Conferences related to Benign tumors

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2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting

The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science


2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

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


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

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 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 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.

  • 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)


2020 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 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


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Periodicals related to Benign tumors

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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.


Engineering in Medicine and Biology Magazine, IEEE

Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.


Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.


Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.


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Most published Xplore authors for Benign tumors

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Xplore Articles related to Benign tumors

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Determining the through-plane resolution of strain-encoded MRI

Proceedings IEEE International Symposium on Biomedical Imaging, 2002

Strain encoded magnetic resonance elastography (SENC MRE) has been proposed for imaging elastic variation by obtaining images whose intensity directly represents through-plane strain. It is useful for detecting tumors because tumors exhibit different elastic properties than the surrounding tissue. SENC MRE, however, assumes homogeneous tissue elasticity in the through-plane direction, an assumption that requires the acquisition of relatively thin image ...


Computer aided diagnosis (CAD) of breast mass on ultrasonography and scintimammography

Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005., 2005

Both breast ultrasonography (US) and scintimammography (SMM) shows limited diagnostic accuracy in the differential diagnosis of breast cancer. We investigated whether the diagnostic performance of computer-aided diagnosis (CAD) of US was improved by adding SMM results. We retrospectively reviewed 40 breast US images and corresponding SMM images from 40 patients who presented with breast masses (21 malignant and 19 benign ...


Classifying Digital Mammogram Masses Using Univariate ANOVA Discriminant Analysis

2009 International Conference on Advances in Recent Technologies in Communication and Computing, 2009

An Univariate Analysis Of Variance (ANOVA) Discriminant Analysis (DA) classifier is proposed for classifying the masses present in mammogram. This approach combines the 19 shape properties of the mass regions and classifies the masses as benign or malignant using Univariate ANOVA. The experiment is performed on DDSM database images. Experimental results shows that the proposed method reaches high classification accuracy ...


Adaptive filter to detect rounded convex regions: iris filter

Proceedings of 13th International Conference on Pattern Recognition, 1996

This paper proposes a unique filter, called "iris filter", which evaluates the degree of convergence of gradient vectors in the neighborhood of the pixel of interest. The generalized iris filter and its simplified one are given. The degree of convergence is related to the distribution of orientations of gradient vectors. The region of support of the iris filter is controlled ...


Shape based classification of breast tumors using fractal analysis

2009 International Multimedia, Signal Processing and Communication Technologies, 2009

In this paper we adopt FFT based fractal analysis method. With the help FFT based method breast tumors (benign and malignant) are classified based on their shapes. In general malignant tumors contour have rough and irregular shapes whereas benign contour have smooth and macrolobulated shapes. In this paper we present a fractal based Fourier transform method to classify the contours. ...


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Educational Resources on Benign tumors

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IEEE-USA E-Books

  • Determining the through-plane resolution of strain-encoded MRI

    Strain encoded magnetic resonance elastography (SENC MRE) has been proposed for imaging elastic variation by obtaining images whose intensity directly represents through-plane strain. It is useful for detecting tumors because tumors exhibit different elastic properties than the surrounding tissue. SENC MRE, however, assumes homogeneous tissue elasticity in the through-plane direction, an assumption that requires the acquisition of relatively thin image slices. This causes a reduction in the signal-to-noise-ratio (SNR) of the images and lengthens the scanning time when acquiring large volumes. In this paper, we evaluated imaging with thick slices (>10 mm) where the homogeneity assumption would fail in cases of small tumors that are thinner than the image slice. We propose enhancing the SENC MRE technique to detect thin tumors by modifying the image slice profile. Phantom experiments were performed to demonstrate the ability of the improved SENC MRE technique to detect the presence of thin tumors, as small as one quarter of the slice thickness.

  • Computer aided diagnosis (CAD) of breast mass on ultrasonography and scintimammography

    Both breast ultrasonography (US) and scintimammography (SMM) shows limited diagnostic accuracy in the differential diagnosis of breast cancer. We investigated whether the diagnostic performance of computer-aided diagnosis (CAD) of US was improved by adding SMM results. We retrospectively reviewed 40 breast US images and corresponding SMM images from 40 patients who presented with breast masses (21 malignant and 19 benign tumors). The morphologic features of the breast lesions on US were extracted and quantitated using the automated CAD software program (So no Eye, CAD Impact, Inc., Seoul, Korea), which calculated the probability of malignancy based on the stored database. The quantitative data of SMM were obtained as the uptake ratio of lesion to contralateral normal breast on SMM SPECT. The diagnostic accuracy of CAD of US and SMM was determined using ROC curve analysis, respectively. The best discriminating function combining the CAD results of US and SMM uptake value was created using linear discriminant analysis and the diagnostic performance was compared to that using only one diagnostic modality. Both US and SMM showed a relatively good diagnostic accuracy (area under curve=0.831 and 0.846, respectively). Combining CAD results of US and SMM resulted in improved diagnostic accuracy (area under curve =0.860), but it was not statistically significant. The diagnostic performance of CAD of breast US in the differential diagnosis of the breast mass was not significantly improved by adding SMM. However, SMM SPECT may be complementary to CAD of US in differential diagnosis of breast cancer.

