For obtaining an good yet easy to use luminance dynamic range conversion, we describe an image color processing apparatus (200) arranged to transform an input color (R,G,B) of a pixel of an input image (Im_in) having a first luminance dynamic range into an output color (Rs, Gs, Bs) of a pixel of an output image (Im_res) having a second luminance dynamic range, which first and second dynamic ranges differ in extent by at least a multiplicative factor 2, comprising: a maximum determining unit (101) arranged to calculate a maximum (M) of color components of the input color, the color components at least comprising a red, green and blue component; —a uniformization unit (201) arranged to apply a function (FP) to the maximum (M) as input, which function has a logarithmic shape and was predetermined to be of a fixed shape enabling to transform a linear input to a more perceptually uniform output variable (u); a function application unit (203) arranged to receive a functional shape of a function, which was specified previously by a human color grader, and apply the function to the uniform output variable (u), yielding a transformed uniform value (TU); a linearization unit (204) arranged to transform the transformed uniform value (TU) to a linear domain value (LU); a multiplication factor determination unit (205) arranged to determine a multiplication factor (a) being equal to the linear domain value (LU) divided by the maximum (M); and a multiplier (104) arranged to multiply at least three linear color components (R,G,B) by the multiplication factor (a), yielding the output color.

An image processing device includes: an image data acquisition unit for acquiring SPECT image data of a brain; a brain-region ROI definition unit for defining a brain-region ROI in the SPECT image; a striatum ROI definition unit for defining a striatum ROI in the SPECT image; and a threshold determination unit for, based on counts in the SPECT image's background which is the brain-region ROI except the striatum ROI, determining a threshold for distinguishing ventricles and sulci in the SPECT image; a region distinction unit for distinguishing between a region whose number of counts is smaller than or equal to the threshold and a region whose number of counts is larger than the threshold.

The present application discloses a method and apparatus for determining a route, a device and a computer storage medium, and relates to the field of big data. An implementation includes: acquiring route description information input by a user, and acquiring a route contour with the route description information; matching the route contour in road network data to obtain the route matched with the route contour, so as to generate recommended routes, wherein this operation specifically includes: extracting intersection points in the route contour, each of which is formed by intersecting at least two lines; selecting one of the intersection points, and querying the road network data using a corresponding angle sequence of the selected intersection point in the route contour, so as to obtain intersections matched with the selected intersection point as candidate intersections; traversing the candidate intersections, fixedly mapping the selected intersection point to the positions of the candidate intersections, equally scaling the route contour in the road network data, and recording mapped road information if all lines of the route contour are mapped onto connected roads; and generating the recommended routes with the recorded road information.

Using a computer-implemented intermediary by which contouring performed by two participants, such as two physicians, can be compared. First, contouring performed by each participant can be compared to contouring performed by the intermediary. Then, by way of the common intermediary and a transitive analysis, contouring performed by each participant can be compared.

A method for inspecting an object includes determining guide image data of the object from a determined orientation, the guide image data including a guide image pixel array and a pixel property for at least one guide image pixel in the guide image pixel array. The method also includes receiving inspection image data indicative of an inspection image and associating the inspection image data with the guide image data with a processor of a computing device. Additionally, the method includes determining a property of the object based on the guide image data and the associated inspection image data.

A method for inspecting an object includes receiving or determining inspection image data, the inspection image data including an inspection image pixel array with at least one inspection image pixel in the inspection image pixel array having a pixel property associated therewith. The method includes receiving via a processor a user input associated with a continuous segment of inspection image pixels in the inspection image pixel array. The method includes determining a property of the object based on the pixel properties associated with the continuous segment of inspection image pixels in the inspection image pixel array.

An interactive image marking method is introduced. The interactive image marking method includes the following steps, displaying a target image and at least one marked region in the target image; receiving an interactive signal, where the interactive signal corresponds to a first pixel of the target image; calculating a correlation between the first pixel and pixels of the target image, and determining a correlation range in the target image according to the correlation; editing the marked region according to the correlate range; and displaying the edited marked region. In addition, an electronic device and a recording medium using the method are also introduced.

Techniques for generating aligned, augmented reality views are disclosed. In some embodiments, an estimate of a floorplan of a three-dimensional space is first generated based on one or more received views of the three-dimensional space from a camera located in the three-dimensional space. A camera pose of the camera in the three-dimensional space is next determined based on generating a corrected floorplan from the estimate of the floorplan based on foreknowledge associated with the floorplan. Display of a rendering having the determined camera pose is facilitated in an actual view of the camera, resulting in an aligned, augmented reality view.

An ultrasonic imaging system produces more diagnostic cardiac images of the left ventricle by plotting the longitudinal medial axis of the chamber between the apex and mitral valve plane as a curved line evenly spaced between the opposite walls of the myocardium. Transverse image planes are positioned orthogonal to the curved medial axis with control points positioned in the short axis view on lines evenly spaced around and emanating from the medial axis. If the short axis view is of an oval shaped chamber the transverse image is stretched to give the heart a more rounded appearance resulting in better positioning of editing control points.

A method comprising identifying a robotic device and a calibration fixture in a vicinity of the robotic device; referencing the calibration fixture to a base of the robotic device to determine a first pose of the robotic device; receiving a 3D image of the environment, wherein the 3D image includes the calibration fixture; determining a second pose of the calibration fixture relative to the sensor; determining a third pose of the robotic device relative to the sensor based on the first pose and the second pose; receiving a plurality of trajectory points; determining a plurality of virtual trajectory points corresponding to the plurality of trajectory points based on the 3D image and the third pose; providing for display of the plurality of virtual trajectory points; and providing an interface for manipulating the virtual trajectory points.