1-9. (canceled)
10. A device for imparting a whirling motion on the flow of air for supplying a turbo-supercharged internal-combustion engine,
said device comprising:
an elbow-shaped portion of duct for the supply air, with an upstream branch and a downstream branch forming an angle between them; and
means for partializing the section of passage of the flow of air through said upstream branch, which is able to limit the section of passage of the fluid to an area that constitutes only a fraction of the total section of duct, adjacent to a wall of the duct, in such a way that the downstream branch of the aforesaid elbow portion is reached by a localized tangential flow adjacent to a wall of the duct that is thus forced, as a result of the change in direction from the upstream branch to the downstream branch, to traverse said downstream branch according to a substantially helical path,
wherein said partializing means comprise a throttle valve with a vane mounted oscillating about an axis in the upstream branch of the aforesaid elbow portion of duct, and wherein said upstream branch has a squared (rectangular) cross section, in that said axis of oscillation of the vane is orthogonal to two opposite walls of the aforesaid upstream branch of the duct, and in that said axis of oscillation is set at a distance from the central axis of said upstream branch in such a way that, when one end of the vane is in contact with a wall of the duct, the opposite end is set at a distance from the facing wall of the duct so as to leave free the aforesaid area of passage.
11. The device according to claim 10, wherein the aforesaid downstream branch has a circular cross section.
12. The device according to claim 10, wherein said vane has a profile with an aerodynamic wing so that, when said vane has a reduced inclination with respect to the axis of said upstream branch, the flow of air that laps the two opposite faces of the vane tends to remain adherent thereto in such a way that the entire flow is deflected by the vane in the direction of a wall of the duct.
13. An internal-combustion engine comprising a supercharger interposed in a duct for supplying the air to the engine, wherein the engine comprises a device according to claim 10 interposed in the supply duct upstream of the supercharger.
14. The internal-combustion engine according to claim 13, wherein the aforesaid device is interposed in the supply duct upstream of the confluence of a duct for recirculation of the exhaust gases.
15. The engine according to claim 14, wherein said duct for recirculation of the exhaust gases branches off from an exhaust duct of the engine, upstream of a turbine for driving the supercharger and upstream of a particulate filter.
16. The engine according to claim 13, wherein the engine is provided with an electronic control unit, which controls actuator means for controlling the aforesaid throttle valve according to signals indicating the engine r.p.m. and load and enables increase in the degree of opening of the throttle valve as the load and r.p.m. increase, according to a predetermined criterion.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A non-transitory computer readable medium storing executable instructions comprising:
a coarse segmentation component configured to determine, for each of a series of B-scan images, a set of constraint boundaries, based on natural contours within a region of tissue, from an optical coherence tomography (OCT) B-scan image and truncate all image area outside of the constraint boundaries to provide a truncated image;
a fine segmentation component configured to determine, for each truncated image, a set of pathology boundaries within the truncated image representing a cross-section of the pathological feature by defining an undirected graph having vertices representing image pixels and edges between the vertices having respective weights defined from a set of at least one image characteristic and find an optimal segmentation for the defined graph;
a mesh generation component configured to link the sets of pathology boundaries from adjacent images in the series of B-scan images to generate a polygonal mesh representing a volumetric reconstruction of the pathological feature; and
a user interface configured to provide the polygonal mesh to an associated display.
2. The non-transitory computer readable medium of claim 1, further comprising a volumetric measurement component configured to calculate volumetric parameters from the volumetric reconstruction representing the pathological feature.
3. The non-transitory computer readable medium of claim 2, further comprising a predictive model configured to predict a clinical outcome for a patient according to a plurality of predictors, the plurality of predictors including at least one volumetric parameter.
4. The non-transitory computer readable medium of claim 2, further comprising a predictive model configured to predict a clinical outcome for a patient according to a plurality of predictors, the plurality of predictors including at least one predictor that is a function of a first volumetric parameter, derived from an OCT scan taken prior to a start of a therapeutic intervention, and a second volumetric parameter, derived from an OCT scan taken after the start of a therapeutic intervention.
5. The non-transitory computer readable medium of claim 1, wherein the set of at least one image characteristic is a first set of at least one image characteristic and the fine segmentation component is configured to define the undirected graph such that each pixel has defined edges to each of a source and a sink vertex, the edges having respective weights based on a second set of at least one image characteristic and find the optimal segmentation for the defined graph as an optimal solution to a maximum-flow, minimum-cut problem defined by the undirected graph.
