Conferences related to Tumors

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2016 IEEE International Ultrasonics Symposium (IUS)

International Symposium dealing with recent developments on ultrasound, including ultrasound imaging, transducers, non destructuve testing and physical acoustics.

  • 2015 IEEE International Ultrasonics Symposium (IUS)

    Annual meeting of the UFFC Society that is being held regularly. It is focusing on ultrasonics.

  • 2013 IEEE International Ultrasonics Symposium (IUS)

    the joint IUS, ISAF, IFC, and EFTF conference is aimed at bringing the ultrasonics, ferroelectrics, Frequency Control and Time Forum communities around the world together more closely and through discussions on recent research and development of fundamentals, materials, devices, and applications .

  • 2012 IEEE International Ultrasonics Symposium

    The conference will bring together the community of ultrasonics around the world in the center of Europe for discussion and cooperation and to stimulate the research and development in the widespread field of ultrasonic theories and applications

  • 2011 IEEE International Ultrasonics Symposium (IUS)

    The Symposium is aimed at bringing the ultrasonics communities around the world together more closely and through discussions on recent research and development of ultrasonics theories and applications.

  • 2010 IEEE Ultrasonics Symposium (IUS)

    The conference will cover all high frequency Ultrasound application including medical.

  • 2009 IEEE International Ultrasonics Symposium

    Conference includes short courses on topics of current interest in ultrasonics. The next three days will include parallel oral and poster sessions covering 1) Medical Ultrasonics, 2) Sensors, NDE & Industrial Applications, 3) Physical Acoustics, 4) Microacoustics SAW, FBAR, MEMS, and 5) Transducers & Transducer Materials.

  • 2008 IEEE Ultrasonics Symposium


2011 IEEE 4th International Symposium on Microwave, Antenna, Propagation, and EMC Technologies for Wireless Communications (MAPE)

This Symposium will cover all the basic theories and techniques in the area of Electromagnetic Fields, Microwave Devices, Circuits, or Systems, Antennas & Propagations, Signal Processing, Coding, or Waveforms, Remote Sensing, and EMC Technology necessary for application in wireless communications.

  • 2009 3rd IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE 2009)

    This Symposium will cover all the basic theories and techniques in the area of Electromagnetic Fields, Microwave Devices, Circuits, or Systems, Antennas & Propagations, Signal Processing, Coding, or Waveforms, Remote Sensing, and EMC Technology necessary for application in wireless communications.

  • 2007 International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE 2007)


2008 3rd International Advanced Research Workshop on "In Silico Oncology: Advances and Challenges"

The workshop aims at contributing to the shaping of the emerging field of in silico (computational) oncology. In Silico Oncology is a complex and multiscale combination of sciences and technologies intending to simulate malignant tumour growth and tumour and normal tissue response to therapeutic modalities at all levels of biocomplexity. The long term goal is to quantitatively understand cancer and related phenomena and optimize therapeutic interventions by performing in silico (on the computer) experiments


2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)



Periodicals related to Tumors

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Medical Imaging, IEEE Transactions on

Imaging methods applied to living organisms with emphasis on innovative approaches that use emerging technologies supported by rigorous physical and mathematical analysis and quantitative evaluation of performance.


Microwave Theory and Techniques, IEEE Transactions on

Microwave theory, techniques, and applications as they relate to components, devices, circuits, and systems involving the generation, transmission, and detection of microwaves.


Selected Topics in Quantum Electronics, IEEE Journal of

40% devoted to special issues published in J. Quantum Electronics. Other topics: solid-state lasers, fiber lasers, optical diagnostics for semi-conductor manufacturing, and ultraviolet lasers and applications.




Xplore Articles related to Tumors

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Reduced Growth Rate of Tumors from Melanoma B16 Cells Exposed to Focused Shock Waves

P. Sunka; V. Stelmashuk; J. Benes; P. Pouckova Conference Record of the 2006 Twenty-Seventh International Power Modulator Symposium, 2006

We have developed a generator of two successive shock waves focused to a common focal point. Amplitude of the pressure waves reaches up to 100 MPa at the focus and the rarefaction waves of 25 MPa in amplitude produce cavitations. Schlieren photography of the focal region has demonstrated that interaction of the two successive shocks results in creation of a ...


Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET

Hongmei Mi; Caroline Petitjean; Bernard Dubray; Pierre Vera; Su Ruan IEEE Transactions on Medical Imaging, 2014

We propose a patient-specific model based on partial differential equation to predict the evolution of lung tumors during radiotherapy. The evolution of tumor cell density is formulated by three terms: 1) advection describing the advective flux transport of tumor cells, 2) proliferation representing the tumor cell proliferation modeled as Gompertz differential equation, and 3) treatment quantifying the radiotherapeutic efficacy from ...


Effects of perfusion and vascular architecture on contrast dispersion: Validation in ex-vivo porcine liver under machine perfusion

Simona Turco; Christina Keravnou; Ruud J. G. van Sloun; Hessel Wijkstra; Mike Averkiou; Massimo Mischi 2016 IEEE International Ultrasonics Symposium (IUS), 2016

Dynamic contrast enhanced ultrasound (DCE-US) enables imaging of cancer angiogenesis by quantification of perfusion and dispersion. Although increased perfusion may be found in areas of active angiogenesis due to increased demands for blood supply, decreased perfusion may be caused by the decreased efficiency and functionality, typical of cancer angiogenic microvasculature. Contrast dispersion, mainly determined by the flow profile in large ...


Adaptive segmentation of gray areas in dermoscopy images

Gianluca Sforza; Giovanna Castellano; R. Joe Stanley; William V. Stoecker; Jason Hagerty 2011 IEEE International Symposium on Medical Measurements and Applications, 2011

In this work, a dermoscopic image analysis technique is proposed. A novel approach, based on the detection of gray areas using image analysis techniques is explored. To this aim, a statistical histogram analysis is carried out using the HSB color space to derive the relationship between the skewness and the mean of the brightness color plane histogram. The derived framework ...


Framework for abnormality detection in magnetic resonance brain images

Aleksandar Stojak; Eva Tuba; Milan Tuba 2016 24th Telecommunications Forum (TELFOR), 2016

Magnetic resonance images (MRI) are often the most powerful diagnostics tool in medicine. They are especially useful for brain examination where precise differentiation of various tissues is possible with the goal of discovering abnormalities. Different abnormalities appear in images as regions with different features. In this paper we propose a software framework for segmentation of abnormalities in brain MRI. Main ...


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Educational Resources on Tumors

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eLearning

Reduced Growth Rate of Tumors from Melanoma B16 Cells Exposed to Focused Shock Waves

P. Sunka; V. Stelmashuk; J. Benes; P. Pouckova Conference Record of the 2006 Twenty-Seventh International Power Modulator Symposium, 2006

We have developed a generator of two successive shock waves focused to a common focal point. Amplitude of the pressure waves reaches up to 100 MPa at the focus and the rarefaction waves of 25 MPa in amplitude produce cavitations. Schlieren photography of the focal region has demonstrated that interaction of the two successive shocks results in creation of a ...


Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET

Hongmei Mi; Caroline Petitjean; Bernard Dubray; Pierre Vera; Su Ruan IEEE Transactions on Medical Imaging, 2014

We propose a patient-specific model based on partial differential equation to predict the evolution of lung tumors during radiotherapy. The evolution of tumor cell density is formulated by three terms: 1) advection describing the advective flux transport of tumor cells, 2) proliferation representing the tumor cell proliferation modeled as Gompertz differential equation, and 3) treatment quantifying the radiotherapeutic efficacy from ...


