Mammography

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Mammography is the process of using low-energy-X-rays (usually around 30 kVp) to examine the human breast and is used as a diagnostic and a screening tool. (Wikipedia.org)






Conferences related to Mammography

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2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore


2019 44th International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)

Science, technology and applications spanning the millimeter-waves, terahertz and infrared spectral regions


2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2019 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2019, the 26th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

This conference is the annual premier meeting on the use of instrumentation in the Nuclear and Medical fields. The meeting has a very long history of providing an exciting venue for scientists to present their latest advances, exchange ideas, renew existing collaboration and form new ones. The NSS portion of the conference is an ideal forum for scientists and engineers in the field of Nuclear Science, radiation instrumentation, software engineering and data acquisition. The MIC is one of the most informative venues on the state-of-the art use of physics, engineering, and mathematics in Nuclear Medicine and related imaging modalities, such as CT and increasingly so MRI, through the development of hybrid devices


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Periodicals related to Mammography

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Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Computational Intelligence Magazine, IEEE

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications.


Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


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Most published Xplore authors for Mammography

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Xplore Articles related to Mammography

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Detection of masses in mammography through redundant expansions of scale

[{u'author_order': 1, u'affiliation': u'Ecole Centrale de Nantes, France', u'authorUrl': u'https://ieeexplore.ieee.org/author/37327468600', u'full_name': u'V. Laffont', u'id': 37327468600}, {u'author_order': 2, u'affiliation': u'Ecole Centrale de Nantes, France', u'authorUrl': u'https://ieeexplore.ieee.org/author/37327467900', u'full_name': u'F. Durupt', u'id': 37327467900}, {u'author_order': 3, u'authorUrl': u'https://ieeexplore.ieee.org/author/37327468100', u'full_name': u'M.A. Birgen', u'id': 37327468100}, {u'author_order': 4, u'authorUrl': u'https://ieeexplore.ieee.org/author/37327463300', u'full_name': u'S. Bauduin', u'id': 37327463300}, {u'author_order': 5, u'authorUrl': u'https://ieeexplore.ieee.org/author/37294103400', u'full_name': u'A.F. Laine', u'id': 37294103400}] 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2001

We show that dyadic scales may not be sufficient for the detection of masses in mammograms: a lesion may be too blurred on one scale, and then too fragmented at the next. In this paper, we report on the preliminary evidence of our study using a continuous wavelet transform in two dimensions with arbitrary positioning of a wavelet's center frequency ...


Tsallis Entropy Based Contrast Enhancement of Microcalcifications

[{u'author_order': 1, u'authorUrl': u'https://ieeexplore.ieee.org/author/37567961400', u'full_name': u'J. Mohanalin', u'id': 37567961400}, {u'author_order': 2, u'authorUrl': u'https://ieeexplore.ieee.org/author/37267941600', u'full_name': u'P.K. Kalra', u'id': 37267941600}, {u'author_order': 3, u'authorUrl': u'https://ieeexplore.ieee.org/author/37572652500', u'full_name': u'Nirmal Kumar', u'id': 37572652500}] 2009 International Conference on Signal Acquisition and Processing, 2009

This paper presents a new approach to enhance the contrast of microcalcifications in mammograms using a fuzzy algorithm based on Tsallis entropy. In phase I image is fuzzified using S membership function. In Phase II using the non-uniformity factor calculated from local information the contrast of microcalcifications were enhanced while suppressing the background heavily. This is the first time in ...


High resolution large formatted CMOS flat panel sensors for X-ray

[{u'author_order': 1, u'affiliation': u'Hamamatsu Photonics, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37272768400', u'full_name': u'K. Fujita', u'id': 37272768400}, {u'author_order': 2, u'affiliation': u'Hamamatsu Photonics, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37277105500', u'full_name': u'H. Mori', u'id': 37277105500}, {u'author_order': 3, u'affiliation': u'Hamamatsu Photonics, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37268402200', u'full_name': u'R. Kyuushima', u'id': 37268402200}, {u'author_order': 4, u'affiliation': u'Hamamatsu Photonics, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37280733600', u'full_name': u'M. Honda', u'id': 37280733600}, {u'author_order': 5, u'affiliation': u'Hamamatsu Photonics, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37278470700', u'full_name': u'K. Yamamoto', u'id': 37278470700}] 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515), 2003

This paper describes world largest monolithic CMOS flat panel sensor (FPS) and high speed amplifier with columnar CsI scintillator directly deposited onto the active area. These elements have been employed as a compact digital camera module for dynamic X-ray imaging will be used in digital mammography and scientific image measurement. The FPS has a diagonal size of 11 inches and ...