6. The non-transitory computer readable medium of claim 1, the second set of at least one image characteristic comprising a set of pixel intensity values and histogram similarity metrics representing regions of the image.
7. The non-transitory computer readable medium of claim 1, the set of at least one image characteristic for a given edge comprising a gradient between pixels linked by the edge and a neighborhood similarity metric representing the similarity of pixels connected to a given pixel associated with the edge.
8. A non-transitory computer readable medium storing executable instructions comprising:
a segmentation component configured to determine, for each of a series of images of a region of interest containing a pathological feature, a set of segmentation boundaries within the image representing a cross-section of the pathological feature by defining an undirected graph having vertices representing image pixels and edges between the vertices having respective weights defined from a set of at least one image characteristic and find an optimal segmentation for the defined graph;
a mesh generation component configured to link the sets of segmentation boundaries from adjacent images in the series of images to generate a polygonal mesh representing a volumetric reconstruction of the pathological feature;
a volumetric measurement component configured to calculate volumetric parameters from the volumetric reconstruction representing the pathological feature; and
a user interface configured to provide the calculated volumetric parameters to an associated display.
9. The non-transitory computer readable medium of claim 8, further comprising a predictive model configured to predict a clinical outcome for a patient according to a plurality of predictors, the plurality of predictors including at least one of the calculated volumetric parameters.
10. The non-transitory computer readable medium of claim 8, further comprising a predictive model configured to predict a clinical outcome for a patient according to a plurality of predictors, the plurality of predictors including at least one predictor that is a function of a first volumetric parameter, derived from a set of images taken prior to a start of a therapeutic intervention, and a second volumetric parameter, derived from a set of images taken after the start of a therapeutic intervention.
11. A system comprising:
an OCT imager to provide the a series of images of the region of interest;
the non-transitory computer readable medium of claim 8;
a processor operatively connected to the non-transitory computer readable medium; and
the display associated with the user interface.
12. A method comprising:
imaging a region of interest containing a pathological feature with an associated imager prior to a start of a therapeutic intervention to provide a set of pre-intervention scan data;
calculating a first value of a volumetric parameter from the set of pre-intervention scan data, wherein calculating a first value of a volumetric parameter from the set of pre-intervention scan data comprises:
determining, for each of a series of images in the pre-intervention scan data, a set of segmentation boundaries within each image representing a cross-section of the pathological feature by defining an undirected graph having vertices representing image pixels and edges between the vertices having respective weights defined from a set of at least one image characteristic and finding an optimal segmentation for the defined graph;
linking the sets of segmentation boundaries from adjacent images in the series of images to generate a polygonal mesh representing a volumetric reconstruction of the pathological feature; and
calculating the first value of the volumetric parameter from the volumetric reconstruction representing the pathological feature;
imaging the region of interest with the imager after the start of the therapeutic intervention to provide a set of post-intervention scan data;
calculating a second value of the volumetric parameter from the set of post-intervention scan data;
predicting a clinical outcome associated with the therapeutic intervention as at least a function of the first value of the volumetric parameter and the second value of the volumetric parameter, the clinic outcome comprising a minimum period of time for which it is necessary for the patient to remain in a prone position after the therapeutic intervention; and
displaying the predicted clinical outcome to a user at an associated output device.
13. The method of claim 12, wherein imaging the region of interest comprises imaging a region of eye tissue using an OCT imager to provide a series of B-scan images.
14. The method of claim 12, wherein the volumetric parameter can include one of a base area, a top area, a maximal base width, and a minimum width of the volume representing the pathological feature.
15. The method of claim 12, wherein predicting a clinical outcome associated with the therapeutic intervention comprises providing a plurality of predictors to a predictive model, the plurality of predictors including one of the function of the first value of the volumetric parameter and the second value of the volumetric parameter and a set including both of the first value of the volumetric parameter and the second value of the volumetric parameter.
16. The method of claim 15, the plurality of predictors comprising at least one biometric parameter representing the patient that is not derived from either of the set of pre-intervention scan data and the set of post-intervention scan data.
17. The method of claim 12, wherein the volumetric parameter represents one of a volume and a basal diameter.