FUZZY KERNEL REGRESSION FOR REGISTRATION AND OTHER IMAGE WARPING APPLICATIONS

In this dissertation a new approach for non-rigid medical im- age registration is presented. It relies onto a probabilistic framework based on the novel concept of Fuzzy Kernel Regression. The theoric framework, after a formal introduction is applied to develop several complete registration systems, two of them are interactive and one is fully automatic. They all use the composition of local deforma- tions to achieve the final alignment. Automatic one is based onto the maximization of mutual information to produce local affine aligments which are merged into the global transformation. Mutual Information maximization procedure uses gradient descent method. Due to the huge amount of data associated to medical images, a multi-resolution topology is embodied, reducing processing time. The distance based interpolation scheme injected facilitates the similairity measure op- timization by attenuating the presence of local maxima in the func- tional. System blocks are implemented on GPGPUs allowing efficient parallel computation of large 3d datasets using SIMT execution. Due to the flexibility of Mutual Information, it can be applied to multi- modality image scans (MRI, CT, PET, etc.). Both quantitative and qualitative experiments show promising results and great potential for future extension. Finally the framework flexibility is shown by means of its succesful application to the image retargeting issue, methods and results are presented

Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm.

The aims of this work were to evaluate the performance of several deformable image registration (DIR) algorithms implemented in our in-house software (NiftyReg) and the uncertainties inherent to using different algorithms for dose warping

PowerBit - Power aware arithmetic bit-width optimization

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Nonlinear time-warping made simple: a step-by-step tutorial on underwater acoustic modal separation with a single hydrophone

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bonnel, J., Thode, A., Wright, D., & Chapman, R. Nonlinear time-warping made simple: a step-by-step tutorial on underwater acoustic modal separation with a single hydrophone. The Journal of the Acoustical Society of America, 147(3), (2020): 1897, doi:10.1121/10.0000937.Classical ocean acoustic experiments involve the use of synchronized arrays of sensors. However, the need to cover large areas and/or the use of small robotic platforms has evoked interest in single-hydrophone processing methods for localizing a source or characterizing the propagation environment. One such processing method is “warping,” a non-linear, physics-based signal processing tool dedicated to decomposing multipath features of low-frequency transient signals (frequency f  1 km). Since its introduction to the underwater acoustics community in 2010, warping has been adopted in the ocean acoustics literature, mostly as a pre-processing method for single receiver geoacoustic inversion. Warping also has potential applications in other specialties, including bioacoustics; however, the technique can be daunting to many potential users unfamiliar with its intricacies. Consequently, this tutorial article covers basic warping theory, presents simulation examples, and provides practical experimental strategies. Accompanying supplementary material provides matlab code and simulated and experimental datasets for easy implementation of warping on both impulsive and frequency-modulated signals from both biotic and man-made sources. This combined material should provide interested readers with user-friendly resources for implementing warping methods into their own research.This work was supported by the Office of Naval Research (Task Force Ocean, project N00014-19-1-2627) and by the North Pacific Research Board (project 1810). Original warping developments were supported by the French Delegation Generale de l'Armement

COMPUTER-GENERATED CARS YOU HAVE TO LOVE: HOW IMAGE MORPHING AND WARPING HELP DESIGNERS TO OPTIMIZE THEIR DESIGN SKETCHES

Although product design is considered as a core determinant of a product\u27s market success, systematic approaches that allow managers to increase a product\u27s visual attractiveness are not available. The present research addresses this gap by adapting an approach that was originally developed in research on human facial attractiveness to a product design context. In particular, we propose that image morphing and warping techniques can be used to identify and manipulate those design features that drive a product\u27s perceived attractiveness. Moreover, we also develop a computer-assisted interface that allows consumers to individually determine their optimal car design. Three studies with real consumers focusing on the automotive market confirm the viability and the usefulness of our approach. From a managerial perspective, the approach may increase the effectiveness of design efforts and may help in integrating consumers\u27 preferences in an early stage of the product design process

Accuracy-guaranteed bit-width optimization

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Classification of functional brain data for multimedia retrieval

