Hemm-Ode, Simone
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Hemm-Ode
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Simone
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Hemm-Ode, Simone
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- PublikationProbabilistic maps for deep brain stimulation – Impact of methodological differences(Elsevier, 2022) Nordin, Teresa; Vogel, Dorian; Osterlund, Erik; Johansson, Johannes; Fytagoridis, Anders; Blomstedt, Patric; Hemm-Ode, Simone; Wardell, Karin [in: Brain Stimulation]Background Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations. Objective To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters. Methods Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function. Results Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters. Conclusion The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationLamb waves and adaptive beamforming for aberration correction in medical ultrasound imaging(IEEE, 06.07.2020) Mozaffarzadeh, Moein; Minonzio, Claudio; de Jong, Nico; Verweij, Martin; Hemm-Ode, Simone; Daeichin, Verya [in: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control]Phase aberration in transcranial ultrasound imaging (TUI) caused by the human skull leads to an inaccurate image reconstruction. In this article, we present a novel method for estimating the speed of sound and an adaptive beamforming technique for phase aberration correction in a flat polyvinylchloride (PVC) slab as a model for the human skull. First, the speed of sound of the PVC slab is found by extracting the overlapping quasi-longitudinal wave velocities of symmetrical Lamb waves in the frequency-wavenumber domain. Then, the thickness of the plate is determined by the echoes from its front and back side. Next, an adaptive beamforming method is developed, utilizing the measured sound speed map of the imaging medium. Finally, to minimize reverberation artifacts caused by strong scatterers (i.e., needles), a dual probe setup is proposed. In this setup, we image the medium from two opposite directions, and the final image can be the minimum intensity projection of the inherently co-registered images of the opposed probes. Our results confirm that the Lamb wave method estimates the longitudinal speed of the slab with an error of 3.5% and is independent of its shear wave speed. Benefiting from the acquired sound speed map, our adaptive beamformer reduces (in real time) a mislocation error of 3.1, caused by an 8 mm slab, to 0.1 mm. Finally, the dual probe configuration shows 7 dB improvement in removing reverberation artifacts of the needle, at the cost of only 2.4-dB contrast loss. The proposed image formation method can be used, e.g., to monitor deep brain stimulation procedures and localization of the electrode(s) deep inside the brain from two temporal bones on the sides of the human skull.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationAnatomical brain structures normalization for deep brain stimulation in movement disorders(Elsevier, 25.04.2020) Vogel, Dorian; Shah, Ashesh; Hemm-Ode, Simone [in: NeuroImage: Clinical]Deep brain stimulation (DBS) therapy requires extensive patient-specific planning prior to implantation to achieve optimal clinical outcomes. Collective analysis of patient’s brain images is promising in order to provide more systematic planning assistance. In this paper the design of a normalization pipeline using a group specific multi-modality iterative template creation process is presented. The focus was to compare the performance of a selection of freely available registration tools and select the best combination. The workflow was applied on 19 DBS patients with T1 and WAIR modality images available. Non-linear registrations were computed with ANTS, FNIRT and DRAMMS, using several settings from the literature. Registration accuracy was measured using single-expert labels of thalamic and subthalamic structures and their agreement across the group. The best performance was provided by ANTS using the High Variance settings published elsewhere. Neither FNIRT nor DRAMMS reached the level of performance of ANTS. The resulting normalized definition of anatomical structures were used to propose an atlas of the diencephalon region defining 58 structures using data from 19 patients.01A - Beitrag in wissenschaftlicher Zeitschrift