Abstract: A method for controlling an X-ray projection imaging device includes applying preferences for a serial radiography image acquisition to the X-ray projection imaging device. The method further includes executing the serial radiography image acquisition with the X-ray projection imaging device; recording data frames at different times during the serial radiography image acquisition; applying a trigger signal to the X-ray projection imaging device during the serial radiography image acquisition; and generating a snapshot image from a subset of the data frames, wherein the subset is chosen from the data frames recorded based on the trigger signal. A related system, a related control unit and a related X-ray projection imaging system are also disclosed.

Abstract: A method for controlling an X-ray projection imaging device includes applying preferences for a serial radiography image acquisition to the X-ray projection imaging device. The method further includes executing the serial radiography image acquisition with the X-ray projection imaging device; recording data frames at different times during the serial radiography image acquisition; applying a trigger signal to the X-ray projection imaging device during the serial radiography image acquisition; and generating a snapshot image from a subset of the data frames, wherein the subset is chosen from the data frames recorded based on the trigger signal. A related system, a related control unit and a related X-ray projection imaging system are also disclosed.

Abstract: Images of an object, such as OCT scans of a human eye, can include distortions and data gaps due to relative motion of the object and the image acquisition device. Methods and systems for correction of such distortions and data gaps are described herein. Motion-corrected data is arrived at by applying three-dimensional transforms to input three-dimensional data sets that represent at least partially overlapping regions of the imaged object. The three dimensional transforms are computed based on an objective function that accounts for similarity between the transformed three-dimensional data sets and the estimated motion of the object relative to an imaging instrument. Methods and systems described herein advantageously eliminate the need for postulated assumptions and reliance on landmarks and are capable of filling data gaps, thereby producing high quality, undistorted images of objects subject to movement during imaging.

Abstract: Images of an object, such as OCT scans of a human eye, can include distortions and data gaps due to relative motion of the object and the image acquisition device. Methods and systems for correction of such distortions and data gaps are described herein. Motion-corrected data is arrived at by applying three-dimensional transforms to input three-dimensional data sets that represent at least partially overlapping regions of the imaged object. The three dimensional transforms are computed based on an objective function that accounts for similarity between the transformed three-dimensional data sets and the estimated motion of the object relative to an imaging instrument. Methods and systems described herein advantageously eliminate the need for postulated assumptions and reliance on landmarks and are capable of filling data gaps, thereby producing high quality, undistorted images of objects subject to movement during imaging.

Abstract: Images of an object, such as OCT scans of a human eye, can include distortions and data gaps due to relative motion of the object and the image acquisition device. Methods and systems for correction of such distortions and data gaps are described herein. Motion-corrected data is arrived at by applying three-dimensional transforms to input three-dimensional data sets that represent at least partially overlapping regions of the imaged object. The three dimensional transforms are computed based on an objective function that accounts for similarity between the transformed three-dimensional data sets and the estimated motion of the object relative to an imaging instrument. Methods and systems described herein advantageously eliminate the need for postulated assumptions and reliance on landmarks and are capable of filling data gaps, thereby producing high quality, undistorted images of objects subject to movement during imaging.

Abstract: Images of an object, such as OCT scans of a human eye, can include distortions and data gaps due to relative motion of the object and the image acquisition device. Methods and systems for correction of such distortions and data gaps are described herein. Motion-corrected data is arrived at by applying three-dimensional transforms to input three-dimensional data sets that represent at least partially overlapping regions of the imaged object. The three dimensional transforms are computed based on an objective function that accounts for similarity between the transformed three-dimensional data sets and the estimated motion of the object relative to an imaging instrument. Methods and systems described herein advantageously eliminate the need for postulated assumptions and reliance on landmarks and are capable of filling data gaps, thereby producing high quality, undistorted images of objects subject to movement during imaging.