Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, a motion estimate is calculated between each of the mask images and a background region of the contrast image and a covariance is calculated for each motion estimate. Multiple background layer predictions are generated by generating a background layer prediction for each mask image based on the calculated motion estimate and covariance. The multiple background layer estimates are combined using statistical fusion to generate a final estimated background layer. The final estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: A method and system for co-registration of angiography data and intra vascular ultrasound (IVUS) data is disclosed. A vessel branch is detected in an angiogram image. A sequence of IVUS images is received from an IVUS transducer while the IVUS transducer is being pulled back through the vessel branch. A fluoroscopic image sequence is received while the IVUS transducer is being pulled back through the vessel branch. The IVUS transducer and a guiding catheter tip are detected in each frame of the fluoroscopic image sequence. The IVUS transducer detected in each frame of the fluoroscopic image sequence is mapped to a respective location in the detected vessel branch of the angiogram image. Each of the IVUS images is registered to a respective location in the detected vessel branch of the angiogram image based on the mapped location of the IVUS transducer detected in a corresponding frame of the fluoroscopic image sequence.

Abstract: A method and system for detecting a guiding catheter in a 2D fluoroscopic image is disclosed. A plurality of guiding catheter centerline segment candidates are detected in the fluoroscopic image. A guiding catheter centerline connecting an input guiding catheter centerline ending point in the fluoroscopic image with an image margin of the fluoroscopic image is detected based on the plurality of guiding catheter centerline segment candidates.

Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image by estimating a motion field between the mask image and the background image and performing covariance-based filtering over the estimated motion field. The mask image is then warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence.

Abstract: A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence.

Abstract: A method and system for co-registration of angiography data and intra vascular ultrasound (IVUS) data is disclosed. A vessel branch is detected in an angiogram image. A sequence of IVUS images is received from an IVUS transducer while the IVUS transducer is being pulled back through the vessel branch. A fluoroscopic image sequence is received while the IVUS transducer is being pulled back through the vessel branch. The IVUS transducer and a guiding catheter tip are detected in each frame of the fluoroscopic image sequence. The IVUS transducer detected in each frame of the fluoroscopic image sequence is mapped to a respective location in the detected vessel branch of the angiogram image. Each of the IVUS images is registered to a respective location in the detected vessel branch of the angiogram image based on the mapped location of the IVUS transducer detected in a corresponding frame of the fluoroscopic image sequence.

Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: A method and system for evaluating image segmentation is disclosed. In order to quantitatively evaluate an image segmentation technique, synthetic image data is generated and the synthetic image data is segmented to extract an object using the segmentation technique. This segmentation results in a foreground containing the extracted object and a background. The visibility of the extracted object is quantitatively measured based on the intensity distributions of the segmented foreground and background. The visibility is quantitatively measured by calculating the Jeffries-Matusita distance between the foreground and background intensity distributions. This method can be used to evaluate segmentation of vessels in fluoroscopic image sequences by coronary digital subtraction angiography (DSA).

Abstract: A method and system for detecting a guiding catheter in a 2D fluoroscopic image is disclosed. A plurality of guiding catheter centerline segment candidates are detected in the fluoroscopic image. A guiding catheter centerline connecting an input guiding catheter centerline ending point in the fluoroscopic image with an image margin of the fluoroscopic image is detected based on the plurality of guiding catheter centerline segment candidates.

Abstract: The present invention refers to a method and system for automatizing optimization of reuse of artifacts in industrial engineering, wherein the reuse of artifacts is optimized by assessing of artifacts based on classifying of artifacts by assessing of a top-down artifact and assessing of a bottom-up artifact. Assessing of a bottom-up artifact includes classifying of the bottom-up artifact based on a classification scheme for bottom-up artifacts using two dimensions for classification.

