Browsing by Subject "Virtual Reality"

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    ItemOpen Access
    A New Concept In The Evaluation Of Cybernetic Actuators Control Using Virtual Reality
    (1995) Zahedi, Edmond; Miyake, Hitoshi
    In order to control the movement of a cybernetic actuator the EMG signal is generally used as a source of command. This signal has to be processed in order to extract relevant features, which are then classified. Many schemes exist today in both feature extraction and classification, each one claiming to reduce the error rate and there has been some approaches in order to assess the input-output characteristics of prostheses. This paper vvill introduce a new concept in developing a unique platform using virtual reality (VR) tools for evaluating both the different schemes of EMG signal processing and cybernetic control. The design follows a modular approach allowing for the change of each module (analog signal conditiorming, data acquisition, signal processing, actuator control, VR aspects) accordingly to the specific needs of an application. The foreseen applications of this work are performance evaluation of EMG signal processing algorithms for prosthesis control in real conditions, performance evaluation of the motor control schemes by executing real tasks, selection of the optimum scheme for a particular application (spatial, medical surgery, underwater, etc...) and training of amputees or future users of the system in real conditions where "real conditions" means the VR simulated environment.
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    ItemOpen Access
    Utility of virtual monoenergetic images derived from a dual-layer detector-based spectral CT in the assessment of aortic anatomy and pathology: A retrospective case control study.
    (Clinical imaging, 2018-11) Chalian, Hamid; Kalisz, Kevin; Rassouli, Negin; Dhanantwari, Amar; Rajiah, Prabhakar
    OBJECTIVES:To evaluate the ability of the retrospectively generated virtual monoenergetic images (VMIs) from a dual-layer detector-based spectral computed tomography (SDCT) to augment aortic enhancement for the evaluation of aortic anatomy and pathology. METHODS:98 patients with suboptimal aortic enhancement (≤200 HU) were retrospectively identified from SDCT scans. VMI from 40 to 80 keV were generated. Attenuation, noise, SNR, and CNR were measured at seven levels in the aorta. Image quality was graded on a 5-point scale, 5 being the best. From the VMI, an ideal set was chosen with mean vascular attenuation above 200 HU while maintaining diagnostic quality. Image parameters and quality of this ideal-set were compared to the standard 120-kVp images. RESULTS:The mean attenuation of all seven measured anatomical regions was 156.6 ± 61.7 HU in the 120-kVp images. Attenuation of the VMI from 40 to 70 keV were higher than the 120-kVp image, measuring 439.2 ± 215.3 HU, 298.5 ± 140.6 HU, 213.4 ± 94.3 HU, and 164.7 ± 90.2 HU, for 40 keV, 50 keV, 60 keV, and 70 keV, respectively (p value <0.01 for 40, 50, 60 keV; 0.07 for 70 keV). SNR and CNR showed similar trends. The 50 keV VMI had the best image quality (4.48 ± 0.84 vs. 2.24 ± 0.92 on 120-kVp images, p < 0.001). Attenuation, CNR, and SNR increased by 90.6%, 85.0%, and 108.1% at 50 keV compared to 120-kVp. CONCLUSIONS:A contrast-enhanced CT study can be optimized for the assessment of the aorta by using low-energy VMI obtained using SDCT. At the optimal monoenergetic level, attenuation, SNR, CNR and image quality were significantly higher than that of conventional polyenergetic images.