invasive ductal or intraductal carcinoma. Extensive intervention, correct diagnosis and prompt treatment are essential. Any breast pathology requires triple assessment including FP of the nipple. Once the diagnosis of ductal carcinoma is excluded, simple complete excision can be undertaken. This is to ensure complete obliteration of disease recurrence and preservation of cosmetic result. We discuss the pathology and psychosocial aspects of FP.
    Matched MeSH terms: Mammography/methods
  14. Fadzli F, Rahmat K, Ramli MT, Rozalli FI, Hooi TK, Fadzli AN, et al.
    Medicine (Baltimore), 2021 Apr 23;100(16):e25297.
    PMID: 33879660 DOI: 10.1097/MD.0000000000025297
    To evaluate the clinical and imaging findings of papillary breast neoplasm and review the pathologic correlation at a tertiary center.Retrospective study of patients diagnosed with benign and malignant papillary lesions between 2008 to 2018. 147 patients were identified with histology diagnosis of papillary lesions. The clinical, imaging, and pathological characteristics were reviewed.Patient cohort included 147 women diagnosed with papillary lesions (mean age at diagnosis 53.8 years) and were divided into 3 histology groups (benign, atypical, and malignant). Common clinical presentations were breast lump (n = 60) and nipple discharge (n = 29), 48 patients were asymptomatic.Only 37 were detected as a mass lesion on mammogram. The presence of mass lesion on mammogram was the most common feature in all 3 papillary lesion groups, and with the presence of asymmetric density, were the 2 mammographic features significantly associated (P 
    Matched MeSH terms: Mammography/methods*
  15. Bohan S, Ramli Hamid MT, Chan WY, Vijayananthan A, Ramli N, Kaur S, et al.
    Sci Rep, 2021 01 08;11(1):129.
    PMID: 33420200 DOI: 10.1038/s41598-020-80124-4
    This study aims to evaluate the diagnostic accuracy of digital breast tomosynthesis-guided vacuum assisted breast biopsy (DBT-VABB) of screening detected suspicious mammographic abnormalities comprising of calcifications, asymmetric densities, architectural distortions and spiculated masses. In this institutionally approved study, a total of 170 (n = 170) DBT-VABB were performed, 153 (90%) were for calcifications, 8 (4.7%) for spiculated mass, 5 (2.9%) for asymmetric density and 4 (2.4%) for architectural distortion. All these lesions were not detected on the corresponding ultrasound. Histopathology results revealed 140 (82.4%) benign, 9 (5.3%) borderline and 21 (12.4%) malignant lesions. The total upgrade rate at surgery was 40% for atypical ductal hyperplasia and 5.9% for ductal carcinoma in-situ. 3.6% discordant benign lesions showed no upgrade. DBT-VABB showed 100% specificity, 91.3% sensitivity and 100% positive predictive value (PPV) for detecting malignant lesions. The negative predictive value (NPV) was 80%. 2 (1.2%) patients had mild complications and 1 (0.6%) had severe pain. Our study showed that DBT-VABB was a safe and reliable method, with high sensitivity, specificity, PPV and NPV in the diagnosis of non-palpable benign and malignant breast lesions. Our data also confirmed the accuracy of DBT-VABB in detecting malignant lesions and we suggest further surgical excision in borderline lesions for a more accurate diagnostic evaluation.
    Matched MeSH terms: Mammography/methods*
  16. Alhabshi SM, Rahmat K, Abdul Halim N, Aziz S, Radhika S, Gan GC, et al.
    Ultrasound Med Biol, 2013 Apr;39(4):568-78.
    PMID: 23384468 DOI: 10.1016/j.ultrasmedbio.2012.10.016
    The purpose of this study was to evaluate the diagnostic value of qualitative and semi-quantitative assessment of ultrasound elastography in differentiating between benign and malignant breast lesions. This prospective study was conducted in two tertiary medical centers. Consecutive B-mode ultrasound and real-time elastographic images were obtained for 67 malignant and 101 benign breast lesions in 168 women. Four experienced radiologists analyzed B-mode ultrasound alone and B-mode ultrasound combined with elastography independently. Conventional ultrasound findings were classified according to the American College of Radiology Breast Imaging Reporting and Data System classification. The elastographic assessment was based on qualitative and semi-quantitative parameters (i.e., strain pattern, width ratio, strain ratio). The sensitivity and specificity of combined elastography and conventional ultrasound were significantly higher than that of conventional ultrasound alone. The sensitivity, specificity, positive predictive value and negative predictive value was 97%, 61.4%, 62.5% and 96.8%, respectively, for conventional ultrasound and 100%, 93%, 99% and 90%, respectively, for combined technique. The semi-quantitative assessment with strain ratio and width ratio in elastography were the most useful parameters in differentiating between benign and malignant breast lesions. Cut-off point values for width ratio of more than 1.1 and strain ratio of more than 5.6 showed a high predictive value of malignancy with specificities of 84% and 76%, respectively (p 
    Matched MeSH terms: Mammography/methods*
  17. Vairavan R, Abdullah O, Retnasamy PB, Sauli Z, Shahimin MM, Retnasamy V
    Curr Med Imaging Rev, 2019;15(2):85-121.
    PMID: 31975658 DOI: 10.2174/1573405613666170912115617
    BACKGROUND: Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival.

    DISCUSSION: This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.

    CONCLUSION: This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.

    Matched MeSH terms: Mammography/methods
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