Augmented active surface model for the recovery of small structures in CT.

This paper devises an augmented active surface model for the recovery of small structures in a low resolution and high noise setting, where the role of regularization is especially important. The emphasis here is on evaluating performance using real clinical computed tomography (CT) data with comparisons made to an objective ground truth acquired using micro-CT. In this paper, we show that the application of conventional active contour methods to small objects leads to non-optimal results because of the inherent properties of the energy terms and their interactions with one another. We show that the blind use of a gradient magnitude based energy performs poorly at these object scales and that the point spread function (PSF) is a critical factor that needs to be accounted for. We propose a new model that augments the external energy with prior knowledge by incorporating the PSF and the assumption of reasonably constant underlying CT numbers.

PET protection optimization for streaming scalable videos with multiple transmissions.

This paper investigates priority encoding transmission (PET) protection for streaming scalably compressed video streams over erasure channels, for the scenarios where a small number of retransmissions are allowed. In principle, the optimal protection depends not only on the importance of each stream element, but also on the expected channel behavior. By formulating a collection of hypotheses concerning its own behavior in future transmissions, limited-retransmission PET (LR-PET) effectively constructs channel codes spanning multiple transmission slots and thus offers better protection efficiency than the original PET. As the number of transmission opportunities increases, the optimization for LR-PET becomes very challenging because the number of hypothetical retransmission paths increases exponentially. As a key contribution, this paper develops a method to derive the effective recovery-probability versus redundancy-rate characteristic for the LR-PET procedure with any number of transmission opportunities. This significantly accelerates the protection assignment procedure in the original LR-PET with only two transmissions, and also makes a quick and optimal protection assignment feasible for scenarios where more transmissions are possible. This paper also gives a concrete proof to the redundancy embedding property of the channel codes formed by LR-PET, which allows for a decoupled optimization for sequentially dependent source elements with convex utility-length characteristic. This essentially justifies the source-independent construction of the protection convex hull for LR-PET.

A mathematical model of human semicircular canal geometry: a new basis for interpreting vestibular physiology.

We report a precise, simple, and accessible method of mathematically measuring and modeling the three-dimensional (3D) geometry of semicircular canals (SCCs) in living humans. Knowledge of this geometry helps understand the development and physiology of SCC stimulation. We developed a framework of robust techniques that automatically and accurately reconstruct SCC geometry from computed tomography (CT) images and are directly validated using micro-CT as ground truth. This framework measures the 3D centroid paths of the bony SCCs allowing direct comparison and analysis between ears within and between subjects. An average set of SCC morphology is calculated from 34 human ears, within which other geometrical attributes such as nonplanarity, radius of curvature, and inter-SCC angle are examined, with a focus on physiological implications. These measurements have also been used to critically evaluate plane fitting techniques that reconcile many of the discrepancies in current SCC plane studies. Finally, we mathematically model SCC geometry using Fourier series equations. This work has the potential to reinterpret physiology and pathophysiology in terms of real individual 3D morphology.

Psychophysics of prosthetic vision: III. stochastic rendering, the phosphene image, and perception.

For pt.I see ibid., p.Z004024-7. For pt.II see ibid., p.Z004558-61. This paper examines the rendering of luminous spots ("phosphenes") in the visual field, and their stochastic positioning as a means of anti-aliasing the resulting spotty image ("phosphene image"). We derive an equation concerning the correlations of pairs of phosphenes comprising the phosphene image, and show the relationship to the statistics governing the stochastic positioning. We present some examples where stochastic rendering assists the veridical perception of textures, and argue for its superiority as cf. ordered rendering. Our preliminary results suggest that it may be perceptually effective to manufacture disordered arrays of stimulating electrodes for intraocular implantation.

Simulated prosthetic visual fixation, saccade, and smooth pursuit.

A visual tracking task was administered to 20 subjects afforded simulated prosthetic vision (a phosphene array); a total of 3h data was taken from each subject over the course of 10 visits. The experiment assessed prosthetic visual fixation, saccade and smooth pursuit and the effect of practice. Further, we demonstrated an image analysis technique that assisted fixation and pursuit (but not saccade) accuracy, and required less vigorous movement of the phosphene array in pursuing the target. As measured by mean deviation from the target, fixation and pursuit accuracies were improved by 8.3 and 3.3 min of visual arc, respectively (35.8% and 6.8%), for inter-phosphene spacing of 1.9 degrees . The analysis technique, involving overlapping Gaussian kernels, was an heuristic design; this is the first step of an iterative, experimental approach to devising effective image analysis to be contained in an electronic vision prosthesis. The approach should ultimately afford implanted patients improved prosthetic visual function.