Synthetic disease face image and disease facemask generation can provide training data for supervised learning of a variety of machine learning systems, including neural networks, which serve as detection models to detect disease or disorder affecting part or all of a person's face and/or cranium. Geometric transformations can be applied to facial images to generate the synthetic disease face images and disease facemasks.

A method for determining the image position of a marker point (3) in an image of an image sequence including the method steps of: setting (S2) a marker point in a first image (1) of the image sequence, determining (S4) a transformation at least between corresponding portions of the first image (1) and a second image (4) of the image sequence, transforming (S5) at least the portion of the first image (1) or the portion of the second image (4) on the basis of the transformation determined, localizing (S6) the marker point (3) in the transformed portion of the image (4), and mapping (S7) the localized marker point into the second image (4) on the basis of the determined transformation.

Systems and methods are disclosed for aligning a two-dimensional (2D) design image to a 2D projection image of a three-dimensional (3D) design model. One method comprises receiving a 2D design document, the 2D design document comprising a 2D design image, and receiving a 3D design file comprising a 3D design model, the 3D design model comprising one or more design elements. The method further comprises generating a 2D projection image based on the 3D design model, the 2D projection image comprising a representation of at least a portion of the one or more design elements, generating a projection barcode based on the 2D projection image, and generating a drawing barcode based on the 2D design image. The method further comprises aligning the 2D projection image and the 2D design image by comparing the projection barcode and the drawing barcode.

A sampling and weighting technique is presented. Given a 3D model that is composed out of n separated entities, a set of parameters is obtained for each entity. A weight is calculated for each entity, giving higher weight for entities corresponding to rarer parameters. Entities are assigned to components based on their corresponding parameters. Entities are sampled based on the weights or based on the components. A new 3D model is constructed from the sampled entities.

A method of defect validation for a device manufacturing process, the method including: obtaining a first image of a pattern processed into an area on a substrate using the device manufacturing process under a first condition; obtaining a metrology image from the area; aligning the metrology image and the first image; and determining from the first image and the metrology image whether the area contains a defect, based on one or more classification criteria.

The present invention discloses a registration method and system for a non-rigid multi-modal medical image. The registration method comprises: obtaining local descriptors of a reference image according to Zernike moments of order 0 and repetition 0 and Zernike moments of order 1 and repetition 1 of the reference image; obtaining local descriptors of a floating image according to Zernike moments of order 0 and repetition 0 and Zernike moments of order 1 and repetition 1 of the floating image; and finally obtaining a registration image according to the local descriptors of the reference image and the floating image. In the present, by using self-similarity of the multi-modal medical image and adopting the Zernike moment based local descriptor, the non-rigid multi-modal medical image registration is thus converted into the non-rigid mono-modal medical image registration, thereby greatly improving its accuracy and robustness.

Sparse phase unwrapping is disclosed. A first image and a second image are received. The first image and the second image are coregistered. The first image and the second image comprise respective phase data. An unwrapped interferogram is generated, including by solving an optimization problem using a nonconvex penalty function, where minimizing the penalty function produces sparse minimizers.

An image fusion-guidance device based on respiratory gating and CT includes a CT scanner, which is provided with a respiratory gating device and a gantry. A patient couch and a treatment head are provided in the gantry. A respiratory gating sensor is provided on the patient couch. The respiratory gating device is connected to a CT image workstation and an image fusion acquisition device via synchronization signal lines. The image fusion acquisition device is connected to an image fusion-processing device, which is connected to an image fusion display device. The treatment head is connected to a beam output controller via a beam output control line. The present application further provides an image fusion-guidance method based on respiratory gating and CT. In the guiding process, the patient is only required to hold the breath once, and then the patient breathes freely in the subsequent treatment.

Color calibration for digital pathology is provided. A standard glass slide is prepared with a specimen having zero or more stains. The specimen is scanned a first time using a hyperspectral imaging system to produce a first digital image having XYZ color values. The specimen is scanned a second time using a digital pathology imaging system to produce a second digital image having RGB color values. The first and second digital images are then registered against each other to align the digital image data. Individual pixels of the first and second images may be combined in the registration process so that the first and second digital images have substantially similar pixel sizes. A lookup table is generated to associate XYZ color values to RGB color values. Once the lookup table has been generated, it can be used to present RGB color on a display using the corresponding XYZ color.

An electronic device includes a camera, a memory, and a processor. The processor is configured to: (1) obtain a plurality of images having a first attribute with respect to an external object, by using the camera, (2) generate at least one first image by correcting images included in a first image set from among the plurality of images, during at least a portion of the obtaining of the plurality of images, (3) display the generated at least one first image, (4) obtain a plurality of images having a second attribute with respect to the external object, based on a received signal corresponding to an image capture of the external object, during the at least portion of obtaining the plurality of images, and (5) store at least one second image generated by correcting the plurality of images having the second attribute based on the first image set.