  • Classifying Digital Mammogram Masses Using Univariate ANOVA Discriminant Analysis

    An Univariate Analysis Of Variance (ANOVA) Discriminant Analysis (DA) classifier is proposed for classifying the masses present in mammogram. This approach combines the 19 shape properties of the mass regions and classifies the masses as benign or malignant using Univariate ANOVA. The experiment is performed on DDSM database images. Experimental results shows that the proposed method reaches high classification accuracy in compared to existing algorithms.

  • Adaptive filter to detect rounded convex regions: iris filter

    This paper proposes a unique filter, called "iris filter", which evaluates the degree of convergence of gradient vectors in the neighborhood of the pixel of interest. The generalized iris filter and its simplified one are given. The degree of convergence is related to the distribution of orientations of gradient vectors. The region of support of the iris filter is controlled so that the degree of convergence of gradient vectors in it becomes maximum. It means that the size and the shape of the region of support changes adaptively according to the distribution pattern of gradient vectors around the pixel of interest. Theoretical analysis using models of a rounded convex region and a semi-cylindrical region is given. It shows that rounded convex regions are mostly enhanced even if their original contrasts to their background are weak and elongated objects are suppressed. However, the filter output is 1//spl pi/ at the boundaries of rounded convex regions and semi-cylindrical ones in spite of their contrast. This absolute value can be used to detect boundaries of those objects. The proposed filter is effective to enhance and detect rounded convex regions with various sizes and contrasts.

  • Shape based classification of breast tumors using fractal analysis

    In this paper we adopt FFT based fractal analysis method. With the help FFT based method breast tumors (benign and malignant) are classified based on their shapes. In general malignant tumors contour have rough and irregular shapes whereas benign contour have smooth and macrolobulated shapes. In this paper we present a fractal based Fourier transform method to classify the contours. The log -log magnitude frequency response plot and rose plot (for average radial distance and angle variations in terms of average slops and slope of intercept) are used in this study in order to extract the features for classifications.

  • Linear decision fusions in multilayer perceptrons for breast cancer diagnosis

    We introduce a non-parametric linear decision fusion called perceptron average (PA) for breast cancer diagnosis. We concretely compare the accuracy between both two fusion strategies for breast cancer diagnosis. The PA fusion demonstrates a higher overall diagnostic accuracy versus the weighted average fusion, and the PA fusion method also exhibits a better capability of generalization when a casualty of training data sizes. Moreover, the PA fusion gains a larger area covered by its receiver operating characteristic curve

  • The investigation of contrast-agent enhanced ultrasound thermal effect

    None

  • Quantification of shrinkage of lung lobe from chest CT images using the 3D extended Voronoi division and its application to the benign/malignant discrimination of tumor shadows

    In this paper, we propose a method to quantify the convergence of tissue in lung caused by cancer, using the three-dimensional (3D) extended Voronoi division from chest X-ray CT images. The convergence is the phenomenon that the pulmonary tumors pull tissues such as blood vessels and interstitium toward the pulmonary tumors. Because the malignant tumors (especially adenocarcinoma) often accompanies the convergence, quantification of the convergence is useful for the benign/malignant discrimination. We first calculate the Voronoi diagrams using the vessel regions which were classified according to the radius of vessels. Then a feature was calculated using the volumes of the Voronoi regions in the whole of lung region and those of the neighborhood of tumor region. The significant correlation between the proposed feature and the existence of the convergence is shown experimentally using actual CT images.

  • Shape and Boundary Analysis for Classification of Breast Masses

    Malignant breast tumors appear spiculate or microlobulate in the boundary and irregular in shape. But benign breast masses appear smooth in the boundary and round in shape. We used polygonal modeling to draw Index of spiculation(SI), index of lobule(IF), measure of fractal dimension (FD) and measure of circularity (C) to represent the characteristic of the boundary and the shape of breast masses. The boundary of the mass is divided into three type: 1. spiculate; 2. microlobulate; 3.smooth.The shape of the mass is divided into two types: 1. irregular; 2. sub-circular. Considering the boundary and the shape style the masses can be divided into malignant ones and benign ones. The test is based on a dataset of 93 images from MIAS with 54 benign masses and 39 malignant tumors. The accuracy of the classification reach 0.9265 in terms of the area(A<sub>z</sub>) under the ROC curve.

  • Evaluation of surface roughness of tumor using neural network

    Since surface roughness of a malignant tumor is more remarkable than that of a benign tumor, it is possible to classify pathological states of the tumor by computing the degree of surface roughness. We have proposed a method for the segmentation of the tumor in ultrasonic echography and confirmed the feasibility of the technique. This paper describes a neural network based classifier using the surface roughness of a breast tumor which is extracted from ultrasonic echography. We define nine parameters for evaluation of the surface roughness, which form an artificial neural network (ANN) input vector. The ANN output sequence displays two types of pathological states; malignant and benign. We use twenty seven benign tumors and twenty four malignant tumors for the feasibility study. Twenty four tumors are used for learning data and the other tumors are used for the trial. As a result, successful classification is obtained.



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