Effects of perfusion and vascular architecture on contrast dispersion: Validation in ex-vivo porcine liver under machine perfusion

Simona Turco; Christina Keravnou; Ruud J. G. van Sloun; Hessel Wijkstra; Mike Averkiou; Massimo Mischi 2016 IEEE International Ultrasonics Symposium (IUS), 2016

Dynamic contrast enhanced ultrasound (DCE-US) enables imaging of cancer angiogenesis by quantification of perfusion and dispersion. Although increased perfusion may be found in areas of active angiogenesis due to increased demands for blood supply, decreased perfusion may be caused by the decreased efficiency and functionality, typical of cancer angiogenic microvasculature. Contrast dispersion, mainly determined by the flow profile in large ...


Adaptive segmentation of gray areas in dermoscopy images

Gianluca Sforza; Giovanna Castellano; R. Joe Stanley; William V. Stoecker; Jason Hagerty 2011 IEEE International Symposium on Medical Measurements and Applications, 2011

In this work, a dermoscopic image analysis technique is proposed. A novel approach, based on the detection of gray areas using image analysis techniques is explored. To this aim, a statistical histogram analysis is carried out using the HSB color space to derive the relationship between the skewness and the mean of the brightness color plane histogram. The derived framework ...


Framework for abnormality detection in magnetic resonance brain images

Aleksandar Stojak; Eva Tuba; Milan Tuba 2016 24th Telecommunications Forum (TELFOR), 2016

Magnetic resonance images (MRI) are often the most powerful diagnostics tool in medicine. They are especially useful for brain examination where precise differentiation of various tissues is possible with the goal of discovering abnormalities. Different abnormalities appear in images as regions with different features. In this paper we propose a software framework for segmentation of abnormalities in brain MRI. Main ...


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IEEE-USA E-Books

  • No title

    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 desc ibed 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 br ast cancer. Table of Contents: Computer-Aided Diagnosis of Breast Cancer / Detection and Analysis ofnewline Breast Masses / Datasets of Images of Breast Masses / Methods for Fractal Analysis / Pattern Classification / Results of Classification of Breast Masses / Concluding Remarks

  • No title

    Malignant tumors due to breast cancer and masses due to benign disease appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. In spite of the established importance of shape factors in the analysis of breast tumors and masses, difficulties exist in obtaining accurate and artifact-free boundaries of the related regions from mammograms. Whereas manually drawn contours could contain artifacts related to hand tremor and are subject to intra-observer and inter- observer variations, automatically detected contours could contain noise and inaccuracies due to limitations or errors in the procedures for the detection and segmentation of the related regions. Modeling procedures are desired to eliminate the artifa ts in a given contour, while preserving the important and significant details present in the contour. This book presents polygonal modeling methods that reduce the influence of noise and artifacts while preserving the diagnostically relevant features, in particular the spicules and lobulations in the given contours. In order to facilitate the derivation of features that capture the characteristics of shape roughness of contours of breast masses, methods to derive a signature based on the turning angle function obtained from the polygonal model are described. Methods are also described to derive an index of spiculation, an index characterizing the presence of convex regions, an index characterizing the presence of concave regions, an index of convexity, and a measure of fractal dimension from the turning angle function. Results of testing the methods with a set of 111 contours of 65 benign masses and 46 malignant tumors are presented and discussed. It is shown that shape modeling and a alysis can lead to classification accuracy in discriminating between benign masses and malignant tumors, in terms of the area under the receiver operating characteristic curve, of up to 0.94. The methods have applications in modeling and analysis of the shape of various types of regions or objects in images, computer vision, computer graphics, and analysis of biomedical images, with particular significance in computer-aided diagnosis of breast cancer. Table of Contents: Analysis of Shape / Polygonal Modeling of Contours / Shape Factors for Pattern Classification / Classification of Breast Masses

