System-Level Analysis of Closed-Loop Anesthesia Control Under Temporal Sensor Faults via UPPAAL-SMC.

Hypnosis control is an essential process commonly used during medical surgeries and operations. In clinical practice, this process is achieved by an anesthesiologist who estimates the required dose for a patient and monitors the hypnotic status of the patient. For closed-loop sedation control systems to be approved for clinical practice, they have to demonstrate efficiency and robustness under parameter uncertainties and potential device faults.

Computer-Aided Diagnosis System of Alzheimer's Disease Based on Multimodal Fusion: Tissue Quantification Based on the Hybrid Fuzzy-Genetic-Possibilistic Model and Discriminative Classification Based on the SVDD Model.

An improved computer-aided diagnosis (CAD) system is proposed for the early diagnosis of Alzheimer's disease (AD) based on the fusion of anatomical (magnetic resonance imaging (MRI)) and functional (F-fluorodeoxyglucose positron emission tomography (FDG-PET)) multimodal images, and which helps to address the strong ambiguity or the uncertainty produced in brain images. The merit of this fusion is that it provides anatomical information for the accurate detection of pathological areas characterized in functional imaging by physiological abnormalities. First, quantification of brain tissue volumes is proposed based on a fusion scheme in three successive steps: modeling, fusion and decision.

A hybrid camera- and ultrasound-based approach for needle localization and tracking using a 3D motorized curvilinear ultrasound probe.

Three-dimensional (3D) motorized curvilinear ultrasound probes provide an effective, low-cost tool to guide needle interventions, but localizing and tracking the needle in 3D ultrasound volumes is often challenging. In this study, a new method is introduced to localize and track the needle using 3D motorized curvilinear ultrasound probes. In particular, a low-cost camera mounted on the probe is employed to estimate the needle axis.