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Artificial Neural Networks in Image Processing for Early Detection of Breast Cancer

M. M. Mehdy, P. Y. Ng, E. F. Shair, N. I. Md Saleh, C. Gomes
2017 Computational and Mathematical Methods in Medicine  
Medical imaging techniques have widely been in use in the diagnosis and detection of breast cancer.  ...  Neural network (NN) plays an important role in this respect, especially in the application of breast cancer detection.  ...  Acknowledgments This study has been supported by the Departments of Computer and Communication Engineering, Electrical and Electronics Engineering and Chemical and Environmental Engineering at Universiti  ... 
doi:10.1155/2017/2610628 pmid:28473865 pmcid:PMC5394406 fatcat:25zbqzges5ahjh6dmswxomxp6q

A State-of-the-art Survey on Deep Learning Methods for Detection of Architectural Distortion from Digital Mammography

Olaide N. Oyelade, Absalom E. Ezugwu
2020 IEEE Access  
The databases used were IRMA version of a digital database for screening mammogram (DDSM) and Mammographic Image Analysis Society (MIAS).  ...  mammography (DDSM) [65] , INbreast database, breast cancer digital repository (BCDR), and image retrieval in medical applications (IRMA).  ...  Author Name: Preparation of Papers for IEEE Access (February 2017) VOLUME XX, 2017 CONFLICT OF INTEREST The authors declare that there is no conflict of interests regarding the publication of the paper  ... 
doi:10.1109/access.2020.3016223 fatcat:h2khlie66zggffe5dezuj3o5aa

A Novel Approach to Mammogram Classification using Spatio-Temporal and Texture Feature Extraction using Dictionary based Sparse Representation Classifier

Vaishali D. Shinde, B. Thirumala
2020 International Journal of Advanced Computer Science and Applications  
In order to predict the breast cancer, mammogram is considered as a promising technique which helps to identify the early stages of cancer.  ...  Cancer is a chronic disease and increasing rapidly worldwide. Breast cancer is one of the most crucial cancer which affects the women health and causes death of the women.  ...  In this work, focus is on the CAD systems for mammogram image analysis because of its significant performance for breast cancer mammogram image analysis.  ... 
doi:10.14569/ijacsa.2020.0111041 fatcat:ostbwzbl6femjnuhv7xwunyxnu

Smart Digital Mammographic Screening System for Bulk Image Processing

Duraipandian M, Vinothkanna R
2021 Journal of Electrical Engineering and Automation  
Further, online databases like Breast Cancer Database (BCDB) and BreakHis are also used for analysis.  ...  Existence of masses, calcification and mammogram are the evidences that help radiologists in early cancer identification.  ...  The mammograms are analyzed for detection and segmentation of the masses using local statistical texture analysis and constraint region growing technique schemes for improving the distinct structure of  ... 
doi:10.36548/jeea.2020.4.003 fatcat:fguns322bnedrjirni53dgsvnu

Combining Feature Methods for Content-Based Classification of Mammogram Images

Keith Chikamai, Serestina Viriri, Jules Raymond Tapamo
2013 International Journal of Computers Communications & Control  
Mammography is one of the successful ways for early detection of breast cancer. It mostly involves manual reading of mammograms, a process that is difficult and error-prone.  ...  Breast cancer is among the leading cause of death among females. Studies show that early detection allows for a better prognosis.  ...  It is commonly used for identification of suspicious regions in a mammogram, as well as for determination of malignancy.  ... 
doi:10.15837/ijccc.2013.4.273 fatcat:knirqdeqr5hvzh5d2hqhveabiy

Analysis of Oriented Texture with Applications to the Detection of Architectural Distortion in Mammograms

Fábio J. Ayres, Rangaraj M. Rangayyan, J. E. Leo Desautels
2010 Synthesis Lectures on Biomedical Engineering  
As in many other applications of computer vision, the general framework for the understanding of oriented features in images can be divided into low-and high-level analysis.  ...  This book presents an analysis of several important methods for the detection of oriented features in images, and a discussion of the phase portrait method for high-level analysis of orientation fields  ...  [30] developed a method for the analysis of asymmetry in mammograms using directional filtering with Gabor wavelets.  ... 
doi:10.2200/s00301ed1v01y201010bme038 fatcat:acm7pqcz35gydnyisqbadop7my

Medical Image Classification Using the Discriminant Power Analysis (DPA) of Discrete Cosine Transform (DCT) Coefficients [chapter]

Nasser Edinne Benhassine, Abdelnour Boukaache, Djalil Boudjehem
2021 Real Perspective of Fourier Transforms and Current Developments in Superconductivity  
The classification of mammogram images represents a very important operation to identify whether the breast cancer is benign or malignant.  ...  In the final step of the proposed system, we have used the most known classifiers in the field of the image classification for evaluation.  ...  Frameworks); Subset of CBIS-DDSM Curated Breast Imaging of DDSM (Digital Database for Screening Mammography).  ... 
doi:10.5772/intechopen.94026 fatcat:wf2ygdukgzh7zjkxiy3w7ux3d4

