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

We present an ultrasound vibro-elastography system designed to acquire viscoelastic properties of the prostate and peri-prostatic tissue. An excitation stage imparts low-frequency (<20 Hz), limited amplitude (<± 2mm), broadband vibratory motion to an endorectal transducer, along a radial/transversal direction. The induced tissue motion is estimated from ultrasound radio-frequency data and is used to estimate the mechanical frequency response of tissue to the excitation at different spatial locations. This can be used to determine the spatial distribution of various mechanical parameters of tissue, such as stiffness and viscosity. Phantom and in-vivo images are presented. The results obtained demonstrate high phantom and tissue linearity and high signal-to-noise ratio.

/pdf/viscoelasticity-modeling-of-the-prostate-region-using-vibro-3vte2z7wdr.pdf

Viscoelasticity modeling of the prostate region using vibro-elastography

Good robot performance often relies upon the selection of design parameters that lead to a well conditioned Jacobian or impedance "design" matrix. In this paper a new design matrix normalization technique is presented to cope with the problem of nonhomogeneous physical units. The technique pre and post-multiplies a design matrix by diagonal scaling matrices corresponding to the range of joint and task space variables. In the case of the Jacobian, normalization leads to a practical interpretation of a robot's "characteristic length" as the desired ratio between maximum linear and angular force or velocity. The scale factors can also be used to set relative required strength or speed along any axes of end-point motion and/or can be treated as free design parameters to improve isotropy through asymmetric actuation. The effect of scaling on actual designs is illustrated by a number of design examples using a global search method previously developed by the authors.

/pdf/matrix-normalization-for-optimal-robot-design-412sp6p76h.pdf

Matrix normalization for optimal robot design

Describes the haptic rendering of a virtual environment by drawing upon concepts developed in the area of teleoperation. A four-channel teleoperation architecture is shown to be an effective means of coordinating the control of a 3-DOF haptic interface with the simulation of a virtual dynamic environment.

/pdf/haptic-interface-control-design-issues-and-experiments-with-17yuigl0ny.pdf

Haptic interface control-design issues and experiments with a planar device

Purpose:

To develop an image-based technique capable of detection and grading of prostate cancer, which combines features extracted from multiparametric MRI into a single parameter map of cancer probability.



Materials and Methods:

A combination of features extracted from diffusion tensor MRI and dynamic contrast enhanced MRI was used to characterize biopsy samples from 29 patients. Support vector machines were used to separate the cancerous samples from normal biopsy samples and to compute a measure of cancer probability, presented in the form of a cancer colormap. The classification results were compared with the biopsy results and the classifier was tuned to provide the largest area under the receiver operating characteristic (ROC) curve. Based solely on the tuning of the classifier on the biopsy data, cancer colormaps were also created for whole-mount histopathology slices from four radical prostatectomy patients.



Results:

An area under ROC curve of 0.96 was obtained on the biopsy dataset and was validated by a “leave-one-patient-out” procedure. The proposed measure of cancer probability shows a positive correlation with Gleason score. The cancer colormaps created for the histopathology patients do display the dominant tumors. The colormap accuracy increases with measured tumor area and Gleason score.



Conclusion:

Dynamic contrast enhanced imaging and diffusion tensor imaging, when used within the framework of supervised classification, can play a role in characterizing prostate cancer. J. Magn. Reson. Imaging 2012;35:1403–1413. © 2012 Wiley Periodicals, Inc.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.23540

Multiparametric MRI maps for detection and grading of dominant prostate tumors

An iterative solution to the inverse problem of elasticity and viscosity is proposed in this paper. A new dynamic finite element model that is consistent with known rheological models has been derived to account for the viscoelastic changes in soft tissue. The model assumes known lumped masses at the nodes, and comprises two vectors of elasticity and viscosity parameters that depend on the material elasticity and viscosity distribution, respectively. Using this deformation model and the observed dynamic data for harmonic excitation, the inverse problem is solved to reconstruct the viscosity and elasticity in the medium by using a Gauss-Newton-based approach. As in other inverse problems, previous knowledge of the parameters on the boundaries of the medium is necessary to assure uniqueness and convergence and to obtain an accurate map of the viscoelastic properties. The sensitivity of the solutions to noise, model and boundary conditions has been studied through numerical simulations. Experimental results are also presented. The viscosity and elasticity of a gelatin-based phantom with inclusion of known properties have been reconstructed and have been shown to be close to the values obtained using standard rheometry.

https://iopscience.iop.org/article/10.1088/0031-9155/53/22/018/pdf

Septimiu E. Salcudean

Papers

Viscoelasticity modeling of the prostate region using vibro-elastography

Matrix normalization for optimal robot design

Haptic interface control-design issues and experiments with a planar device

Multiparametric MRI maps for detection and grading of dominant prostate tumors

Viscoelastic characterization of soft tissue from dynamic finite element models