Abstract: A system and method are provided for displaying medical images. A first viewport is generated which shows a part of a first medical image which shows a region of interest. A second viewport is generated which shows a part of a second medical image which shows a corresponding region of interest, e.g., representing a same anatomical structure or a same type of anatomical structure. In order to establish this ‘synchronized’ display of regions of interest, a displacement field is estimated between the first medical image and the second medical image. However, the displacement field is not used to deform the second medical image. Rather, the displacement field is used to identify the corresponding region of interest and thereby which part of the second medical image is to be shown. It is thus avoided that the second medical image itself is deformed, which would typically also deform the region of interest and thereby impair its assessment.

Abstract: The present invention is directed towards a system and method for transarterial chemoembolization using differently sized drug-eluting microsphere beads filled with drugs and determining a delivered drug concentration using an imaging system.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

Abstract: Minimally-invasive spinal inventions are often performed using fluoroscopic imaging methods, which can give a real-time impression of the location of a surgical instrument, at the expense of a small field of view. When operating on a spinal column, a small field of view can be a problem, because a medical professional is left with no reference vertebra in the fluoroscopy image, from which to identify a vertebra, which is the subject of the intervention. Identifying contiguous vertebrae is difficult because such contiguous vertebrae are similar in shape. However, characteristic features, which differentiate one vertebra from other vertebra, and which are visible in the fluoroscopic view, may be used to provide a reference.

Abstract: A voxel tagging system (100) includes a sensing enabled device (104) having an optical fiber (126) configured to sense induced strain within the device (Bragg grating sensor). An interpretation module (112) is configured to receive signals from the optical fiber interacting with an internal organ, e.g. heart, and to interpret the signals to determine positions visited by the at least one optical fiber within the internal organ. A data source (152, 154) is configured to generate data associated with an event or status, e.g. respiration, ECG phase, time stamp, etc. A storage device (116) is configured to store a history (136) of the positions visited in the internal organ and associate the positions with the data generated by the data source (152, 154).

Abstract: A method, system and program product are provided for planning an intervention procedure in a body lumen. A CT scan of the body lumen is performed. A virtual rendering is created of the inside of the body lumen corresponding to an interventional camera image. Then a virtual tape corresponding to a planned path for the intervention procedure is projected onto a wall of the body lumen. The virtual tape is projected onto the lumen wall, which is relatively distant from the camera point on the virtual rendering, so the tape does not appear to oscillate like a central thread. Also, since the virtual tape is located on the lumen wall, it does not occlude the center of the lumen, allowing a user to better visualize the lumen during planning, during fly through, and even during an actual intervention.

Abstract: The invention relates to an imaging system (10) for imaging an elongated region of interest of an object, an imaging method for imaging an elongated region of interest of an object, a computer program element for controlling such system for performing such method and a computer readable medium having stored such computer program element. The imaging system (10) comprises an acquisition unit (11) and a processing unit (13). The acquisition unit (11) is a C-arm acquisition unit and configured to acquire first image data of the object to be imaged with a first imaging parameter. The acquisition unit (11) is further configured to acquire second, different image data of an object to be imaged with a second imaging parameter. The second geometric imaging parameter is defined based on object specific data for the volume data to be aligned with the elongated region of interest of the object to be imaged. The processing unit (13) is configured to combine the first and second image data into volume data.

Abstract: A method includes determining a change in a volume of a tissue of interest located in at least two data sets between the at least two data sets. The at least two image data sets include a first image data set acquired at a first time and a second image data set acquired at a second time, and the first and second times are different. The method includes generating a rendering which includes a region in which the tissue of interest is located and indicia that indicates a magnitude of the change across the region. The region is superimposed over the rendering, which is generated based on at least one of the at least two image data sets, and linked to a corresponding image respectively in the at least two image data sets including voxels representing tissue of interest. The method includes visually presenting the rendering in a graphical user interface.

Abstract: Image processing method or apparatus (IP) to transform a 3D image data set (DS) into a visually protected one (DSX). The 3D image set includes an object region (OR) and a background region (BR) that defines s silhouette of an imaged object (P). An inadvertent or malicious direct volume rendering of the silhouette (IF) of the object is prevented by applying a randomization operation to at least the background region (BR).

Abstract: A method includes obtaining contrast-enhanced image data having a plurality of voxels, each voxel having an intensity value. The method further includes determining a vesselness value for each voxel. The method further includes determining a hypo-density value for each voxel. The method further includes weighting each of the intensity values by a corresponding vesselness value. The method further includes weighting each of the hypo- density values by the corresponding vesselness value. The method further includes combining the weighted intensity values and the weighted hypo-density values, thereby generating composite image data. The method further includes visually displaying the composite image data.

