Counterflow dielectrophoresis for trypanosome enrichment and detection in blood

Human African trypanosomiasis or sleeping sickness is a deadly disease endemic in sub-Saharan Africa, caused by single-celled protozoan parasites. Although it has been targeted for elimination by 2020, this will only be realized if diagnosis can be improved to enable identification and treatment of afflicted patients. Existing techniques of detection are restricted by their limited field-applicability, sensitivity and capacity for automation. Microfluidic-based technologies offer the potential for highly sensitive automated devices that could achieve detection at the lowest levels of parasitemia and consequently help in the elimination programme. In this work we implement an electrokinetic technique for the separation of trypanosomes from both mouse and human blood. This technique utilises differences in polarisability between the blood cells and trypanosomes to achieve separation through opposed bi-directional movement (cell counterflow). We combine this enrichment technique with an automated image analysis detection algorithm, negating the need for a human operator

Steerable filters and local analysis of image structure

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Architecture, 1992.Includes bibliographical references (leaves 124-133).by William Tafel Freeman.Ph.D

A polar prediction model for learning to represent visual transformations

All organisms make temporal predictions, and their evolutionary fitness level depends on the accuracy of these predictions. In the context of visual perception, the motions of both the observer and objects in the scene structure the dynamics of sensory signals, allowing for partial prediction of future signals based on past ones. Here, we propose a self-supervised representation-learning framework that extracts and exploits the regularities of natural videos to compute accurate predictions. We motivate the polar architecture by appealing to the Fourier shift theorem and its group-theoretic generalization, and we optimize its parameters on next-frame prediction. Through controlled experiments, we demonstrate that this approach can discover the representation of simple transformation groups acting in data. When trained on natural video datasets, our framework achieves better prediction performance than traditional motion compensation and rivals conventional deep networks, while maintaining interpretability and speed. Furthermore, the polar computations can be restructured into components resembling normalized simple and direction-selective complex cell models of primate V1 neurons. Thus, polar prediction offers a principled framework for understanding how the visual system represents sensory inputs in a form that simplifies temporal prediction

Elliptical Monogenic Wavelets for the analysis and processing of color images

International audienceThis paper studies and gives new algorithms for image processing based on monogenic wavelets. Existing greyscale monogenic filterbanks are reviewed and we reveal a lack of discussion about the synthesis part. The monogenic synthesis is therefore defined from the idea of wavelet modulation, and an innovative filterbank is constructed by using the Radon transform. The color extension is then investigated. First, the elliptical Fourier atom model is proposed to generalize theanalytic signal representation for vector-valued signals. Then a color Riesz-transform is defined so as to construct color elliptical monogenic wavelets. Our Radon-based monogenic filterbank can be easily extended to color according to this definition. The proposed wavelet representation provides efficient analysis of local features in terms of shape and color, thanks to the concepts of amplitude, phase, orientation, and ellipse parameters. The synthesis from local features is deeply studied. We conclude the article by defining the color local frequency, proposing an estimation algorithm

Augmented Slepians: Bandlimited Functions that Counterbalance Energy in Selected Intervals

Slepian functions provide a solution to the optimization problem of joint time-frequency localization. Here, this concept is extended by using a generalized optimization criterion that favors energy concentration in one interval while penalizing energy in another interval, leading to the "augmented" Slepian functions. Mathematical foundations together with examples are presented in order to illustrate the most interesting properties that these generalized Slepian functions show. Also the relevance of this novel energy-concentration criterion is discussed along with some of its applications

