Indian Statistical Institute (ISI), invites applications for the post of Research Fellow in Biomedical Engineering research
Project Name: Biomedical Imaging and Machine Learning for Cancer Research
Qualification: ME/ M.Tech in Computer Science/ Engineering, Biomedical Engineering, Electronics/ Electrical Engineering, Information Technology.
Desirable: Knowledge/ research experience in medical image modelling and analysis, machine learning techniques and imaging techniques, and imaging techniques (CT, MRI, PET), DICOM, Fluency in English, both writing and speaking, Readiness to travel to Europe for longer durations. An independent and practical personality and ability to take initiatives.
Pay: Rs.30000 PM
Age Limit: 35 yrs as on 01 April 2011
This is a preview of Research Fellow for Medical imaging required in ISI kolkata[M.Tech Research].
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Recent Advances in Biomedical Imaging and Signal Analysis
M. Unser 
Proceedings of the Eighteenth European Signal Processing Conference (EUSIPCO’10), Ålborg, Denmark, August 23-27, 2010, EURASIP Fellow inaugural lecture.
Wavelets have the remarkable property of providing sparse representations of a wide variety of “natural” images. They have been applied successfully to biomedical image analysis and processing since the early 1990s.
In the first part of this talk, we explain how one can exploit the sparsifying property of wavelets to design more effective algorithms for image denoising and reconstruction, both in terms of quality and computational performance. This is achieved within a variational framework by imposing some ?1-type regularization in the wavelet domain, which favors sparse solutions. We discuss some corresponding iterative skrinkage-thresholding algorithms (ISTA) for sparse signal recovery and introduce a multi-level variant for greater computational efficiency. We illustrate the method with two concrete imaging examples: the deconvolution of 3-D fluorescence micrographs, and the reconstruction of magnetic resonance images from arbitrary (non-uniform) k-space trajectories.
In the second part, we show how to design new wavelet bases that are better matched to the directional characteristics of images. We introduce a general operator-based framework for the construction of steerable wavelets in any number of dimensions. This approach gives access to a broad class of steerable wavelets that are self-reversible and linearly parameterized by a matrix of shaping coefficients; it extends upon Simoncelli’s steerable pyramid by providing much greater wavelet diversity. The basic version of the transform (higher-order Riesz wavelets) extracts the partial derivatives of order N of the signal (e.g., gradient or Hessian). We also introduce a signal-adapted design, which yields a PCA-like tight wavelet frame. We illustrate the capabilities of these new steerable wavelets for image analysis and processing (denoising).
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Medical imaging refers to the techniques and processes used to create images of the human body (or parts thereof) for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). As a discipline and in its widest sense, it is part of biological imaging and incorporates radiology (in the wider sense), radiological sciences, endoscopy, (medical) thermography, medical photography and microscopy (e.g. for human pathological investigations). Measurement and recording techniques which are not primarily designed to produce images, such as electroencephalography (EEG) and magnetoencephalography (MEG) and others, but which produce data susceptible to be represented as maps (i.e. containing positional information), can be seen as forms of medical imaging.
This is a preview of An Introduction To Medical Imaging Modalities For Biomedical Beginners.
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Medical imaging is a mainstay in the field of nuclear medicine. In nuclear medicine, radioactive elements (as isotopes) that are part of specific fluids are introduced into the body (usually by injection into the blood). As it circulates, a particular radioisotope tends to distribute throughout the body at points served by the blood flow and may even concentrate preferentially in certain organs (for example, radioactive iodine in the thyroid gland). As the isotope decays, it gives off radiation (most commonly, gamma rays) which can be intercepted by a gamma camera or other detector. Variations in radiation intensity and in spatial location at point sources in the body activate film or more usually a detector array that responds by mapping the radiation intensity in X-Y space to create an image. The radioisotopes in normal usage have relatively short half lifes, thus decaying rapidly, and minimizing the exposure to damaging radiation.
This is a preview of Basic & Detailed Tutorial on Nuclear Medicine & Imaging for Biomedical Beginners.
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