There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

CA : A Cancer Journal for Clinicians

Introduction to linear and nonlinear programming

Bilateral teleoperation: An historical survey

A position-based impedance controller has been implemented on a mini-excavator. Its performance and an approach to evaluate its stability robustness for given environment impedances are discussed. A dual hybrid teleoperation controller is proposed for machine control. Issues of transparency are discussed.

Evaluation of impedance and teleoperation control of a hydraulic mini-excavator

A needle-tissue interaction model is an essential part of every needle insertion simulator. In this paper, a new experimental method for the modeling of needle-tissue interaction is presented. The method consists of measuring needle and tissue displacements with ultrasound, measuring needle base forces, and using a deformation simulation model to identify the parameters of a needle-tissue interaction model. The feasibility of this non-invasive approach was demonstrated in an experiment in which a brachytherapy needle was inserted into a prostate phantom. Ultrasound radio-frequency data and the time-domain cross-correlation method, often used in ultrasound elastography, were used to generate the tissue displacement field during needle insertion. A three-parameter force density model was assumed for the needle-tissue interaction. With the needle displacement, tissue displacement and needle base forces as input data, finite element simulations were carried out to adjust the model parameters to achieve a good fit between simulated and measured data.

/pdf/modeling-of-needle-tissue-interaction-using-ultrasound-based-223538kl6k.pdf

Modeling of needle-tissue interaction using ultrasound-based motion estimation

The low diagnostic value of ultrasound in prostate cancer imaging has resulted in an effort to enhance the tumor contrast using ultrasound-based technologies that go beyond traditional B-mode imaging. Ultrasound RF time series, formed by echo samples originating from the same location over a few seconds of imaging, has been proposed and experimentally used for tissue typing with the goal of cancer detection. In this work, for the first time we report the preliminary results of in vivo clinical use of spectral parameters extracted from RF time series in prostate cancer detection. An image processing pipeline is designed to register the ultrasound data to wholemount histopathology references acquired from prostate specimens that are removed in radical prostatectomy after imaging. Support vector machine classification is used to detect cancer in 524 regions of interest of size 5×5 mm, each forming a feature vector of spectral RF time series parameters. Preliminary ROC curves acquired based on RF time series analysis for individual cases, with leave-one-patient-out cross validation, are presented and compared with B-mode texture analysis.

Ultrasound RF time series for tissue typing: First in vivo clinical results

The finite element method is commonly used to model tissue deformation in order to solve for unknown parameters in the inverse problem of viscoelasticity. Typically, a (regular-grid) structured mesh is used since the internal geometry of the domain to be identified is not known a priori. In this work, the generation of problem-specific meshes is studied and such meshes are shown to significantly improve inverse-problem elastic parameter reconstruction. Improved meshes are generated from axial strain images, which provide an approximation to the underlying structure, using an optimization-based mesh adaptation approach. Such strain-based adapted meshes fit the underlying geometry even at coarse mesh resolutions, therefore improving the effective resolution of the reconstruction at a given mesh size/complexity. Elasticity reconstructions are then performed iteratively using the reflective trust-region method for optimizing the fit between estimated and observed displacements. This approach is studied for Young's modulus reconstruction at various mesh resolutions through simulations, yielding 40%-72% decrease in root-mean-square reconstruction error and 4-52 times improvement in contrast-to-noise ratio in simulations of a numerical phantom with a circular inclusion. A noise study indicates that conventional structured meshes with no noise perform considerably worse than the proposed adapted meshes with noise levels up to 20% of the compression amplitude. A phantom study and preliminary in vivo results from a breast tumor case confirm the benefit of the proposed technique. Not only conventional axial strain images but also other elasticity approximations can be used to adapt meshes. This is demonstrated on images generated by combining axial strain and axial-shear strain, which enhances lateral image contrast in particular settings, consequently further improving mesh-adapted reconstructions.

Mesh Adaptation for Improving Elasticity Reconstruction Using the FEM Inverse Problem

Modeling the deflection of flexible needles is an essential part of needle insertion simulation and path planning In this paper, three models are compared in terms of accuracy in simulating the bending of a prostate brachytherapy needle The first two utilize the finite element method, one using geometric non-linearity and triangular plane elements, the other using non-linear beam elements The third model uses angular springs to model cantilever deflection The simulations are compared with the experimental bent needle configurations The models are assessed in terms of geometric conformity using independently identified and pre-identified model parameters The results show that the angular spring model, which is also the simplest, simulates the needle more accurately than the others

/pdf/a-comparison-of-needle-bending-models-3dyd3iqw1p.pdf

Septimiu E. Salcudean

Papers

Evaluation of impedance and teleoperation control of a hydraulic mini-excavator

Modeling of needle-tissue interaction using ultrasound-based motion estimation

Ultrasound RF time series for tissue typing: First in vivo clinical results

Mesh Adaptation for Improving Elasticity Reconstruction Using the FEM Inverse Problem

A comparison of needle bending models