Abstract: A method of preparing a Polygoni Milletii Rhizome tincture includes: preparing a first mixture; extracting the first mixture with 70-90% ethanol under reflux condition to obtain a first extract solution; preparing a second mixture; extracting the second mixture with 50-70% ethanol to obtain a second extract solution; and mixing the first extract solution with the second extract solution to obtain the polygoni milletii rhizome tincture. A method of preparing a Polygoni Milletii Rhizome poultice includes: reparing a Polygoni Milletii Rhizome mixture; mixing the Polygoni Milletii Rhizome mixture and a skin penetration enhancer in water; mixing a moisturizing agent and a binder in water; adding a thickener in water; mixing methylparaben and ethylparaben in 90% ethanol; mixing all solutions to form a mixture; and applying the mixture on a non-woven fabric cloth and drying to form the Polygoni Milletii Rhizome poultice.

Abstract: Systems and methods for determining at least one scanning parameter for a scanning by an imaging device (110) are provided. The methods may include obtaining a scout image of at least one portion of a subject (502), and determining, in the scout image, a region of interest (ROI) corresponding to the at least one portion of the subject (504). The methods may further include determining, based on the ROI, the at least one scanning parameter associated with the at least one portion of the subject for performing the scanning by the imaging device (506). Systems and methods for evaluating a scanning parameter are further provided. The methods may include determining a scanning parameter associated with the ROI (1606) and obtaining a reference scanning parameter associated with the ROI (1608). The methods may further include determining whether the scanning parameter needs to be adjusted by comparing the scanning parameter and the reference scanning parameter (1610).

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: Systems and methods for a hybrid system-on-chip usable for predicting performance and power requirements of a host server include a big cores module, including central processing units, for receiving and pre-processing performance and power metrics data of the host server and to allocate computing resources, a small cores module, including massively parallel processing units, for mapping each instance associated with host server in the performance and power metrics data to a corresponding massively parallel processing unit based on the allocated computing resources for a per-instance metrics calculation, and an artificial intelligence (AI) accelerator for calculating performance and power prediction results based on the per-instance calculations from the small cores module.

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: Systems and methods for determining at least one scanning parameter for a scanning by an imaging device (110) are provided. The methods may include obtaining a scout image of at least one portion of a subject (502), and determining, in the scout image, a region of interest (ROI) corresponding to the at least one portion of the subject (504). The methods may further include determining, based on the ROI, the at least one scanning parameter associated with the at least one portion of the subject for performing the scanning by the imaging device (506). Systems and methods for evaluating a scanning parameter are further provided. The methods may include determining a scanning parameter associated with the ROI (1606) and obtaining a reference scanning parameter associated with the ROI (1608). The methods may further include determining whether the scanning parameter needs to be adjusted by comparing the scanning parameter and the reference scanning parameter (1610).

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: A system and method for image segmentation are provided. A three-dimensional image data set representative of a region including at least one airway may be acquired. The data set may include a plurality of voxels. A first-level seed within the region may be identified. A first-level airway within the region may be identified based on the first-level seed. A second-level airway may be identified within the region based on the first-level airway. The first-level airway and the second-level airway may be fused to form an airway tree.

Abstract: A system and method for image segmentation are provided. A three-dimensional image data set representative of a region including at least one airway may be acquired. The data set may include a plurality of voxels. A first-level seed within the region may be identified. A first-level airway within the region may be identified based on the first-level seed. A second-level airway may be identified within the region based on the first-level airway. The first-level airway and the second-level airway may be fused to form an airway tree.

Abstract: A system and method for image segmentation are provided. A three-dimensional image data set representative of a region including at least one airway may be acquired. The data set may include a plurality of voxels. A first-level seed within the region may be identified. A first-level airway within the region may be identified based on the first-level seed. A second-level airway may be identified within the region based on the first-level airway. The first-level airway and the second-level airway may be fused to form an airway tree.

Abstract: An image processing method is provided, including: obtaining image data of a cavity wall of an organ; unfolding the cavity wall; and generating an image of the unfolded cavity wall. The unfolding of the cavity wall may include: obtaining a mask and a centerline of the organ; obtaining a connected region of the mask; dividing the connected region into at least one equidistant block; determining an orientation of the equidistant block in a three-dimensional coordinate system including a first direction, a second direction and a third direction; determining an initial normal vector and an initial tangent vector of a center point of the centerline; assigning a projection of the initial normal vector to a normal vector of a light direction of the center point; assigning the third direction or an reverse direction of the third direction to a tangent vector of the light direction of the center point.

Abstract: A system and method for image segmentation are provided. A three-dimensional image data set representative of a region including at least one airway may be acquired. The data set may include a plurality of voxels. A first-level seed within the region may be identified. A first-level airway within the region may be identified based on the first-level seed. A second-level airway may be identified within the region based on the first-level airway. The first-level airway and the second-level airway may be fused to form an airway tree.