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Multi-View Feature Fusion based Four Views Model for Mammogram Classification using Convolutional Neural Network

Hasan Nasir Khan, Ahmad Raza Shahid, Basit Raza, Amir Hanif Dar, Hani Alquhayz
2019 IEEE Access  
In this study, we propose Multi-View Feature Fusion (MVFF) based CADx system using feature fusion technique of four views for classification of mammogram.  ...  The 5-year survival rate of breast cancer is 99% if it is located only in breast.  ...  ACKNOWLEDGMENT This work has been carried out at Medical Imaging and Diagnostics Lab at COMSATS University Islamabad (CUI), Islamabad under the umbrella of National Center of Artificial Intelligence, Pakistan  ... 
doi:10.1109/access.2019.2953318 fatcat:455h4vtzdjg53gydbuebcsywtm

Diagnosis of breast cancer based on modern mammography using hybrid transfer learning

Aditya Khamparia, Subrato Bharati, Prajoy Podder, Deepak Gupta, Ashish Khanna, Thai Kim Phung, Dang N. H. Thanh
2021 Multidimensional systems and signal processing  
Breast cancer is a common cancer in women.  ...  Early detection of breast cancer in particular and cancer, in general, can considerably increase the survival rate of women, and it can be much more effective.  ...  In Vang et al. (2018) , the ensemble-based architecture is proposed for multi-class image classification of breast cancer.  ... 
doi:10.1007/s11045-020-00756-7 pmid:33456204 pmcid:PMC7798373 fatcat:l355bmkn4vebngdsnsp7shsjzi

The Impact of Data processing and Ensemble on Breast Cancer Detection Using Deep Learning

Ammar Mohamed, Eslam Amer, sara Noor Eldin, jana khaled, Maysoon Hossam, Noha Elmasry, Ganna Tamer Adnan
2022 Journal of Computing and Communication (Online)  
Breast cancer diagnostics range from mammograms to CT scans and ultrasounds, but a biopsy is the only way to know for sure if the suspicious cells detected in the breast are cancerous or not.  ...  This paper's main contribution is multi-fold. First, it proposes a deep learning approach to detect breast cancer from biopsy microscopy images. Deep convolution nets of various types are used.  ...  A breast biopsy is a procedure in which a small piece of breast tissue is removed and examined by pathologists.  ... 
doi:10.21608/jocc.2022.218453 fatcat:6etbxv5ogfdzrl3haqgemnvro4

Breast Mass Classification from Mammograms using Deep Convolutional Neural Networks [article]

Daniel Lévy, Arzav Jain
2016 arXiv   pre-print
In this work, we present how Convolutional Neural Networks can be used to directly classify pre-segmented breast masses in mammograms as benign or malignant, using a combination of transfer learning, careful  ...  Because of its mostly manual nature, variability in mass appearance, and low signal-to-noise ratio, a significant number of breast masses are missed or misdiagnosed.  ...  The authors also ackowledge the support of AWS Educate program for generously providing free instances with GPUs.  ... 
arXiv:1612.00542v1 fatcat:zovhgz4ujrf63nj74u7j227gdq

Computer-aided Diagnosis in Breast Ultrasound

Dar-Ren Chen, Yi-Hsuan Hsiao
2008 Journal of Medical Ultrasound  
Cancer remains a leading cause of death in Taiwan, and the prevalence of breast cancer has increased in recent years.  ...  Mammography and ultrasound (US) are the main imaging techniques used in the detection of breast cancer.  ...  Technical advances in breast imaging have been developed to avoid unnecessary biopsy and diminish the number of missed tumors.  ... 
doi:10.1016/s0929-6441(08)60005-3 fatcat:x6r54dxu25gc7c34qq3kebdid4

Breast compression parameters among women imaged with full field digital mammography and breast tomosynthesis in BreastScreen Norway

