Generation and control of locomotion patterns for biped robots by using central pattern generators

This paper presents an efficient closed-loop locomotion control system for biped robots that operates in the joint space. The robot’s joints are directly driven through control signals generated by a central pattern generator (CPG) network. A genetic algorithm is applied in order to find out an optimal combination of internal parameters of the CPG given a desired walking speed in straight line. Feedback signals generated by the robot’s inertial and force sensors are directly fed into the CPG in order to automatically adjust the locomotion pattern over uneven terrain and to deal with external perturbations in real time. Omnidirectional motion is achieved by controlling the pelvis motion. The performance of the proposed control system has been assessed through simulation experiments on a NAO humanoid robot

Analytical, experimental, and Monte Carlo system response matrix for pinhole SPECT reconstruction

PURPOSE: To assess the performance of two approaches to the system response matrix (SRM) calculation in pinhole single photon emission computed tomography (SPECT) reconstruction. METHODS: Evaluation was performed using experimental data from a low magnification pinhole SPECT system that consisted of a rotating flat detector with a monolithic scintillator crystal. The SRM was computed following two approaches, which were based on Monte Carlo simulations (MC-SRM) and analytical techniques in combination with an experimental characterization (AE-SRM). The spatial response of the system, obtained by using the two approaches, was compared with experimental data. The effect of the MC-SRM and AE-SRM approaches on the reconstructed image was assessed in terms of image contrast, signal-to-noise ratio, image quality, and spatial resolution. To this end, acquisitions were carried out using a hot cylinder phantom (consisting of five fillable rods with diameters of 5, 4, 3, 2, and 1 mm and a uniform cylindrical chamber) and a custom-made Derenzo phantom, with center-to-center distances between adjacent rods of 1.5, 2.0, and 3.0 mm. RESULTS: Good agreement was found for the spatial response of the system between measured data and results derived from MC-SRM and AE-SRM. Only minor differences for point sources at distances smaller than the radius of rotation and large incidence angles were found. Assessment of the effect on the reconstructed image showed a similar contrast for both approaches, with values higher than 0.9 for rod diameters greater than 1 mm and higher than 0.8 for rod diameter of 1 mm. The comparison in terms of image quality showed that all rods in the different sections of a custom-made Derenzo phantom could be distinguished. The spatial resolution (FWHM) was 0.7 mm at iteration 100 using both approaches. The SNR was lower for reconstructed images using MC-SRM than for those reconstructed using AE-SRM, indicating that AE-SRM deals better with the projection noise than MC-SRM. CONCLUSIONS: The authors' findings show that both approaches provide good solutions to the problem of calculating the SRM in pinhole SPECT reconstruction. The AE-SRM was faster to create and handle the projection noise better than MC-SRM. Nevertheless, the AE-SRM required a tedious experimental characterization of the intrinsic detector response. Creation of the MC-SRM required longer computation time and handled the projection noise worse than the AE-SRM.Nevertheless, the MC-SRM inherently incorporates extensive modeling of the system and therefore experimental characterization was not required

Impact of Region-of-Interest Delineation Methods, Reconstruction Algorithms, and Intra- and Inter-Operator Variability on Internal Dosimetry Estimates Using PET

Purpose: Human dosimetry studies play a central role in radioligand development for positron emission tomography (PET). Drawing regions of interest (ROIs) on the PET images is used to measure the dose in each organ. In the study aspects related to ROI delineation methods were evaluated for two radioligands of different biodistribution (intestinal vs urinary). Procedures: PET images were simulated from a human voxel-based phantom. Several ROI delineation methods were tested: antero-posterior projections (AP), 3D sub-samples of the organs (S), and a 3D volume covering the whole-organ (W). Inter- and intra-operator variability ROI drawing was evaluated by using human data. Results: The effective dose estimates using S and W methods were comparable to the true values. AP methods overestimated (49 %) the dose for the radioligand with intestinal biodistribution. Moreover, the AP method showed the highest inter-operator variability: 11 ± 1 %. Conclusions: The sub-sampled organ method showed the best balance between quantitative accuracy and inter- and intra-operator variability

Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

It is well-known that in pinhole SPECT (single-photon-emission computed tomography), iterative reconstruction methods including accurate estimations of the system response matrix can lead to submillimeter spatial resolution. There are two different methods for obtaining the system response matrix: those that model the system analytically using an approach including an experimental characterization of the detector response, and those that make use of Monte Carlo simulations. Methods based on analytical approaches are faster and handle the statistical noise better than those based on Monte Carlo simulations, but they require tedious experimental measurements of the detector response. One suggested approach for avoiding an experimental characterization, circumventing the problem of statistical noise introduced by Monte Carlo simulations, is to perform an analytical computation of the system response matrix combined with a Monte Carlo characterization of the detector response. Our findings showed that this approach can achieve high spatial resolution similar to that obtained when the system response matrix computation includes an experimental characterization. Furthermore, we have shown that using simulated detector responses has the advantage of yielding a precise estimate of the shift between the point of entry of the photon beam into the detector and the point of interaction inside the detector. Considering this, it was possible to slightly improve the spatial resolution in the edge of the field of view

SLSNet: Skin lesion segmentation using a lightweight generativeadversarial network

