Abstract: This invention is related to a method to adjust the starting position of an acquisition trajectory of a mobile X-ray device that is to perform a portable X-ray tomography acquisition sequence. The invention supports an operator in positioning a mobile X-ray device such that it can subsequently successfully and autonomously perform a digital tomosynthesis exam. Alternatively may an operator provide visual input on a camera image on where he desires the tomosynthesis acquisition to be performed, allowing the mobile X-ray device to adjust its initial starting position autonomously.

Abstract: Digital signal representations of sub-images are obtained by applying an optimization process wherein a sum is minimized, the sum having a first term representing a measure of the consistency of the sum of a digital representations of sub-images with said radiographic image and wherein the second term is a sum of cost functions each describing the type of one of said sub-images.

Abstract: A method and system to correct for alignment errors between assumed and actual geometric parameters of an acquisition geometry during image reconstruction in a chest tomosynthesis application includes receiving at least 2 raw projection images acquired on at least 2 different positions in a known acquisition geometry, determining an actual geometric parameter value by determining the minimum of a redundant planes cost function which is calculated for a varying range of the geometric parameter values, and which is determined by: a) at least one plane which intersects an X-ray source trajectory with at least two points, b) an intersection between the planes and a detector surface for which points the source positions are determined, and c) for which the parameters determining the intersection (?, ?, l) are used for the construction of the cost function, applying the calculated actual geometric parameter value of the acquisition geometry for the image reconstruction of the plurality of images, characterized in t

Abstract: Tomographic images, acquired by iterative reconstruction of lower quality images, are enhanced by a trained neural network. Next, the enhanced tomographic images are input to the next step of the iterative reconstruction. For this purpose, one or several neural networks are trained with a first set of tomographic images and a second set of tomographic images at lower quality. The second set of tomographic images at lower quality are acquired by applying an iterative reconstruction algorithm to lower quality projection images. The iterative reconstruction can use a normal quality tomographic image as input.

Abstract: A visual indication is generated of depth locations of slices obtained by applying a reconstruction algorithm in a computed tomography method with given settings, the display being shown on the object, e.g. on the patient's lateral side or in close relation to the patient.

Abstract: A method and system to correct for alignment errors between assumed and actual geometric parameters of an acquisition geometry during image reconstruction in a chest tomosynthesis application includes receiving at least 2 raw projection images acquired on at least 2 different positions in a known acquisition geometry, determining an actual geometric parameter value by determining the minimum of a redundant planes cost function which is calculated for a varying range of the geometric parameter values, and which is determined by: a) at least one plane which intersects an X-ray source trajectory with at least two points, b) an intersection between the planes and a detector surface for which points the source positions are determined, and c) for which the parameters determining the intersection (?, ?, l) are used for the construction of the cost function, applying the calculated actual geometric parameter value of the acquisition geometry for the image reconstruction of the plurality of images, characterized in t

Abstract: A visual indication is generated of depth locations of slices obtained by applying a reconstruction algorithm in a computed tomography method with given settings, the display being shown on the object, e.g. on the patient's lateral side or in close relation to the patient.

Abstract: A computerized tomographic image exposure and reconstruction method wherein an object is subjected to irradiation during a relative movement of a source of radiation, the object, and a radiation detector and wherein a digital representation of the radiation image of the object is computed by applying a tomographic reconstruction algorithm to image data read out of the irradiated radiation detector. A number of projection images are generated, each of the projection images being generated by integrating X-ray beams continuously emitted during the relative movement through a predefined movement path, and the created projection images are modeled in a tomographic reconstruction algorithm.

Abstract: A computerized tomographic image exposure and reconstruction method wherein an object is subjected to irradiation during a relative movement of a source of radiation, saidthe object, and a radiation detector and wherein a digital representation of the radiation image of saidthe object is computed by applying a tomographic reconstruction algorithm to image data read out of the irradiated radiation detector. A number of projection images are generated, each of saidthe projection images being generated by integrating X-ray beams continuously emitted during saidthe relative movement through a predefined movement path, and the created projection images are modeled in a tomographic reconstruction algorithm.

Abstract: An image is segmented by subjecting the image to an iterative thresholding operation, and a hierarchical representation of clusters is obtained by analyzing the results of each of the iterative thresholding steps to find clusters of adjacent image elements. A type class is assigned to a leaf cluster of the hierarchical representation and the assigned class is propagated towards the top of the hierarchical representation. Then a mask is generated marking the locations of image elements contained in the top ancestral clusters of a specific type.

Abstract: An image is segmented by subjecting the image to an iterative thresholding operation, and a hierarchical representation of clusters is obtained by analyzing the results of each of the iterative thresholding steps to find clusters of adjacent image elements. A type class is assigned to a leaf cluster of the hierarchical representation and the assigned class is propagated towards the top of the hierarchical representation. Then a mask is generated marking the locations of image elements contained in the top ancestral clusters of a specific type.

Abstract: A method for processing a medical image represented by a digital image signal and accompanying image identification data wherein upon processing of one of the image and the image identifying data, a corresponding change of the other is effectuated.