  • Maxillofacial Virtual Surgery from 3D CT Images

    The history of scientific development is characterized by some key moments owing to the union of competences coming from far away research areas. Virtual surgery, a new discipline that recently appeared among the medical sciences, is an excellent example of contribution from medical and computational knowledges to health development and progress. Craniofacial surgery is a surgical branch regarding study and treatment of any kind of disease (malformations, trauma, and tumors) affecting the face. The anatomic and functional complexity of the face and skull, characterized by the presence of the eyes, ear, nose, mouth, facial nerves, and the proximity of important the brain and the respiratory system, make this area extremely hazardous for even skilled surgeons and a dangerous mine field for residents, fellows, and surgeons in training. For scientific and teaching reasons, we planned a research project for craniofacial surgery simulation from 3-D CT images. Generally, the goal of computer-based surgery simulation is to enable a surgeon to experiment with different surgical procedures in an artificial environment. We propose a simulation method that allows one to deal with extremely complex anatomical geometries. The computational grid is the natural Cartesian grid in which the acquired 3-D image is defined. The rest of the chapter discusses theoretical basis of the linear elastic problem with embedded Dirichlet boundary conditions, the numerical approximation scheme and the solution method, and the results obtained by the application of the method to a number of datasets. We show comparisons between virtual and real operations in real patients, and consider future work.

  • No title

    Segmentation and landmarking of computed tomographic (CT) images of pediatric patients are important and useful in computer-aided diagnosis (CAD), treatment planning, and objective analysis of normal as well as pathological regions. Identification and segmentation of organs and tissues in the presence of tumors are difficult. Automatic segmentation of the primary tumor mass in neuroblastoma could facilitate reproducible and objective analysis of the tumor's tissue composition, shape, and size. However, due to the heterogeneous tissue composition of the neuroblastic tumor, ranging from low-attenuation necrosis to high-attenuation calcification, segmentation of the tumor mass is a challenging problem. In this context, methods are described in this book for identification and segmentation of several abdominal and thoracic landmarks to assist in the segmentation of neuroblastic tumors in pediatric CT images. Methods to identify and segment automatically the peripheral artifacts and tissu s, the rib structure, the vertebral column, the spinal canal, the diaphragm, and the pelvic surface are described. Techniques are also presented to evaluate quantitatively the results of segmentation of the vertebral column, the spinal canal, the diaphragm, and the pelvic girdle by comparing with the results of independent manual segmentation performed by a radiologist. The use of the landmarks and removal of several tissues and organs are shown to assist in limiting the scope of the tumor segmentation process to the abdomen, to lead to the reduction of the false-positive error, and to improve the result of segmentation of neuroblastic tumors. Table of Contents: Introduction to Medical Image Analysis / Image Segmentation / Experimental Design and Database / Ribs, Vertebral Column, and Spinal Canal / Delineation of the Diaphragm / Delineation of the Pelvic Girdle / Application of Landmarking / Concluding Remarks

  • Appendix B: Magnetography, October 1971

    On September 2, 1971, the chemist Paul Lauterbur had an idea that would change the practice of medical research. Considering recent research findings about the use of nuclear magnetic resonance (NMR) signals to detect tumors in tissue samples, Lauterbur realized that the information from NMR signals could be recovered in the form of images -- and thus obtained noninvasively from a living subject. It was an unexpected epiphany: he was eating a hamburger at the time. Lauterbur rushed out to buy a notebook in which to work out his idea; he completed his notes a few days later. He had discovered the basic method used in all MRI scanners around the world, and for this discovery he would share the Nobel Prize for Physiology or Medicine in 2003. This book, by Lauterbur's wife and scientific partner, M. Joan Dawson, is the story of Paul Lauterbur's discovery and the subsequent development of the most important medical diagnostic tool since the X-ray.With MRI, Lauterbur had discovered an entirely new principle of imaging. Dawson explains the science behind the discovery and describes Lauterbur's development of the idea, his steadfastness in the face of widespread skepticism and criticism, and related work by other scientists including Peter Mansfield (Lauterbur's Nobel co-recipient), and Raymond Damadian (who famously feuded with Lauterbur over credit for the ideas behind MRI). She offers not only the story of one man's passion for his work but also a case study of how science is actually done: a flash of insight followed by years of painstaking work.