Not your mother's mammography [breast cancer detection]

[{u'author_order': 1, u'full_name': u'L.M. Sheppard'}] IEEE Spectrum, 2002

Breast cancer accounts for nearly one of every three cancers diagnosed in US women. While great strides have been made in early detection, the conventional method of mammography is not failproof it has trouble imaging dense tissue, it may show suspicious areas where no malignancy exists, and radiologists interpreting the images can miss up to 15 percent of cancers. It's ...


A method for detecting suspicious regions in mammograms based on multiscale image filtering and regression-line analysis

[{u'author_order': 1, u'affiliation': u'Shimane University, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37284342500', u'full_name': u'Shoji Hirano', u'id': 37284342500}, {u'author_order': 2, u'affiliation': u'Shimane University, Japan', u'authorUrl': u'https://ieeexplore.ieee.org/author/37284439400', u'full_name': u'Shusaku Tsumoto', u'id': 37284439400}] 2008 World Automation Congress, 2008

Early detection of breast cancer is an important task for preventing the loss of lives/breasts of the women. In this paper we propose a method for detecting suspicious features of breast cancers on mammograms by the combination of multiscale image filtering and regression-line analysis. Images are represented and analyzed at different scales. Calcifications are detected on the finest resolution, masses ...


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Educational Resources on Mammography

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IEEE-USA E-Books

  • Learning a New View of a Database: With an Application in Mammography

    This chapter contains sections titled: Introduction, View Learning for Mammography, Naive View Learning Framework, Initial Experiments, Intergrated View Learning Framework, Further Experiments and Results, Related Work, Conclusions and Future Work, Acknowledgments, References

  • Content-based Retrieval of Medical Images: Landmarking, Indexing, and Relevance Feedback

    Content-based image retrieval (CBIR) is the process of retrieval of images from a database that are similar to a query image, using measures derived from the images themselves, rather than relying on accompanying text or annotation. To achieve CBIR, the contents of the images need to be characterized by quantitative features; the features of the query image are compared with the features of each image in the database and images having high similarity with respect to the query image are retrieved and displayed. CBIR of medical images is a useful tool and could provide radiologists with assistance in the form of a display of relevant past cases. One of the challenging aspects of CBIR is to extract features from the images to represent their visual, diagnostic, or application-specific information content. In this book, methods are presented for preprocessing, segmentation, landmarking, feature extraction, and indexing of mammograms for CBIR. The preprocessing steps include anisotropic diffusion and the Wiener filter to remove noise and perform image enhancement. Techniques are described for segmentation of the breast and fibroglandular disk, including maximum entropy, a moment-preserving method, and Otsu's method. Image processing techniques are described for automatic detection of the nipple and the edge of the pectoral muscle via analysis in the Radon domain. By using the nipple and the pectoral muscle as landmarks, mammograms are divided into their internal, external, upper, and lower parts for further analysis. Methods are presented for feature extraction using texture analysis, shape analysis, granulometric analysis, moments, and statistical measures. The CBIR system presented provides options for retrieval using the Kohonen self- organizing map and the k-nearest-neighbor method. Methods are described for inclusion of expert knowledge to reduce the semantic gap in CBIR, including the query point movement method for relevance feedback (RFb). Analysis of performance is described in terms of precision, recall, and relevance-weighted precision of retrieval. Results of application to a clinical database of mammograms are presented, including the input of expert radiologists into the CBIR and RFb processes. Models are presented for integration of CBIR and computer-aided diagnosis (CAD) with a picture archival and communication system (PACS) for efficient workflow in a hospital. Table of Contents: Introduction to Content-based Image Retrieval / Mammography and CAD of Breast Cancer / Segmentation and Landmarking of Mammograms / Feature Extraction and Indexing of Mammograms / Content-based Retrieval of Mammograms / Integration of CBIR and CAD into Radiological Workflow

  • Computerized Analysis of Mammographic Images for Detection and Characterization of Breast Cancer

    The identification and interpretation of the signs of breast cancer in mammographic images from screening programs can be very difficult due to the subtle and diversified appearance of breast disease. This book presents new image processing and pattern recognition techniques for computer-aided detection and diagnosis of breast cancer in its various forms. The main goals are: (1) the identification of bilateral asymmetry as an early sign of breast disease which is not detectable by other existing approaches; and (2) the detection and classification of masses and regions of architectural distortion, as benign lesions or malignant tumors, in a unified framework that does not require accurate extraction of the contours of the lesions. The innovative aspects of the work include the design and validation of landmarking algorithms, automatic Tabár masking procedures, and various feature descriptors for quantification of similarity and for contour independent classification of mammographic lesions. Characterization of breast tissue patterns is achieved by means of multidirectional Gabor filters. For the classification tasks, pattern recognition strategies, including Fisher linear discriminant analysis, Bayesian classifiers, support vector machines, and neural networks are applied using automatic selection of features and cross-validation techniques. Computer-aided detection of bilateral asymmetry resulted in accuracy up to 0.94, with sensitivity and specificity of 1 and 0.88, respectively. Computer-aided diagnosis of automatically detected lesions provided sensitivity of detection of malignant tumors in the range of [0.70, 0.81] at a range of falsely detected tumors of [0.82, 3.47] per image. The techniques presented in this work are effective in detecting and characterizing various mammographic signs of breast disease.

