There is provided an information processing device that includes a display control unit that controls display of image data in which a biological region is captured, an information acquisition unit that acquires first region information input with respect to the image data, and a processing unit that generates second region information on the basis of the image data, the first region information, and a fitting mode.

Methods, systems, and articles of manufacture, including computer program products, are provided for image cleanup. In some embodiments, there is provide a method which may include subsampling a first image to a first level image of a multiscale transform; performing, based on a machine learning model, an identification of a foreground portion of the first level image and a background portion of the first level image; generating, based on the identification of the foreground portion and the background portion, a first mask; upscaling the first mask to a resolution corresponding to the first image depicting the foreground item; applying the upscaled first mask to the first image to form a second image depicting the foreground item; and providing the second image depicting the foreground item to a publication system. Related systems and articles of manufacture, including computer program products, are also provided.

Images that are associated with an identification of a tracking target of a patient to receive radiation treatment may be received. The images may be sorted into a sequence based on a motion of the patient. The sorted images may be provided via a graphical user interface. The sequence of the sorted images that are based on the motion of the patient may be provided.

Provided are a repair diagram generation device, a repair diagram generation method, and a program which accurately and efficiently generate a repair diagram showing a repair region to be repaired and a repair method from a captured image of a structure. A repair diagram generation device includes an image acquisition unit that acquires a captured image of a structure, a damage detection unit that detects damage from the captured image by image processing and specifies a degree of the damage, a method specifying unit that specifies a repair method of the damage based on the damage and the degree of the damage, and a repair diagram generation unit that generates a repair diagram showing a repair region and the repair method for repairing the damage based on the damage and the repair method.

Systems and methods for detecting an edge-perimeter of a wound from a digital wound image are disclosed, which may include: receiving, as an initial sampling point, an input from a user of a point on the digital wound image located inside of the wound; determining an initial edge-perimeter of the wound based on the initial sampling point by determining an initial representative color space spectrum from the initial sampling point; determining an initial center point of the wound on the digital wound image based on the initial edge-perimeter; determining a final edge-perimeter of the wound by using the initial center point as a second sampling point and determining a second representative color space spectrum from the second sampling point; and displaying an overlay of the final edge-perimeter superimposed on the digital wound image.

Rooms, structures, vehicles, and other objects can be accurately diagrammed, often without performing a physical on-site inspection. Photographs of a room, structure, vehicle, or other object are uploaded to a computer having a processor. A base calibration measure is determined for a room, structure, vehicle, object, or component thereof, depicted in the photographs using at least one known dimension for items observable in the photographs. The base calibration measure is then used to determine dimensions of other areas, items, or objects depicted in such photographs, and to create at least one scale diagram of the subject matter of the photographs. Damages areas of the structure/vehicle/object can be assessed from the scale diagram. The scale diagram can then be used to calculate appropriate insurance payment amounts for damage claims.

An image processing apparatus includes a memory and a processor coupled to the memory and configured to perform acquiring object area information representing an image area of a target object in an image from an image database, using the object area information to calculate a distance map representing distance values from a contour of the target object inside the image area, and generating, based on the distance map, a line of points representing a curved line reflecting a global shape of the target object.

A method and a system automatically generate a digital representation of an annulus structure of a valve from a segmented digital representation of a human internal heart. The basis for the segmented digital representation is multi-slice computed tomography image data. The method includes automatically determining, for at least a first effective time point, based on a segmentation, i.e. labels, of a provided input segmented digital representation, a candidate plane, and/or a candidate orientation vector together with a candidate center point, arranged with respect to the input segmented digital representation for the first effective time point, and candidate points for the annulus structure are determined automatically. From the candidate points acting as support points, a candidate spline interpolation is generated which is then adapted based on the input segmented digital representation. The digital representation of the annulus structure is then generated based on the adapted candidate spline interpolation.

A medical image processing method includes following steps. A first medical image about a first patient under a first examination condition is obtained. A second medical image about the first patient under a second examination condition is obtained. A first label corresponding to the first medical image is collected. The first label marks a lesion within the first medical image. A transformation function between the first medical image and the second medical image is calculated by aligning the first medical image with the second medical image. The transformation function is applied to convert the first label into a second label corresponding to the second medical image.

A curve alignment method and apparatus are provided. In the method, data obtained by at least one equipment analyzing a test sample is retrieved to generate test curves. In response to an alignment operation of directing a first point around a first curve to a second point around a second curve among the test curves, a correspondence between features corresponding to the first and second points is recorded, and correspondences of alignment operations are collected as feature data. Data obtained by the equipment analyzing a current sample is retrieved to generate current curves, and a third point matching the first feature on a third curve and a fourth point matching the second feature on a fourth curve are searched according to the correspondences. At least one of the third curve and the fourth curve is adjusted to align the third point with the fourth point.