The determination of precise skin lesion boundaries in dermoscopic images using automated methods faces many challenges, most importantly, the presence of hair, inconspicuous lesion edges and low contrast in dermoscopic images, and variability in the color, texture and shapes of skin lesions. Existing deep learning-based skin lesion segmentation algorithms are expensive in terms of computational time and memory. Consequently, running such segmentation algorithms requires a powerful GPU and high bandwidth memory, which are not available in dermoscopy devices. Thus, this article aims to achieve precise skin lesion segmentation with minimum resources: a lightweight, efficient generative adversarial network (GAN) model called SLSNet, which combines 1-D kernel factorized networks, position and channel attention, and multiscale aggregation mechanisms with a GAN model. The 1-D kernel factorized network reduces the computational cost of 2D filtering. The position and channel attention modules enhance the discriminative ability between the lesion and non-lesion feature representations in spatial and channel dimensions, respectively. A multiscale block is also used to aggregate the coarse-to-fine features of input skin images and reduce the effect of the artifacts. SLSNet is evaluated on two publicly available datasets: ISBI 2017 and the ISIC 2018. Although SLSNet has only 2.35 million parameters, the experimental results demonstrate that it achieves segmentation results on a par with the state-of-the-art skin lesion segmentation methods with an accuracy of 97.61%, and Dice and Jaccard similarity coefficients of 90.63% and 81.98%, respectively. SLSNet can run at more than 110 frames per second (FPS) in a single GTX1080Ti GPU, which is faster than well-known deep learning-based image segmentation models, such as FCN. Therefore, SLSNet can be used for practical dermoscopic applications

Epileptogenic zone localization with (18)FDG PET using a new dynamic parametric analysis

Introduction: [18F]fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) is part of the regular preoperative work-up in medically refractory epilepsy. As a complement to visual evaluation of PET, statistical parametric maps can help in the detection of the epileptogenic zone (EZ). However, software packages currently available are time-consuming and little intuitive for physicians. We develop a user-friendly software (referred as PET-analysis) for EZ localization in PET studies that allows dynamic real-time statistical parametric analysis. To evaluate its performance, the outcome of PET-analysis was compared with the results obtained by visual assessment and Statistical Parametric Mapping (SPM). Methods: Thirty patients with medically refractory epilepsy who underwent presurgical 18F-FDG PET with good post-operative outcomes were included. The 18F-FDG PET studies were evaluated by visual assessment, with SPM8 and PET-analysis. In SPM, parametric T-maps were thresholded at corrected p < 0.05 and cluster size k = 50 and at uncorrected p < 0.001 and k = 100 (the most used parameters in the literature). Since PET-analysis rapidly processes different threshold combinations, T-maps were thresholded with multiple p-value and different clusters sizes. The presurgical EZ identified by visual assessment, SPM and PET-analysis was compared to the confirmed EZ according to post-surgical follow-up. Results: PET-analysis obtained 66.7% (20/30) of correctly localizing studies, comparable to the 70.0% (21/30) achieved by visual assessment and significantly higher (p < 0.05) than that obtained with the SPM threshold p < 0.001/k = 100, of 36.7% (11/30). Only one study was positive, albeit non-localizing, with the SPM threshold corrected p < 0.05/k = 50. Concordance was substantial for PET-analysis (κ = 0.643) and visual interpretation (κ = 0.622), being fair for SPM (κ = 0.242). Conclusion: Compared to SPM with the fixed standard parameters, PET-analysis may be superior in EZ localization with its easy and rapid processing of different threshold combinations. The results of this initial proof-of-concept study validate the clinical use of PET-analysis as a robust objective complementary tool to visual assessment for EZ localization

Ecología y desarrollo humano

Con motivo de la publicación de la Encíclica "Laudato si'. Sobre el cuidado de la casa común" del Papa Francisco, la Universidad de Navarra organizó el 18 de marzo de 2016 una jornada interdisciplinar titulada "Ecología y desarrollo humano. Conversaciones sobre Laudato si'". La jornada pretendía incitar tanto al estudio y la profundización intelectual como al compromiso práctico acerca de las propuestas formuladas en la Encíclica. Se recogen en esta publicación los textos de las intervenciones iniciales de los ponentes en cada una de las mesas redondas. Se incluye también el coloquio de la primera mesa redonda sobre "El cuidado de la creación, responsabilidad del cristiano", así como las conclusiones de la jornada, que proponen vías para el desarrollo del compromiso ambiental y social en nuestra Universidad

APOE-by-sex interactions on brain structure and metabolism in healthy elderly controls

BACKGROUND: The APOE effect on Alzheimer Disease (AD) risk is stronger in women than in men but its mechanisms have not been established. We assessed the APOE-by-sex interaction on core CSF biomarkers, brain metabolism and structure in healthy elderly control individuals (HC). METHODS: Cross-sectional study. HC from the Alzheimer's Disease Neuroimaging Initiative with available CSF (n = 274) and/or 3T-MRI (n = 168) and/or a FDG-PET analyses (n = 328) were selected. CSF amyloid-β1-42 (Aβ1-42), total-tau (t-tau) and phospho-tau (p-tau181p) levels were measured by Luminex assays. We analyzed the APOE-by-sex interaction on the CSF biomarkers in an analysis of covariance (ANCOVA). FDG uptake was analyzed by SPM8 and cortical thickness (CTh) was measured by FreeSurfer. FDG and CTh difference maps were derived from interaction and group analyses. RESULTS: APOE4 carriers had lower CSF Aβ1-42 and higher CSF p-tau181p values than non-carriers, but there was no APOE-by-sex interaction on CSF biomarkers. The APOE-by-sex interaction on brain metabolism and brain structure was significant. Sex stratification showed that female APOE4 carriers presented widespread brain hypometabolism and cortical thinning compared to female non-carriers whereas male APOE4 carriers showed only a small cluster of hypometabolism and regions of cortical thickening compared to male non-carriers. CONCLUSIONS: The impact of APOE4 on brain metabolism and structure is modified by sex. Female APOE4 carriers show greater hypometabolism and atrophy than male carriers. This APOE-by-sex interaction should be considered in clinical trials in preclinical AD where APOE4 status is a selection criterion