Brainlab Ag

Birte Domnik

Kajetan Berlinger

Pascal Bertram

Elisa Garcia Corisco

Elisa Garcia Corsico

Ivana Ivanovska

A computer implemented method for determining a two dimensional DRR referred to as dynamic DRR based on a 4D-CT, the 4D-CT describing a sequence of three dimensional medical computer tomographic images of an anatomical body part of a patient, the images being referred to as sequence CTs, the 4D-CT representing the anatomical body part at different points in time, the anatomical body part comprising at least one primary anatomical element and secondary anatomical elements, the computer implemented method comprising the following steps: acquiring the 4D-CT; acquiring a planning CT, the planning CT being a three dimensional image used for planning of a treatment of the patient, the planning CT being acquired based on at least one of the sequence CTs or independently from the 4D-CT, acquiring a three dimensional image, referred to as undynamic CT, from the 4D-CT, the undynamic CT comprising at least one first image element representing the at least one primary anatomical element and second image elements representing the secondary anatomical elements; acquiring at least one trajectory, referred to as primary trajectory, based on the 4D-CT, the at least one primary trajectory describing a path of the at least one first image element as a function of time; acquiring trajectories of the second image elements, referred to as secondary trajectories, based on the 4D-CT; for the image elements of the undynamic CT, determining trajectory similarity values based on the at least one primary trajectory and the secondary trajectories, the trajectory similarity values respectively describing a measure of similarity between a respective one of the secondary trajectories and the at least one primary trajectory; determining the dynamic DRR by using the determined trajectory similarity values, and, in case the planning CT is acquired independently from the 4D-CT, further using a transformation referred to as planning transformation from the undynamic CT to the planning CT, at least a part of image values of image elements of the dynamic DRR being determined by using the trajectory similarity values.

Determination of dynamic DRRs

The present invention relates to a computer-implemented medical method for improving the suitability of a tracking structure for tracking by tessellating the tracking structure into a plurality of sub-tracking structures. The invention also relates to a computer configured to execute a program corresponding to the method and a medical system for improving the suitability of a tracking structure for tracking, the system including the aforementioned computer.

Soft tissue tracking using physiologic volume rendering

The disclosed method encompasses reconstruction of a three-dimensional position of a tracking structure (which may comprise a target of radiation treatment) as reconstructed tracking structure data from pairs of two-dimensional tracking images which are input as tracking image data. Each tracking image contained in a pair of tracking images is compared to a tracking representation of the tracking structure contained in a search template image generated from the same perspective onto the tracking structure as the associated tracking image and input as search template data. The tracking image having the highest at local degree of similarity to its associated search template image is selected as a starting point (the first tracking image) for computing a corresponding image position (a complement point) in the other tracking image (the second tracking image) on the basis of applying epipolar geometry outgoing from the position in the first tracking image associated with the highest local degree of similarity. The method then continues with determining whether there is a point in the second tracking image having a higher degree of similarity than the complement point. Depending on the result of this analysis, an accumulated value of similarity is determined for each pair of tracking images depending on the sum of similarity values of the maximum similarity points in the first and second tracking images so determined. The position of the tracking structure is determined as the intersection of back-projection lines of the points being associated with the highest sum of associated similarity values. Thereby, the reliability of position determination from stereoscopic two-dimensional x-ray images can be enhanced.

Soft tissue stereo-tracking

Disclosed is a computer-implemented method for determining a position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a corresponding computer program, a non-transitory program storage medium storing such a program and a computer for executing the program, as well as a system for the position of an anatomical tracking structure in a tracking image usable for controlling a radiation treatment such as at least one of radiotherapy or radio surgery of a patient, a system comprising an electronic data storage device and the aforementioned computer.

Binary tracking of an anatomical tracking structure on medical images

A medical data processing method, performed by a computer (), for determining error analysis data describing the registration accuracy of a first elastic registration between first and second image data (A, B) describing images of an anatomical structure of a patient, comprising the steps of: &#x2014;acquiring the first image data (A) describing a first image of the anatomical structure, &#x2014;acquiring the second image data (B) describing a second image of the anatomical structure, &#x2014;determining first registration data describing a first elastic registration of the first image data (A) to the second image data (B) by mapping the first image data (A) to the second image data (B) using a registration algorithm, &#x2014;determining second registration data describing a second elastic registration of the second image data (B) to the first image data (A) by mapping the second image data (B) to the first image data (A) using the registration algorithm, &#x2014;determining error analysis data describing the registration accuracy of the first elastic registration based on the first registration data and the second registration data.

Determination of registration accuracy

Determination of dynamic DRRS

A medical data processing method and system determines the position of an artifact in patient image data describing a set of tomographic slice images of an anatomical structure of a patient. The images are described by color Values. Color value difference data describing differences in color values for image elements in adjacent slice images is determined. At least one of positive or negative difference data, describing a subset of the differences and consisting of differences having a positive or negative value are determined. Smoothed difference data describing a smoothing of the differences contained in the positive or negative difference data are determined and, based on the positive or negative difference data and the smoothed difference data, artifact position data is determined describing the position of an artifact in the patient image data.

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Munich, Germany

Birte Domnik