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Figure 4: (a) World elevation map, BW = 539. (b) World elevation map, truncated at BW = 69. (c-f) Convolution outputs between the set of lowpass filters shown in Figs. 2-3 and the world elevation map shown in (a).
Figure 4: (a) World elevation map, BW = 539. (b) World elevation map, truncated at BW = 69. (c-f) Convolution outputs between the set of lowpass filters shown in Figs. 2-3 and the world elevation map shown in (a).
Figure 2: Retinotopic Localization of Cortical Thickness Changes.
Figure 2: Retinotopic Localization of Cortical Thickness Changes.
Figure 3: Verbal learning performance was positively related to gray matter density in left medial temporal regions across the entire sample (N = 120, p < 0.001). See text for a detailed description of the statistical analyses and results.
Figure 3: Verbal learning performance was positively related to gray matter density in left medial temporal regions across the entire sample (N = 120, p < 0.001). See text for a detailed description of the statistical analyses and results.
Figure 4: An illustration of target visualization and trajectory planning in an integrated visual display that incorporates co-registered multi-modal images and models.
Figure 4: An illustration of target visualization and trajectory planning in an integrated visual display that incorporates co-registered multi-modal images and models.
Figure 2: Coronal slice of a real human brain. Indefinite tensors appear in the corpus callosum and yield higher than expected planar measures (see circles). The proposed method leads to a visibly smoother estimation of the planar measure within the highly anisotropic corpus callosum.
Figure 2: Coronal slice of a real human brain. Indefinite tensors appear in the corpus callosum and yield higher than expected planar measures (see circles). The proposed method leads to a visibly smoother estimation of the planar measure within the highly anisotropic corpus callosum.
Figure 2: Comparison of shape priors built from SDFs and binary maps. (a): Original training shape. (b): Slight modification of the training shape. (c): Projection on space of Shape built from SDFs. (d): Projection on space of Shape built from binary maps. Projections obtained using binary maps are more faithful to the learned shapes.
Figure 2: Comparison of shape priors built from SDFs and binary maps. (a): Original training shape. (b): Slight modification of the training shape. (c): Projection on space of Shape built from SDFs. (d): Projection on space of Shape built from binary maps. Projections obtained using binary maps are more faithful to the learned shapes.
Figure 4: 3D surface rendering of two reconstructed models of the portal vein and its connected veins. PV: Portal Vein, RPV: Right Portal Vein, LPV: Left Portal Vein, SV: Splenic Vein, SMV: Superior Mesenteric Vein.
Figure 4: 3D surface rendering of two reconstructed models of the portal vein and its connected veins. PV: Portal Vein, RPV: Right Portal Vein, LPV: Left Portal Vein, SV: Splenic Vein, SMV: Superior Mesenteric Vein.
Figure 7: (2d)-connectivity between points (top of the figure) allows for a change in topology when a point is removed even though the homology groups are isomorphic. Removing a point with an acyclic cubical neighborhood using (3d-1) connectivity does not allowsuch a change in topology. (a)Vertical loop. (b) Horizontal loop. (c) Vertical loop represented by cubes. (d) Removing the shaded cube preserves the vertical loop.
Figure 7: (2d)-connectivity between points (top of the figure) allows for a change in topology when a point is removed even though the homology groups are isomorphic. Removing a point with an acyclic cubical neighborhood using (3d-1) connectivity does not allowsuch a change in topology. (a)Vertical loop. (b) Horizontal loop. (c) Vertical loop represented by cubes. (d) Removing the shaded cube preserves the vertical loop.
Figure 1: Left: maxima (black dots) of persistence 0 and 160 (top row) and 640 and 2560 (bottom row) in a slice through one of the sample datasets. The voxel intensities range from 0 to 65535. The last persistence threshold is the most suitable for use in our algorithm. Right: high intensity regions corresponding to the coronary artery.
Figure 1: Left: maxima (black dots) of persistence 0 and 160 (top row) and 640 and 2560 (bottom row) in a slice through one of the sample datasets. The voxel intensities range from 0 to 65535. The last persistence threshold is the most suitable for use in our algorithm. Right: high intensity regions corresponding to the coronary artery.
Figure 2: Graphs depicting left hemisphere (red) and right hemisphere (orange) fractional anisotropy (FA) for each of the six individual patients. FA is shown for each patient across each of the 20 ROIs (plotted by ROI number/slice position, caudal to rostral) and is presented as the di¡erence from average control fractional anisotropy for the same ROI/hemisphere. Differences were calculated using values from the first control scanning session in all graphs to accurately represent patient changes between sessions. <b>(a)</b> Left versus right fractional anisotropy for patients pre-BTX. <b>(b)</b> Left versus right fractional anisotropy for cervical dystonia patients post-BTX. <b>(c)</b> Axial slice through aT1-weighted structural magnetic resonance image, with yellow lines marking the caudal (ROI1) to rostral (ROI 20) range of ROIs for which fractional anisotropy measurements are graphed in <b>(a)</b> and <b>(b)</b> (L, left hemisphere; R, right hemisphere). Red arrows indicate the path of the ansa lenticularis.The green box on the smaller image on the left indicates the field-of-view for the image on the right.
Figure 2: Graphs depicting left hemisphere (red) and right hemisphere (orange) fractional anisotropy (FA) for each of the six individual patients. FA is shown for each patient across each of the 20 ROIs (plotted by ROI number/slice position, caudal to rostral) and is presented as the di¡erence from average control fractional anisotropy for the same ROI/hemisphere. Differences were calculated using values from the first control scanning session in all graphs to accurately represent patient changes between sessions. (a) Left versus right fractional anisotropy for patients pre-BTX. (b) Left versus right fractional anisotropy for cervical dystonia patients post-BTX. (c) Axial slice through aT1-weighted structural magnetic resonance image, with yellow lines marking the caudal (ROI1) to rostral (ROI 20) range of ROIs for which fractional anisotropy measurements are graphed in (a) and (b) (L, left hemisphere; R, right hemisphere). Red arrows indicate the path of the ansa lenticularis.The green box on the smaller image on the left indicates the field-of-view for the image on the right.
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