  • Fractal Analysis of Breast Masses in Mammograms

    Fractal analysis is useful in digital image processing for the characterization of shape roughness and gray-scale texture or complexity. Breast masses present shape and gray-scale characteristics in mammograms that vary between benign masses and malignant tumors. This book demonstrates the use of fractal analysis to classify breast masses as benign masses or malignant tumors based on the irregularity exhibited in their contours and the gray-scale variability exhibited in their mammographic images. A few different approaches are described to estimate the fractal dimension (FD) of the contour of a mass, including the ruler method, box-counting method, and the power spectral analysis (PSA) method. Procedures are also described for the estimation of the FD of the gray-scale image of a mass using the blanket method and the PSA method. To facilitate comparative analysis of FD as a feature for pattern classification of breast masses, several other shape features and texture measures are described in the book. The shape features described include compactness, spiculation index, fractional concavity, and Fourier factor. The texture measures described are statistical measures derived from the gray-level cooccurrence matrix of the given image. Texture measures reveal properties about the spatial distribution of the gray levels in the given image; therefore, the performance of texture measures may be dependent on the resolution of the image. For this reason, an analysis of the effect of spatial resolution or pixel size on texture measures in the classification of breast masses is presented in the book. The results demonstrated in the book indicate that fractal analysis is more suitable for characterization of the shape than the gray-level variations of breast masses, with area under the receiver operating characteristics of up to 0.93 with a dataset of 111 mammographic images of masses. The methods and results presented in the book are useful for computer-aided diagnosis of breast cancer. Table of Contents: Computer-Aided Diagnosis of Breast Cancer / Detection and Analysis of\newline Breast Masses / Datasets of Images of Breast Masses / Methods for Fractal Analysis / Pattern Classification / Results of Classification of Breast Masses / Concluding Remarks

  • Analysis of Oriented Texture: With application to the Detection of Architectural Distortion in Mammograms

    The presence of oriented features in images often conveys important information about the scene or the objects contained; the analysis of oriented patterns is an important task in the general framework of image understanding. 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. In the context of the study of oriented features, low- level analysis includes the detection of oriented features in images; a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field. High- level analysis relates to the discovery of patterns in the orientation field, usually by associating the structure perceived in the orientation field with a geometrical model. 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. In order to illustrate the concepts developed throughout the book, an application is presented of the phase portrait method to computer-aided detection of architectural distortion in mammograms. Table of Contents: Detection of Oriented Features in Images / Analysis of Oriented Patterns Using Phase Portraits / Optimization Techniques / Detection of Sites of Architectural Distortion in Mammograms

  • Computer-aided Detection of Architectural Distortion in Prior Mammograms of Interval Cancer

    Architectural distortion is an important and early sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. Screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. This book presents image processing and pattern recognition techniques to detect architectural distortion in prior mammograms of interval-cancer cases. The methods are based upon Gabor filters, phase portrait analysis, procedures for the analysis of the angular spread of power, fractal analysis, Laws' texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralick's texture features. With Gabor filters and phase-portrait analysis, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws' texture energy measures, and Haralick's 14 texture features were computed. The areas under the receiver operating characteristic (ROC) curves obtained using the features selected by stepwise logistic regression and the leave-one-image-out method are 0.77 with the Bayesian classifier, 0.76 with Fisher linear discriminant analysis, and 0.79 with a neural network classifier. Free-response ROC analysis indicated sensitivities of 0.80 and 0.90 at 5.7 and 8.8 false positives (FPs) per image, respectively, with the Bayesian classifier and the leave-one-image-out method. The present study has demonstrated the ability to detect early signs of breast cancer 15 months ahead of the time of clinical diagnosis, on the average, for interval-cancer cases, with a sensitivity of 0.8 at 5.7 FP/image. The presented computer-aided detection techniques, dedicated to accurate detection and localization of architectural distortion, could lead to efficient detection of early and subtle signs of breast cancer at pre-mass-formation stages. Table of Contents: Introduction / Detection of Early Signs of Breast Cancer / Detection and Analysis of Oriented Patterns / Detection of Potential Sites of Architectural Distortion / Experimental Set Up and Datasets / Feature Selection and Pattern Classification / Analysis of Oriented Patterns Related to Architectural Distortion / Detection of Architectural Distortion in Prior Mammograms / Concluding Remarks



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