Abstract: A method and system for extracting motion-based layers from fluoroscopic image sequences are disclosed. Portions of multiple objects, such as anatomical structures, are detected in the fluoroscopic images. Motion of the objects is estimated between the images is the sequence of fluoroscopic images. The images in the fluoroscopic image sequence are then divided into layers based on the estimated motion. In a particular implementation, the coronary vessel tree and the diaphragm can be extracted in separate motion layers from coronary angiograph fluoroscopic image sequence.

Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, a motion estimate is calculated between each of the mask images and a background region of the contrast image and a covariance is calculated for each motion estimate. Multiple background layer predictions are generated by generating a background layer prediction for each mask image based on the calculated motion estimate and covariance. The multiple background layer estimates are combined using statistical fusion to generate a final estimated background layer. The final estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image by estimating a motion field between the mask image and the background image and performing covariance-based filtering over the estimated motion field. The mask image is then warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: The present invention refers to a method automatizing optimization of reuse of artifacts in industrial engineering, wherein the reuse of artifacts is optimized by assessing of artifacts based on classifying of artifacts. Further, the present invention relates to computing entities and system supporting the optimization of reuse of artifacts in industrial engineering. The present invention enables targeted dealing with deficits of reuse by which identification of artifacts being particularly suitable for reuse becomes possible.

Abstract: A method and system for detecting a spatial and temporal location of a contrast injection in a fluoroscopic image sequence is disclosed. Training volumes generated by stacking a sequence of 2D fluoroscopic images in time order are annotated with ground truth contrast injection points. A heart rate is globally estimated for each training volume, and local frequency and phase is estimated in a neighborhood of the ground truth contrast injection point for each training volume. Frequency and phase invariant features are extracted from each training volume based on the heart rate, local frequency and phase, and a detector is trained based on the training volumes and the features extracted for each training volume. The detector can be used to detect the spatial and temporal location of a contrast injection in a fluoroscopic image sequence.

Abstract: The invention relates to an interventional medical diagnosis or therapy system comprising: an imaging device, which is embodied for recording 3D images of an object under examination, with a control unit and an image processing unit; an at least two-axis robot arm, having means for yield control of the robot arm and a robot control unit for control of the robot arm; an instrument holder, which is connected to the robot arm, for holding an instrument; a position detection device, by means of which the position of the instrument is able to be detected for the robot control unit. The robot arm is embodied to yield to system-external force effects or to follow a system-external guidance.

Abstract: A method and system for evaluating image segmentation is disclosed. In order to quantitatively evaluate an image segmentation technique, synthetic image data is generated and the synthetic image data is segmented to extract an object using the segmentation technique. This segmentation results in a foreground containing the extracted object and a background. The visibility of the extracted object is quantitatively measured based on the intensity distributions of the segmented foreground and background. The visibility is quantitatively measured by calculating the Jeffries-Matusita distance between the foreground and background intensity distributions. This method can be used to evaluate segmentation of vessels in fluoroscopic image sequences by coronary digital subtraction angiography (DSA).

Abstract: A method and system for extracting coronary vessels fluoroscopic image sequences using coronary digital subtraction angiography (DSA) are disclosed. A set of mask images of a coronary region is received, and a sequence of contrast images for the coronary region is received. For each contrast image, vessel regions are detected in the contrast image using learning-based vessel segment detection and a background region of the contrast image is determined based on the detected vessel regions. Background motion is estimated between one of the mask images and the background region of the contrast image, and the mask image is warped based on the estimated background motion to generate an estimated background layer. The estimated background layer is subtracted from the contrast image to extract a coronary vessel layer for the contrast image.

Abstract: A method and system for extracting motion-based layers from fluoroscopic image sequences are disclosed. Portions of multiple objects, such as anatomical structures, are detected in the fluoroscopic images. Motion of the objects is estimated between the images is the sequence of fluoroscopic images. The images in the fluoroscopic image sequence are then divided into layers based on the estimated motion. In a particular implementation, the coronary vessel tree and the diaphragm can be extracted in separate motion layers from coronary angiograph fluoroscopic image sequence.