Biomedical image processing
753 resources related to Biomedical image processing
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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.
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.
IEEE International Conference on Plasma Science (ICOPS) is an annual conference coordinated by the Plasma Science and Application Committee (PSAC) of the IEEE Nuclear & Plasma Sciences Society.
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
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 ...
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.
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.
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.
IEE Colloquium on Morphological and Nonlinear Image Processing Techniques, 1993
IEE Colloquium on Image Processing for Disabled People, 1992
IEE Colloquium on Functional Imaging, 1994
IEEE Robotics & Automation Magazine, 2014
The radiology and surgery worlds need to merge for operations guided by imagery, such as mini-invasive procedures (stenting, valve implants, and so on). Consequently, the current trend is the hybridization of radiology and surgery rooms. These rooms are said to be hybrid when the operating room combines the features of a conventional cardiac surgery operating room with those of a ...
Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop, 1997
Engineering in Medicine and Biology: Segment 3
Zohara Cohen AMA EMBS Individualized Health
Tapping the Computing Power of the Unconscious Brain
ICASSP 2010 - New Signal Processing Application Areas
Dr. Scott Fish
Robotics History: Narratives and Networks Oral Histories: Ray Jarvis
Noise Enhanced Information Systems: Denoising Noisy Signals with Noise
Robotics History: Narratives and Networks Oral Histories: Minoru Asada
2011 IEEE Jack S. Kilby Signal Processing Medal - Ingrid Daubechies
2011 IEEE Medal for Innovations in Healthcare Technology - Harrison H. Barrett
Martin Vetterli accepts the IEEE Jack S. Kilby Signal Processing Medal - Honors Ceremony 2017
ICASSP 2010 - Science and Technology of DSP
"Approximation- Beyond the Tyranny of Digital Computing," (Rebooting Computing)
ICASSP 2010 - Advances in Neural Engineering
How Facial Analysis Technology Can Help Children with Genetic Disorders - IEEE Region 4 Technical Presentation
IMS 2015: Robert H. Caverly - Aspects of Magnetic Resonance Imaging
Quantization Without Fine-Tuning - Tijimen Blankevoort - LPIRC 2019
Neural Processor Design Enabled by Memristor Technology - Hai Li: 2016 International Conference on Rebooting Computing
The Emerging Field of Biomedical Engineering
The radiology and surgery worlds need to merge for operations guided by imagery, such as mini-invasive procedures (stenting, valve implants, and so on). Consequently, the current trend is the hybridization of radiology and surgery rooms. These rooms are said to be hybrid when the operating room combines the features of a conventional cardiac surgery operating room with those of a radiology room, thereby linking medical imaging and surgery.
The notion of linogram is introduced. It corresponds to the notion of a sinogram in the conventional representation of projection data in image reconstruction. In the sinogram the points corresponding to rays that go through a fixed point in the cross section to be reconstructed all fall on a sinusoidal curve. In the linogram, however, these points fall on a straight line, so back projection corresponds to integration along straight lines in the linogram. A theorem is described which expresses the back projection operator in terms of the Radon transform and simple changes of variables. A novel image reconstruction method based on the theorem is introduced.<<ETX>>
Image segmentation is a crucial step in a wide range of medical image processing systems. It is useful in visualization of the different objects present in the image. For example separation of the soft, boney tissues and background on the lateral skull X-ray plays an important role in producing cephalometric tracing and hence producing accurate cephalometric evaluation used in orthodontic practice. In spite of the several methods available in the literature, image segmentation still a challenging problem in most of the image processing applications. The challenge comes from the fuzziness of image objects and the overlapping of the different regions. In this paper we propose fast auto adaptive image segmentation algorithm for finding the optimal thresholds for segmenting gray scale images. The proposed method is based on minimizing a fuzzy index which decreases as the similarity between pixels increases. The system uses initial estimates of the parameters of the fuzzy subsets derived from the image histogram then uses fuzzy entropy as cost measure to maximize the similarity between pixels of the same subset. Experimental results demonstrate the effectiveness of the proposed approach.
Medical image segmentation is one of the most productive research areas in medical image processing. The goal of most new image segmentation algorithms is to achieve higher segmentation accuracy than existing algorithms. But the issue of quantitative, reproducible validation of segmentation results, and the questions: What is segmentation accuracy?, and: What segmentation accuracy can a segmentation algorithm achieve ? remain wide open. The creation of a validation framework is relevant and necessary for consistent and realistic comparisons of existing, new and future segmentation algorithms. An important component of a reproducible and quantitative validation framework for segmentation algorithms is a composite index that will measure segmentation performance at a variety of levels. We present a prototype composite index that includes the measurement of seven metrics on segmented image sets. We explain how the composite index is a more complete and robust representation of algorithmic performance than currently used indices that rate segmentation results using a single metric. Our proposed index can be read as an averaged global metric or as a series of algorithmic ratings that will allow the user to compare how an algorithm performs under many categories.
Image subtraction is widely used in angiography as a means of highlighting differences induced by contrast agents. New knowledge of previously unsuspected causes of disease, in particular, secondhand smoke exposure, spurs interest in pushing the limits of early accurate diagnosis. Simple image subtraction induces artifacts causing problems for ensuing measurements and 3D reconstruction. Image registration techniques have been used to partially solve this problem. However, a complete registration is slow, and misregistration often occurs in images where bones are surrounded by vessels with similar image characteristics. We propose an approach based on the idea of global match followed by local refinements. In the global match, an image pair is aligned using a similarity measure so as to reduce overall difference. In the local refinements, localized displacements and deformations of tissue are handled by a combination of techniques: image registration, region growing, erosion, and dilation. This approach is fast compared to registration based image subtraction and it can find vessels abutting a bone. It is designed to be especially suitable for large cross-section image stacks. With additional vessel connectivity analysis between adjacent slices, the algorithm provides a good foundation for 3D vessel reconstruction.
Real-time image rotation forms a core operation in many applications such as medical image processing and computer vision. High-throughput computations for image rotation are a common requirement in real-time image processing. A VLSI design for image rotation that employs CORDIC was discussed in Ghosh et al. (1994). In this paper, we propose novel techniques to increase the throughput of the CORDIC computations, thereby notably improving the overall performance of the rotation unit with acceptable increase in VLSI area. An efficient sign- prediction method called BTSP (Binary-Tree based Sign Prediction) is proposed in our redundant CORDIC system to eliminate the sign detection process. Our investigations show that the BTSP based CORDIC algorithm for realtime rotation of a 512/spl times/512-pixel image, has a significant speed-up over existing redundant CORDIC methods with reduced hardware area.
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