Abstract: The present invention relates to a method for segmenting MR Dixon image data. A processor and a computer program product are also disclosed for use in connection with the method. The invention finds application in the MR imaging field in general and more specifically may be used in the generation of an attenuation map to correct for attenuation by cortical bone during the reconstruction of PET images. In the method, a surface mesh is adapted to a region of interest by: for each mesh element in the surface mesh: selecting a water target position based on a water image feature response in the MR Dixon water image; selecting a fat target position based on a fat image feature response in the MR Dixon fat image; and displacing each mesh element from its current position to a new position based on both its water target position and its corresponding fat target position.

Abstract: A model-based segmentation system includes a plurality of clusters (48), each cluster being formed to represent an orientation of a target to be segmented. One or more models (140) are associated with each cluster. The one or more models include an aspect associated with the orientation of the cluster, for example, the appearance of the target to be segmented. A comparison unit (124), configured in memory storage media, is configured to compare an ultra-sound image to the clusters to determine a closest matching orientation and is configured to select the one or more models based upon the cluster with the closest matching orientation. A model adaptation module (126) is configured to adapt the one or more models to the ultrasound image.

Abstract: A method includes displaying a background image on a display screen. The method further includes receiving, from an input device, a signal indicative of a free hand line being drawn over the background image. The signal includes coordinates of points of the free hand line with respect to the display screen. The free hand line is independent of content represented in the background image. The method further includes storing the signal in a storage device. The method further includes generating a smooth stiff line based on the stored signal. The method further includes displaying the smooth stiff line over the background image.

Abstract: The present invention relates to an image processing device for detecting line structures in an image data set. The device comprises a model definition unit (12) for defining a line model of a line structure to be detected, said line model comprising a number of voxels, a calculation unit (14) for calculating, per voxel of interest of said image data set, several correlation values of a correlation between said line model and an image area around said voxel of interest, said image area comprising a corresponding number of voxels as said line model, wherein for each of a number of different relative orientations of said line model with respect to said image area a respective correlation value is calculated, and a determining unit (16) for determining, per voxel of interest, the maximum correlation value from said calculated correlation values and the corresponding optimal orientation at which said maximum correlation value is obtained.

Abstract: The present invention relates to devices, system and method for detecting gestures. The devices, systems and methods uses optically shape sensing devices for tracking and monitoring users. This allows unhindered, robust tracking of persons in different setting. The devices, systems and methods are especially useful in health care institutions.

Abstract: A method includes determining a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The method further includes registering first volumetric scan image data and second volumetric scan image data based on the registration transform. The method further includes generating registered image data. A system (100) includes a pre-scan registerer (122) that determines a registration transform between first three dimensional pre-scan image data and second three dimensional pre-scan image data based on a predetermined registration algorithm. The system further includes a volume registerer (126) that registers first volumetric scan image data and second volumetric scan image data based on the registration transform, generating registered image data.

Abstract: A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data, or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.

Abstract: A method includes obtaining 3D pre-scan image data generated from a scan of a subject. The 3D pre-scan image data includes voxels that represent a tissue of interest. The method further includes generating a 2D planning projection image showing the tissue of interest based on the 3D pre-scan image data. A system includes a 2D planning projection image from 3D pre-scan image data generator (218). The 2D planning projection image from 3D pre-scan image data generator obtains 3D pre-scan image data generated from a scan of a subject. The 3D pre-scan image data includes voxels that represent a tissue of interest. The 2D planning projection image from 3D pre-scan image data generator further generates a 2D planning projection image showing the tissue of interest based on the 3D pre-scan image data.

Abstract: A method includes obtaining first image data that includes voxel representing a structure of interest. The structure of interest includes a plurality of different sub-structures. The method further includes segmenting a volume of the first image data that includes only a single sub-structure for each of the plurality of different sub-structures. The method further includes creating a different local coordinate system for each of the different sub-structures for each of the volumes. The method further includes visually presenting the structure of interest through separate visual presentations of sets of reformatted images for each of the individual plurality of different sub-structures. A set of reformatted images for a sub-structure includes different cut planes generated from a corresponding segmented volume of the segmented volumes and the local coordinate system for the sub-structure.

Abstract: A method image data processor (318) includes a shape likelihood determiner (402) that processes voxels of image data and determines a likelihood that a voxel represents predetermined tissue of interest for a plurality of the voxels based on a shape of a tissue represented by the voxel, an opacity determiner (406) that determines an opacity suppression for each of the plurality of voxels based on the likelihood, a re-formatter (410) that re-formats the image data based on the determined opacity suppression, generating opacity suppressed re-formatted data, and a rendering engine (412) that visually presents the opacity suppressed re-formatted data.