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

Despite the fact that the velocity threshold method is widely applied, the detection of microsaccades continues to be a challenging problem, due to gaze-tracking inaccuracy and the transient nature of microsaccades. Important parameters associated with a saccadic event, e.g., saccade duration, amplitude, and maximum velocity, are sometimes imprecisely estimated, which may lead to biases in inferring the roles of microsaccades in perception and cognition. To overcome the biases and have a better detection algorithm for microsaccades, we propose a novel statistical model for the tracked gaze positions during eye fixations. In this model, we incorporate a parametrization that has been previously applied to model saccades, which allows us to veridically capture the velocity profile of saccadic eye movements. Based on our model, we derive the Neyman Pearson Detector (NPD) for saccadic events. Implemented in conjunction with the maximum likelihood estimation method, our NPD can detect a saccadic event and estimate all parameters simultaneously. Because of its adaptive nature and its statistical optimality, our NPD method was able to better detect microsaccades in some datasets when compared with a recently proposed state-of-the-art method based on convolutional neural networks. NPD also yielded comparable performance with a recently developed Bayesian algorithm, with the added benefit of modeling a more biologically veridical velocity profile of the saccade. As opposed to these algorithms, NPD can lend itself better to online saccade detection, and thus has potential for human-computer interaction applications. Our algorithm is publicly available at https://github.com/hz-zhu/NPD-micro-saccade-detection.

The Neyman Pearson detection of microsaccades with maximum likelihood estimation of parameters.

Jointly Boosting Saliency Prediction and Disease Classification on Chest X-ray Images with Multi-task UNet

Novel stable adaptive nonlinear controllers are proposed for position tracking control of hydraulic manipulators The controllers were developed by using the backstepping approach and are based on realistic models that include rigid body dynamics, friction, and hydraulic actuator dynamics with valve orifice and spool displacement nonlinearities Using Lyapunov analysis, it is shown that tracking errors are bounded and converge to zero in the absence of Coulomb friction and are bounded when Coulomb friction is present The proposed techniques were used to control a hydraulic Stewart platform Their effectiveness were confirmed by simulations and experiments

A New Approach to the Control of a Hydraulic Stewart Platform

Magnetic resonance elastography (MRE), which quantitatively measures shear modulus over a volume, provides an accurate imaging-based fibrosis staging comparable to biopsy. While ultrasound-based elastography methods for liver fibrosis staging have been developed, they are confined to a 1D or a 2D region of interest and to a limited depth. We present a novel matrix array implementation of the 3D Shear Wave Absolute Vibro-Elastography (S-WAVE)and validate its performance. We use an EPIQ 7G ultrasound machine with an X6-1 xMATRIX transducer (Philips Healthcare, Bothell, WA)to sample tissue motion and reconstruct the elasticity map in 3D. The system was validated for a liver tissue phantom against measurements obtained with transient elastography (FibroScan, Echosens), ultrasound point quantification shear wave elastography (ElastPQ, Philips), 2D shear wave imaging (ElastQ, Philips)and MRE. With ethics approval, five healthy volunteers were imaged with MRE and S-WAVE, and the results indicate that S-WAVE with xMATRIX produces comparable results with MRE.

3D Liver Shear Wave Absolute Vibro-Elastography with an xMATRIX Array - A Healthy Volunteer Study

One of the commonly used treatment methods for early-stage prostate cancer is brachytherapy. The standard of care for planning this procedure is segmentation of contours from transrectal ultrasound (TRUS) images, which closely follow the prostate boundary. This process is currently performed either manually or using semi-automatic techniques. This paper introduces a fully automatic segmentation algorithm which uses a priori knowledge of contours in a reference data set of TRUS volumes. A non-parametric deformable registration method is employed to transform the atlas prostate contours to a target image coordinates. All atlas images are sorted based on their registration results and the highest ranked registration results are selected for decision fusion. A Simultaneous Truth and Performance Level Estimation algorithm is utilized to fuse labels from registered atlases and produce a segmented target volume. In this experiment, 50 patient TRUS volumes are obtained and a leave-one-out study on TRUS volumes is reported. We also compare our results with a state-of-the-art semi-automatic prostate segmentation method that has been clinically used for planning prostate brachytherapy procedures and we show comparable accuracy and precision within clinically acceptable runtime.

Septimiu E. Salcudean

Papers

The Neyman Pearson detection of microsaccades with maximum likelihood estimation of parameters.

Jointly Boosting Saliency Prediction and Disease Classification on Chest X-ray Images with Multi-task UNet

A New Approach to the Control of a Hydraulic Stewart Platform

3D Liver Shear Wave Absolute Vibro-Elastography with an xMATRIX Array - A Healthy Volunteer Study

Multi-atlas-based automatic 3D segmentation for prostate brachytherapy in transrectal ultrasound images