Circuit Techniques for Multiple and Wideband Beamforming

University of Minnesota Ph.D. dissertation.June 2018. Major: Electrical Engineering. Advisor: Ramesh Harjani. 1 computer file (PDF); x, 102 pages.This thesis presents different architectures with regard to multiple beamforming and wideband phased array transceiver. Three different designs are implemented in TSMC 65nm RF CMOS to demonstrate different solutions. The design in this thesis have included major RF blocks in state-of-art wireless transceiver: RF receiver, local oscillator, and RF transmitter. First, a RF/analog FFT based four-channel four-beam receiver with progressive partial spatial ltering is proposed. This architecture is particularly well suited for MIMO systems where multiple beams are used to increase throughput. Like the FFT, the proposed architecture reuses computations for multi-beam systems. In particular, the proposed architecture redistributes the computations so as to maximize the reuse of the structure that already exist in a receiver chain. In many fashions the architecture is quite similar to a Butler matrix but unlike the Butler matrix it does not use large passive components at RF. Further, we exploit the normally occurring quadrature down-conversion process to implement the tap weights. In comparison to traditional MIMO architectures, that effectively duplicate each path, the distributed computations of this architecture provide partial spatial ltering before the final stage, improving interference rejection for the blocks between the LNA and the ADC. Additionally, because of the spatial ltering prior to the ADC, a single interferer only jams a single beam allowing for continued operation though at a lower combined throughput. The four-beam receiver core prototype in 65nm CMOS implements the basic FFT based architecture but does not include an LNA or extensive IF stages. This four-channel design consumes 56mW power and occupies an active area of 0:65mm2 excluding pads and test circuits. Second, a wideband phased array receiver architecture with simultaneous spectral and spatial filtering by sub-harmonic injection oscillators is presented. The design avoids using expensive delay elements by many conventional wideband phased array. Different from prior art of channelization which cannot solve beam-squinting issue among the sub-channels, we use sub-harmonic injection locking scheme, which make the center frequencies of all sub-channels point to the same spatial direction to overcome beam-squinting issue. The low frequency, low power and narrowband phase shifters are placed at LO in comparison to conventional way of placing delay elements or phase shifters in the signal path. This avoids receiver performance degradation from delay elements or phase shifters. The simultaneous spectral and spatial ltering dictates less ADC dynamic range requirement and further reduces power. The injection locking scheme reduces the phase noise contribution from the oscillators. The two-band prototype design realized in 65nm GP CMOS is centered at 9GHz, provides 4GHz instantaneous bandwidth, reduces beam-squinting by half, consumes 31.75mW/antenna and occupies 2.7mm2 of chip area. In the third work, a steerable RF/analog FFT based four-beam transmitter architecture is presented. This work is based on the idea of FFT based multiple beamforming in 1st work, but extended to the transmitter and make the all beams steerable. Due to the reciprocity between receiver and transmitter, decimation-in-frequency (DIF) FFT is utilized in the transmitter. All the beams are steered simultaneously by front-end phase shifters, while keep each of the beams is independent of the others. The steerability of FFT based multiple beamforming scheme makes this proposed prototype could tackle more complicated portable wireless environment. The first and second proposed architecture have been silicon veried, and the design of the third has been finished and ready for tapeout

Multispectral texture synthesis

Synthesizing texture involves the ordering of pixels in a 2D arrangement so as to display certain known spatial correlations, generally as described by a sample texture. In an abstract sense, these pixels could be gray-scale values, RGB color values, or entire spectral curves. The focus of this work is to develop a practical synthesis framework that maintains this abstract view while synthesizing texture with high spectral dimension, effectively achieving spectral invariance. The principle idea is to use a single monochrome texture synthesis step to capture the spatial information in a multispectral texture. The first step is to use a global color space transform to condense the spatial information in a sample texture into a principle luminance channel. Then, a monochrome texture synthesis step generates the corresponding principle band in the synthetic texture. This spatial information is then used to condition the generation of spectral information. A number of variants of this general approach are introduced. The first uses a multiresolution transform to decompose the spatial information in the principle band into an equivalent scale/space representation. This information is encapsulated into a set of low order statistical constraints that are used to iteratively coerce white noise into the desired texture. The residual spectral information is then generated using a non-parametric Markov Ran dom field model (MRF). The remaining variants use a non-parametric MRF to generate the spatial and spectral components simultaneously. In this ap proach, multispectral texture is grown from a seed region by sampling from the set of nearest neighbors in the sample texture as identified by a template matching procedure in the principle band. The effectiveness of both algorithms is demonstrated on a number of texture examples ranging from greyscale to RGB textures, as well as 16, 22, 32 and 63 band spectral images. In addition to the standard visual test that predominates the literature, effort is made to quantify the accuracy of the synthesis using informative and effective metrics. These include first and second order statistical comparisons as well as statistical divergence tests