Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Human eyeball model reconstruction and quantitative analysis.
Determining shape of the eyeball is important to diagnose eyeball disease like myopia. In this paper, we present an automatic approach to precisely reconstruct three dimensional geometric shape of eyeball from MR Images. The model development pipeline involved image segmentation, registration, B-Spline surface fitting and subdivision surface fitting, neither of which required manual interaction. ⋯ In addition to the eight metrics commonly used by existing studies, we proposed two novel metrics, Gaussian Curvature Analysis and Sphere Distance Deviation, to quantify the cornea shape and the whole eyeball surface respectively. The experiment results showed that the reconstructed eyeball models accurately represent the complex morphology of the eye. The ten metrics parameterize the eyeball among different subjects, which can potentially be used for eye disease diagnosis.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Rapid and low-invasive functional brain mapping by realtime visualization of high gamma activity for awake craniotomy.
For neurosurgery with an awake craniotomy, the critical issue is to set aside enough time to identify eloquent cortices by electrocortical stimulation (ECS). High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram (ECoG) is assumed to reflect localized cortical processing. In this report, we used realtime HGA mapping and functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. ⋯ Specificities of the motor and language-fMRI, however, did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate functional mapping.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2014
An adaptive brain-machine interface algorithm for control of burst suppression in medical coma.
Burst suppression is an electroencephalogram (EEG) indicator of profound brain inactivation in which bursts of electrical activity alternate with periods of isoelectricity termed suppression. Specified time-varying levels of burst suppression are targeted in medical coma, a drug-induced brain state used for example to treat uncontrollable seizures. A brain-machine interface (BMI) that observes the EEG could automate the control of drug infusion rate to track a desired target burst suppression trajectory. ⋯ We design an adaptive recursive Bayesian estimator to jointly estimate drug concentrations and system parameters in real time. We construct a controller using the linear-quadratic-regulator strategy that explicitly penalizes large infusion rate variations at steady state and uses the estimates as feedback to generate robust control. Using simulations, we show that the adaptive algorithm achieves precise control of time-varying target levels of burst suppression even when model parameters are initialized randomly, and reduces the infusion rate variation at steady state.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Multicategory classification of 11 neuromuscular diseases based on microarray data using support vector machine.
We applied multicategory machine learning methods to classify 11 neuromuscular disease groups and one control group based on microarray data. To develop multicategory classification models with optimal parameters and features, we performed a systematic evaluation of three machine learning algorithms and four feature selection methods using three-fold cross validation and a grid search. This study included 114 subjects of 11 neuromuscular diseases and 31 subjects of a control group using microarray data with 22,283 probe sets from the National Center for Biotechnology Information (NCBI). ⋯ In addition, a gene symbol, SPP1 was selected as the top-ranked gene by the BW method. We confirmed relationships between the gene (SPP1) and Duchenne muscular dystrophy (DMD) from a previous study. With our models as clinically helpful tools, neuromuscular diseases could be classified quickly using a computer, thereby giving a time-saving, cost-effective, and accurate diagnosis.
-
Conf Proc IEEE Eng Med Biol Soc · Jan 2014
Towards a miniaturized brain-machine-spinal cord interface (BMSI) for restoration of function after spinal cord injury.
Nearly 6 million people in the United States are currently living with paralysis in which 23% of the cases are related to spinal cord injury (SCI). Miniaturized closed-loop neural interfaces have the potential for restoring function and mobility lost to debilitating neural injuries such as SCI by leveraging recent advancements in bioelectronics and a better understanding of the processes that underlie functional and anatomical reorganization in an injured nervous system. ⋯ The paper further presents results from a neurobiological study conducted in both normal and SCI rats to investigate the effect of various ISMS parameters on movement thresholds in the rat hindlimb. Coupled with proper signal-processing algorithms in the future for the transformation between the cortically recorded data and ISMS parameters, such a BMSI has the potential to facilitate functional recovery after an SCI by re-establishing corticospinal communication channels lost due to the injury.