N. Moshina, Solveig Hofvind, Gunvor Waade, Åsne Holen, Berit Hanestad, Sofie Sebuødegård, K. Pedersen, Elizabeth A. Krupinski
2018 14th International Workshop on Breast Imaging (IWBI 2018)  
The 361-case dataset included 92 benign and 30 luminal A lesions imaged pre-biopsy, and 40 benign and 199 luminal A lesions imaged post-biopsy.  ...  Pathological diagnosis of primary lesion and LNs were confirmed by US-guided biopsy before NAC.NAC response was evaluated the primary lesion as increased FDG uptake compared to the surrounding breast tissue  ...  The aim of this study is to exploit to use of CNNs for mass detection in mammograms using pre-trained networks.  ... 
doi:10.1117/12.2317918 dblp:conf/iwbi/WadeHHSMPH18 fatcat:gyksxd5b2jf4jpntucqs5zjc5i

Pathological features and patterns of metastatic disease in locally advanced inflammatory and non-inflammatory breast cancer

MZ Mvere, SJ Tennant, AJ Evans, I Ellis, J James, M Shehat, S Chan
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2367 pmcid:PMC4284828 fatcat:pasmwxg6k5ht3hikbmoaehn5mu

Does breast magnetic resonance imaging measurement correlate with pathology in assessment of primary breast cancer?

AN Khan, M Hoosein, H Khan, L Grosvenor, M Al-Attar
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2373 pmcid:PMC4284834 fatcat:byvabjtidngbladzuztdhivw4a

Axillary lymph node ultrasound and fine needle aspiration in pre-operative breast cancer staging

AAM Leaver, L McLean
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2397 pmcid:PMC4284858 fatcat:s6rbgdnugjbfjemna5tol7hhw4

Design Guidelines for Mammogram-based Computer-Aided Systems Using Deep Learning Techniques

Farnoosh Azour, Azzedine Boukerche
2022 IEEE Access  
This critical review of the state-of-the-art techniques is presented, which we believe can serve as a valuable source for research scientists investigating deep learning-based breast mammogram classification  ...  Breast cancer is the second fatal disease among cancers patients both in Canada and across the globe. However, when detected early, a patients' survival rate can be raised.  ...  Thus, employing histopathology images has been quite popular for researchers who want to accurately perform multi-class breast cancer classification [17] .  ... 
doi:10.1109/access.2022.3151830 fatcat:roocprzhabba5pyujfxq3gsbxq

Is mammogram indicated in patients presenting with breast pain alone in the presence of a normal clinical examination?

H Winter, M Dilworth, K Darvall, M Sintler
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2386 pmcid:PMC4284847 fatcat:c4b3h4iadva5hnylxet53mem7y

Performance in digital mammography with and without film prior mammograms

S Taylor-Phillips, MG Wallis, A Duncan, AG Gale
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2385 pmcid:PMC4284846 fatcat:2r5z4gldlbgodi4yw6xxaq6gny

Haematoma-directed ultrasound guidewire localisation of breast lesions

CM Lee, A Redman
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2388 pmcid:PMC4284849 fatcat:jhqtrbzlbje6zehyab23mg4cpe

Multi-view Multi-task Learning for Improving Autonomous Mammogram Diagnosis

Trent Kyono, Fiona J. Gilbert, Mihaela van der Schaar
2019 Machine Learning in Health Care  
We show on full-field mammograms that multi-task learning has three advantages: 1) learning refined feature representations associated with cancer improves the classification performance of the diagnosis  ...  We present a novel multi-view multi-task (MVMT) convolutional neural network (CNN) trained to predict the radiological assessments known to be associated with cancer, such as breast density, conspicuity  ...  For example, MVMT may predict a patient have cancer, but the multi-task annotations reflect a huge discrepancy in the presentation or sign of lesion which a trained radiologist could question and reexamine  ... 
dblp:conf/mlhc/KyonoGS19 fatcat:cjnbjuiarfabznyzf6pjg22yha

Underestimation of invasive malignancy on conventional core biopsy of breast

B Rengabashyam, J Findlay, J Kelly
2009 Breast Cancer Research  
Mammography scores using the RCR Breast Group classification were sequentially obtained for the screening mammogram, 2D digital and DBT, and these were each compared with the final assessment outcome.  ...  Introduction Digital breast tomosynthesis (DBT) may improve the accuracy of mammography by enabling visual separation of overlapping tissues (Andersson et al. 2008, Poplack et al. 2007).  ...  Further investigation and outcome of these lesions was then assessed using radiology, pathology and multi-disciplinary meeting records.  ... 
doi:10.1186/bcr2403 pmcid:PMC4284864 fatcat:kerherv57nbl7bwrvawenh3bjy
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