  • Index

    On September 2, 1971, the chemist Paul Lauterbur had an idea that would change the practice of medical research. Considering recent research findings about the use of nuclear magnetic resonance (NMR) signals to detect tumors in tissue samples, Lauterbur realized that the information from NMR signals could be recovered in the form of images -- and thus obtained noninvasively from a living subject. It was an unexpected epiphany: he was eating a hamburger at the time. Lauterbur rushed out to buy a notebook in which to work out his idea; he completed his notes a few days later. He had discovered the basic method used in all MRI scanners around the world, and for this discovery he would share the Nobel Prize for Physiology or Medicine in 2003. This book, by Lauterbur's wife and scientific partner, M. Joan Dawson, is the story of Paul Lauterbur's discovery and the subsequent development of the most important medical diagnostic tool since the X-ray.With MRI, Lauterbur had discovered an entirely new principle of imaging. Dawson explains the science behind the discovery and describes Lauterbur's development of the idea, his steadfastness in the face of widespread skepticism and criticism, and related work by other scientists including Peter Mansfield (Lauterbur's Nobel co-recipient), and Raymond Damadian (who famously feuded with Lauterbur over credit for the ideas behind MRI). She offers not only the story of one man's passion for his work but also a case study of how science is actually done: a flash of insight followed by years of painstaking work.

  • Epilogue

    On September 2, 1971, the chemist Paul Lauterbur had an idea that would change the practice of medical research. Considering recent research findings about the use of nuclear magnetic resonance (NMR) signals to detect tumors in tissue samples, Lauterbur realized that the information from NMR signals could be recovered in the form of images -- and thus obtained noninvasively from a living subject. It was an unexpected epiphany: he was eating a hamburger at the time. Lauterbur rushed out to buy a notebook in which to work out his idea; he completed his notes a few days later. He had discovered the basic method used in all MRI scanners around the world, and for this discovery he would share the Nobel Prize for Physiology or Medicine in 2003. This book, by Lauterbur's wife and scientific partner, M. Joan Dawson, is the story of Paul Lauterbur's discovery and the subsequent development of the most important medical diagnostic tool since the X-ray.With MRI, Lauterbur had discovered an entirely new principle of imaging. Dawson explains the science behind the discovery and describes Lauterbur's development of the idea, his steadfastness in the face of widespread skepticism and criticism, and related work by other scientists including Peter Mansfield (Lauterbur's Nobel co-recipient), and Raymond Damadian (who famously feuded with Lauterbur over credit for the ideas behind MRI). She offers not only the story of one man's passion for his work but also a case study of how science is actually done: a flash of insight followed by years of painstaking work.

  • Appendix C: Draft Disclosure, August 1972

    On September 2, 1971, the chemist Paul Lauterbur had an idea that would change the practice of medical research. Considering recent research findings about the use of nuclear magnetic resonance (NMR) signals to detect tumors in tissue samples, Lauterbur realized that the information from NMR signals could be recovered in the form of images -- and thus obtained noninvasively from a living subject. It was an unexpected epiphany: he was eating a hamburger at the time. Lauterbur rushed out to buy a notebook in which to work out his idea; he completed his notes a few days later. He had discovered the basic method used in all MRI scanners around the world, and for this discovery he would share the Nobel Prize for Physiology or Medicine in 2003. This book, by Lauterbur's wife and scientific partner, M. Joan Dawson, is the story of Paul Lauterbur's discovery and the subsequent development of the most important medical diagnostic tool since the X-ray.With MRI, Lauterbur had discovered an entirely new principle of imaging. Dawson explains the science behind the discovery and describes Lauterbur's development of the idea, his steadfastness in the face of widespread skepticism and criticism, and related work by other scientists including Peter Mansfield (Lauterbur's Nobel co-recipient), and Raymond Damadian (who famously feuded with Lauterbur over credit for the ideas behind MRI). She offers not only the story of one man's passion for his work but also a case study of how science is actually done: a flash of insight followed by years of painstaking work.



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