Normal breast identification in screening mammography: A study on 18 000 images

Silvia Bessa, Ines Domingues, Jaime S. Cardosos, Pedro Passarinho, Pedro Cardoso, Vitor Rodrigues, Fernando Lage
2014 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)  
Normal breasts are screened-out from the process, leaving radiologists more time to focus on more difficult cases. In this work, a new approach for the identification of normal breasts is presented.  ...  Through the years, several CAD systems have been developed to help radiologists in the hard task of detecting signs of cancer in the numerous screening mammograms.  ...  We would like to thank Liga Portuguesa Contra o Cancro for providing us with the data used in this study.  ... 
doi:10.1109/bibm.2014.6999178 dblp:conf/bibm/BessaDCPCRL14 fatcat:3arzm63645gfrfzkvkh3dwgsdi

A Brief Survey on Breast Cancer Diagnostic with Deep Learning Schemes Using Multi-Image Modalities

Tariq Mahmood, Jianqiang Li, Yan Pei, Faheem Akhtar, Azhar Imran, Khalil ur Rehman
2020 IEEE Access  
[87] proposed KNN method for automatic identification of breast lesion and Gabor wavelet for feature extractions from a mammogram which achieved 98.69% accuracy.  ...  [87] developed a model to segment the breast masses automatically and used Gabor wavelet for feature extraction from breast images which achieved 96.52% accuracy.  ...  For more information, see 1 book, 40+ journal papers, and 58 international patent applications (27 of them have been granted in China, US, or Japan).  ... 
doi:10.1109/access.2020.3021343 fatcat:czvctyngmjg6bhzinpmrfmht64

Improved Threshold Based and Trainable Fully Automated Segmentation for Breast Cancer Boundary and Pectoral Muscle in Mammogram Images

Dilovan Asaad Zebari, Diyar Qader Zeebaree, Adnan Mohsin Abdulazeez, Habibollah Haron, Haza Nuzly Abdull Hamed
2020 IEEE Access  
The proposed segmentation approach was tested by utilizing 322, 200, 100 mammogram images from mammographic image analysis society (mini-MIAS), INbreast, Breast Cancer Digital Repository (BCDR) databases  ...  More so, this paper also included the groundtruth as an evaluation of comprehensive similarity. In the clinic, this analysis may be provided as a valuable support for breast cancer identification.  ...  The automatic analysis of a digitalized mammogram by using a computer requires its segmentation into different anatomical regions.  ... 
doi:10.1109/access.2020.3036072 fatcat:absdaytaw5eyvkerzed3jd4ebm

An Interactive Method Based on the Live Wire for Segmentation of the Breast in Mammography Images

Zhang Zewei, Wang Tianyue, Guo Li, Wang Tingting, Xu Lu
2014 Computational and Mathematical Methods in Medicine  
According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live  ...  and qualitative analysis of breast lumps.  ...  Texture analysis plays an important role in variable of applications of medical image analysis for tumors segmentation based on local spatial variations of intensity.  ... 
doi:10.1155/2014/954148 pmid:25024740 pmcid:PMC4082883 fatcat:xxrdvty2i5dgdilqn3ckg23hfe

Breast Cancer Detection and Diagnosis Using Machine Learning: A Survey

Riyadh M. Al-Tam, Sachin M. Narangale
2021 Journal of scientific research  
In this paper, a comprehensive survey to review most of the accurate techniques being used for both detecting and diagnosing breast cancer is conducted.  ...  Whenever a suspicion is raised, periodical exams usually including digital mammograms (DM), Infrared thermography, magnetic resonance imaging (MRI), ultrasound (US), microscopic (histological) images,  ...  At conventional, the quality of modalities' images using for breast cancer tests, is dependent on two measures: sensitivity and specificity.  ... 
doi:10.37398/jsr.2021.650532 fatcat:r4mo24373rd2pe7ooc3gnwiwue

Segmentation of Breast Regions in Mammogram Based on Density: A Review [article]

Nafiza Saidin, Harsa Amylia Mat Sakim, Umi Kalthum Ngah, Ibrahim Lutfi Shuaib
2012 arXiv   pre-print
Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and is described as breast density.  ...  The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density.  ...  Acknowledgments The authors would like to acknowledge USM-RU Grant 814082 for providing financial support for this work.  ... 
arXiv:1209.5494v1 fatcat:vasxqun575hihpr6vl5e2633vm


2007 Innovative Applications of Information Technology for the Developing World  
Results obtained with a set of mammograms indicate that this method can improve the sensitivity and reliability of the systems for automated detection of breast tumors i.e. microcalcification.  ...  The algorithms are tested on 161 pairs of digitized mammograms from Mammographic Image Analysis Society (MIAS) database.  ...  About 25% of all cancers diagnosed in women are breast cancers and about 20% of all lethal cancers are breast cancers. It is the leading cause of death due to cancer in women [11] .  ... 
doi:10.1142/9781860948534_0017 fatcat:7xyp6hzc5fg3thqhhwqgabtefe

Multi-Resolution and Wavelet Representations for Identifying Signatures of Disease

Paul Sajda, Andrew Laine, Yehoshua Zeevi
2002 Disease Markers  
The signal processing and applied mathematics communities have developed, in recent years, signal representations which take advantage of Gabor-type and wavelet-type functions that localize signal energy  ...  In this paper we review wavelets, and other related multi-resolution transforms, within the context of identifying signatures for disease.  ...  .), the DoD Multidisciplinary University Research Initiative (MURI) program administered by the Office of Naval Research under N00014-01-0625 (P.S and Y.Z), the Department of Biomedical Engineering Imaging  ... 
doi:10.1155/2002/108741 pmid:14646044 pmcid:PMC3851637 fatcat:3igejnra3res3k7m3vhb3sklii
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