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

Since 1999, both traditional and project based learning (PBL) programs have been offered to second year ECE students at the University of British Columbia. This paper describes the structure of the PBL program and a student evaluation of their competencies. The evaluation was carried out by a survey of third and fourth year students who passed through either the PBL or the traditional program. Results of the evaluation indicate that the former PBL students felt significantly more improved than the traditional students in their design-related abilities and some of their teamwork abilities evaluated by the survey.

https://ojs.library.queensu.ca/index.php/PCEEA/article/download/3817/3884

Comparing student assessed competencies in pbl and traditional ece programs

A new method to model the stress–strain relationship in two dimensions is proposed, which is particularly suited for analyzing nearly incompressible materials, such as soft tissue. In most cases of soft tissue modeling, plane strain is reported to approximate the deformation when an external compression is applied. However, it is subject to limitations when dealing with incompressible materials, e.g., when solving the inverse problem of elasticity. We propose a novel 2D model for the linear stress–strain relationship by describing the out-of-plane strain as a linear combination of the two in-plane strains. As such, the model can be represented in 2D while being able to explain the three-dimensional deformation. We show that in simple cases where the applied force is dominantly in one direction, one can approximate the sum of the three principal strain components in a plane by a scalar multiplied by the out-of-plane strain. 3D finite-element simulations have been performed. The proposed model has been tested under different boundary conditions and material properties. The results show that the model parametrization is affected mostly by the boundary conditions, while being relatively independent of the underlying distribution of Young's modulus. An application to the inverse problem of elasticity is presented where a more accurate estimate is obtained using the proposed dilatation model compared to the plane-stress and plane-strain models.

/pdf/dilatation-parameterization-for-two-dimensional-modeling-of-jueu85i8b4.pdf

Dilatation parameterization for two-dimensional modeling of nearly incompressible isotropic materials

In this work we propose to segment the prostate on a challenging dataset of trans-rectal ultrasound (TRUS) images using convolutional neural networks (CNNs) and statistical shape models (SSMs). TRUS is commonly used for a number of image-guided interventions on the prostate. Fast and accurate segmentation on the organ in these images is crucial to planning and fusion with other modalities such as magnetic resonance images (MRIs) . However, TRUS has limited soft tissue contrast and signal to noise ratio which makes the task of segmenting the prostate challenging and subject to inter-observer and intra-observer variability. This is especially problematic at the base and apex where the gland boundary is hard to define. In this paper, we aim to tackle this problem by taking advantage of shape priors learnt on an MR dataset which has higher soft tissue contrast allowing the prostate to be contoured more accurately. We use this shape prior in combination with a prostate tissue probability map computed by a CNN for segmentation.

Automatic Segmentation of the Prostate on 3D Trans-rectal Ultrasound Images using Statistical Shape Models and Convolutional Neural Networks.

This paper addresses the problem of tuning closed-loop controllers using online measurements. Numerical optimization of a controller in "internal model" form is performed by minimizing the performance functionals derived from specifications. By using measurements, not models, to evaluate performance functionals and their descent directions, computational savings and better actual performance are achieved. An example is used to demonstrate the tuning procedure and its usefulness. >

On-line controller tuning using the Q-parameterization

Advances in human-computer interaction (HCI) technologies have granted sonographers and radiologists a much improved user experience when operating different ultrasound (US) machines. Continued HCI improvements in US would benefit from a systematic study of the HCI control logic used in this domain. Such a study has not been presented previously and is the subject of this paper. We surveyed sonographers to determine the most frequently used controls in US machines. We standardized the representation of the US machine HCI control logic by using the unified modelling language (UML). We used UML diagrams to analyze the HCI control logic of 10 different cart-based US machines from several major manufacturers, and we discovered that the control logic for the most frequently used functions are identical. While this control logic does not follow an established standard, it has been commonly adopted. Using the UML for the visualization and formulation of control logic, we can target logically optimal interactions (whose operation steps cannot be further reduced), e.g., adjustment of B-mode gain, frequency and depth, and can derive methods to simplify logically sub-optimal interactions, e.g., the pointing and selecting operation, as well as image measurements.Our study provides insights into existing HCI approaches used in US machines and establishes a rigorous UML-based framework for future US machine design to improve interoperability, efficiency and ease-of-use.

Septimiu E. Salcudean

Papers

Comparing student assessed competencies in pbl and traditional ece programs

Dilatation parameterization for two-dimensional modeling of nearly incompressible isotropic materials

Automatic Segmentation of the Prostate on 3D Trans-rectal Ultrasound Images using Statistical Shape Models and Convolutional Neural Networks.

On-line controller tuning using the Q-parameterization

A Unified Representation of Control Logic in Human-Ultrasound Machine Interaction