Abstract:
A therapy planner (16) is configured to construct a therapy plan based on a planning image segmented into segments delineating features of a subject. A predictive plan adaptation module (20) is configured to adjust the segments to represent a foreseeable change in the subject and to invoke the therapy planner to construct a therapy plan corresponding to the foreseeable change. A data storage (18) stores a plurality of therapy plans generated for a subject by the therapy planner and the predictive plan adaptation module based on at least one planning image of the subject. A therapy plan selector (30) is configured to select one of the plurality of therapy plans for use in a therapy session based on a preparatory image acquired preparatory to the therapy session.
Abstract:
The present invention relates to a method for performing computer-aided detection (CAD) of a disease, e.g. lung tumours, on a medical image data set (20) from a imaging modality, such as MRI or CT. Initially, there is perform a segmentation of the medical image data set (20) using an anatomical model. Secondly, the segmented data is analyzed for characteristics of the disease resulting in a set of analysis data (25), and finally the set of analysis data (25) is evaluating with respect to the disease. At least one of these steps comprises as an input a position dependent probability (P_r) for the disease. The invention isadvantageous in that more efficient computations can be performed because the degree ofanalysis in a certain region of the part of the patient, e.g. the lung, can be adjusted or tailored to the level of probability of the disease in the that region. It is thereby possible to increase computational speed and thereby diseases like cancer, in particular cancer nodules in the lungs, can be more effectively found from medical image analysis.
Abstract:
A method for splitting a dataset relating to an anatomical tree structure (12) comprises establishing a plurality of seed points (24) within the tree structure; establishing a length of a path (20) along the tree structure from each of the plurality of seed points (24) to each of a plurality of other points (14); establishing a Euclidean distance (26) from each of the plurality of seed points (24) to each of the plurality of other points (14); associating with the seed point (24) a measure representing a likelihood that the seed point is the root point in dependence on the established lengths (20) and distances (26); identifying the root point of the tree structure (12) as the seed point (24) associated with a maximum measure representing the likelihood that the respective seed point is the root point; and establishing the principal bifurcation point (64) in dependence on the root point.
Abstract:
A system (500) for visualizing a vascular structure represented by a three- dimensional angiography dataset is disclosed. Respective voxel values are associated with respective voxels. The dataset represents a vascular structure. The system comprises means (502) for establishing respective filling values; means (504) for identifying respective minimum filling values; means (506) for computing respective deficiency values; and an output (514) for providing a visualization in dependence on the deficiency values. A respective filling value is indicative of an amount of blood flow at the respective position in the vascular structure. A respective minimum filling value is a minimum of the filling values associated with the positions upstream of the respective position. A respective deficiency value is indicative of a difference between the filling value associated with the respective position and the minimum filling value associated with the respective position.
Abstract:
The present invention relates to an apparatus (1) for segmenting an object comprising sub-objects shown in an object image. The apparatus comprises a feature image generation unit (2) for generating a feature image showing features related to intermediate regions between the sub-objects and a segmentation unit (3) for segmenting the sub-objects by using the object image and the feature image. Preferentially, the feature image generation unit (2) is adapted for generating a feature image from the object image. In a further embodiment, the feature image generation unit (2) comprises a feature enhancing unit for enhancing features related to intermediate regions between the sub-objects in the object image.
Abstract:
A computer program to identify a single seed point in an image is presented in which a manually positionable region of interest is presented to the user in the image and a single seed point is selected according to pre-defined criteria from the pixels delineated by the region of interest. Such seed points are used to initialise, for example, segmentation algorithms. The invention improves accuracy of seed point selection and also increases reproducibility. In an advantageous embodiment the region of interest is also sizable and a workstation and computer mouse with rotatable control device are provided, where the rotatable control device is used to control the size of the region of interest.
Abstract:
Usually orthogonal slices of a three-dimensional image set of a tracheobronchial tree (40) of a body do not show the tracheobronchial plane. Thus, the plane has to be adjusted manually by the user by trial and error, which is a tedious and time consuming process. The concept of the invention suggests a method of automated extraction and display of at least one oblique slice (49) of the tracheobronchial plane from a three- dimensional image set of a body. The method is fully automated without any user interaction. According to the invention the method comprises the step of: automatically identifying set of image points being part of a tracheobronchial tree (40); automatically identifying at least one oblique slice (49) as a fit to the image points; automatically performing a reformation step on the three-dimensional image set to extract the oblique slice (49); and automatically displaying (Fig. 6, 7) the oblique slice (49) of the tracheobronchial plane. The concept also provides a respective system (1), image acquisition device, workstation and computer program product and information carrier.
Abstract:
An imaging method for identifying abnormal tissue in the lung is provided, comprising the recording of slice images of the lung by means of X-ray radiation, recording of blood vessels, differentiation of blood vessels and abnormal tissue, segmentation of the abnormal tissue and display of the segmented abnormal tissue on an output device. In addition, a computer tomograph for identifying abnormal tissue in the lung is provided, having a radiation source for recording slice images of the lung and blood vessels by means of X-ray radiation, a computer unit for differentiating the blood vessels from the abnormal tissue and for segmenting the abnormal tissue, as well as an output device for displaying the segmented abnormal tissue. Furthermore, a computer program is provided for controlling a computer tomograph for an identification of abnormal tissue in the lung by means of a radiation source, designed to record slice images of the lung and blood vessels by means of X-ray radiation, to differentiate the blood vessels from abnormal tissue, to segment the abnormal tissue and to control an output device for displaying the abnormal tissue.
Abstract:
For differential diagnosis of pulmonary nodules, a certain fraction of malignant nodules do not exhibit significant enhancement when averaged over the whole nodule volume. According to an exemplary embodiment of the present invention, not only a single averaged contrast enhancement number is determined, but an enhancement curve for each nodule, showing the enhancement as a function of distance to boundary of the nodule. This may provide for an improved differential diagnosis.
Abstract:
A system for displaying a plurality of registered images is disclosed. A first viewport unit (1) displays a representation of a first image dataset (4) in a first viewport (201). A second viewport unit (2) displays a representation of a second image dataset (5) in a second viewport (202). A position indication unit (7) enables a user to indicate a position in the first dataset (4) displayed in the first viewport (201), to obtain a user-indicated position. A corresponding position determining unit (8) determines a position in the second image dataset (5) corresponding to the user-indicated position, to obtain a corresponding position in the second image dataset (5), based on correspondence information (9) mapping positions in the first image dataset (4) to corresponding positions in the second image dataset (5). The second viewport unit (2) displays an indication of the corresponding position in the second viewport (202).