This study introduces new signal processing methods for extracting meaningful information from brain signals (functional magnetic resonance imaging and single unit recording) and proposes a content-based retrieval system for functional brain data. First, a new method that combines maximal overlapped discrete wavelet transforms (MODWT) and dynamic time warping (DTW) is presented as a solution for dynamically detecting the hemodynamic response from fMRI data. Second, a new method for neuron spike sorting is presented that uses the maximal overlap discrete wavelet transform and rotated principal component analysis. Third, a procedure to characterize firing patterns of neuron spikes from the human brain, in both the temporal domain and the frequency domain, is presented. The combination of multitaper spectral estimation and a polynomial curve-fitting method is employed to transform the firing patterns to the frequency domain. To generate temporal shapes, eight local maxima are smoothly connected by a cubic spline interpolation. A rotated principal component analysis is used to extract common firing patterns as templates from a training set of 4100 neuron spike signals. Dynamic time warping is then used to assign each neuron firing to the closest template without shift error. These techniques are utilized in the development of a content-based retrieval system for human brain data

A 3D computer assisted Orthopedic Surgery Planning approach based on planar radiography

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)The main goal of this work consisted in develop a system to perform the 3D reconstruction of bone models from radiographic images. This system can be then integrated with a commercial software that performs pre-operative planning of orthopedic surgeries. The benefit of performing this 3D reconstruction from planar radiography is that this modality has some advantages over other modalities that perform this reconstruction directly, like CT and MRI. To develop the system it was used radiographic images of the femur obtained from medical image databases online. It was also used a generic model of the femur available in the online repository BEL. This generic model completes the information missing in the radiographic images. It was developed two methods to perform the 3D reconstruction through the deformation of the generic model, one uses triangulation of extracted edge points and the other don't. The first method was not successful, the final model had very low thickness, possibly because the triangulation process was not performed correctly. With the second method it was obtained a 3D bone model of the femur aligned with the radiographic images of the patient and with the same size as the patient's bone. However, the obtained model still needs some adjustment to coincide fully with reality. To perform this is necessary to enhance the deformation step of the model so that it will have the same shape as the patient's bone. The second method is more advantageous because it doesn't need the parameters of the x-ray imaging system. However, it's necessary to enhance the step deformation of this method so that the final model matches patient's anatomy.O principal objetivo deste trabalho consistiu em desenvolver um sistema capaz de realizar a reconstrução 3D de modelos ósseos a partir de imagens radiográficas. Este sistema pode posteriormente ser integrado num produto comercial que realiza o planeamento pré-operativo de cirurgias ortopédicas. O benefício de realizar esta reconstrução 3D a partir de radiografias está relacionado com o facto desta modalidade ter vantagens em relação às outras modalidades que fazem esta reconstrução diretamente, como as modalidades CT e MRI. Para desenvolver este sistema foram usadas imagens radiográficas do fémur obtidas através de bases de dados online de imagens médicas. Também foi usado um modelo genérico do fémur disponível no repositório online BEL. Este modelo genérico completa a informação que está em falta nas imagens radiográficas. Foram desenvolvidos dois métodos, que realizam a reconstrução 3D através da deformação do modelo genérico sendo que num é feita a triangulação de pontos dos contornos e noutro não. O primeiro método não foi bem sucedido, visto que o modelo final tinha uma espessura muito pequena, possivelmente devido ao facto do processo de triangulação não ter sido executado corretamente. Com o segundo método foi obtido um modelo 3D do fémur alinhado com as imagens radiográficas do paciente e com o mesmo tamanho do osso do paciente. No entanto, o modelo obtido carece ainda de alguma afinação de modo a coincidir na íntegra com a realidade. Para fazer isto é necessário melhorar o passo de deformação do modelo, para que este fique com a mesma forma do osso do paciente. O segundo método é mais vantajoso porque não necessita dos parâmetros dos sistema de raios- X. No entanto, é necessário melhorar o passo de deformação deste método para que o modelo final coincida com a anatomia do paciente