Abstract: A method is for calculating a personalized patient model including an external surface model of a patient and an organ model of the patient. In an embodiment, the method includes acquiring metadata of the patient, the metadata being assigned to at least one metadata category; ascertaining, using the patient metadata acquired, the external surface model of the patient and an internal anatomical model of the patient, the internal anatomical model including a body cavity of the patient; ascertaining the organ model of the patient using the patient metadata acquired and using the internal anatomical model of the patient ascertained; and calculating the personalized patient model, the external surface model of the patient ascertained and the organ model of the patient ascertained, being combined.

Abstract: A method for processing at least one X-ray image is provided. A variance of noise is signal dependent. The method includes applying a variance-stabilizing transformation to image data of the at least X-ray image to generate variance-stabilized data. At least one transform parameter of the variance-stabilizing transformation is dependent on a property of the at least one X-ray image that depends on an X-ray imaging device and/or a measurement parameter used to record the at least one X-ray image. A noise reduction algorithm is applied to the variance-stabilized data to generate noise-reduced data, and an inverse transformation of the variance stabilizing transformation is applied to the noise-reduced data to generate a denoised X-ray image.

Abstract: The invention relates to a method for evaluating treatment-relevant spatial anatomical information among different data sets of the heart, the method comprising the steps of: —determining a reference anatomical 3 dimensional data set of the heart, —providing a first anatomical 3 dimensional data set of the heart, the first anatomical 3 dimensional data set comprising first treatment-relevant spatial anatomical information, —providing a second anatomical 3 dimensional data set of the heart, the second anatomical 3 dimensional data set comprising second treatment-relevant spatial anatomical information, —registering the reference data set to the first and the second data sets, —transferring the treatment relevant spatial anatomical information of the first and the second data set to the reference data set in order to generate a first transferred treatment-relevant spatial anatomical information on the reference data set and a second transferred treatment-relevant spatial anatomical information on the reference

Abstract: A method and system for motion estimation modeling for cardiac and respiratory motion compensation is disclosed. Specifically, a coronary sinus catheter is tracked in a plurality of frames of a fluoroscopic image sequence; and cardiac and respiratory motion of a left atrium is estimated in each of the plurality of frames based on tracking results of the coronary sinus catheter using a trained motion estimation model.

Abstract: A method is for calculating a personalized patient model including an external surface model of a patient and an organ model of the patient. In an embodiment, the method includes acquiring metadata of the patient, the metadata being assigned to at least one metadata category; ascertaining, using the patient metadata acquired, the external surface model of the patient and an internal anatomical model of the patient, the internal anatomical model including a body cavity of the patient; ascertaining the organ model of the patient using the patient metadata acquired and using the internal anatomical model of the patient ascertained; and calculating the personalized patient model, the external surface model of the patient ascertained and the organ model of the patient ascertained, being combined.

Abstract: A method for automatic recognition of at least one anatomical landmark in a hollow organ of a patient is provided. The method includes providing an image dataset of the hollow organ, establishing or providing a three-dimensional mesh of a surface of the hollow organ from the image dataset, and determining a centerline of the mesh by skeletization. At least one feature is determined for each of a plurality of points on the centerline. A classifier pre-trained on the at least one feature is used for detecting candidates for the at least one anatomical landmark from the plurality of points. The candidates are grouped together with a distance from one another below a threshold. At least one specification determined from the anatomy of the hollow organ is used for confirming or rejecting the candidates for the at least one anatomical landmark. One or more candidates are defined as an anatomical landmark.

Abstract: A method for processing at least one X-ray image is provided. A variance of noise is signal dependent. The method includes applying a variance-stabilizing transformation to image data of the at least X-ray image to generate variance-stabilized data. At least one transform parameter of the variance-stabilizing transformation is dependent on a property of the at least one X-ray image that depends on an X-ray imaging device and/or a measurement parameter used to record the at least one X-ray image. A noise reduction algorithm is applied to the variance-stabilized data to generate noise-reduced data, and an inverse transformation of the variance stabilizing transformation is applied to the noise-reduced data to generate a denoised X-ray image.

Abstract: A method for automatic recognition of at least one anatomical landmark in a hollow organ of a patient is provided. The method includes providing an image dataset of the hollow organ, establishing or providing a three-dimensional mesh of a surface of the hollow organ from the image dataset, and determining a centerline of the mesh by skeletization. At least one feature is determined for each of a plurality of points on the centerline. A classifier pre-trained on the at least one feature is used for detecting candidates for the at least one anatomical landmark from the plurality of points. The candidates are grouped together with a distance from one another below a threshold. At least one specification determined from the anatomy of the hollow organ is used for confirming or rejecting the candidates for the at least one anatomical landmark. One or more candidates are defined as an anatomical landmark.

Abstract: A computer-implemented method for tracking one or more objects in a sequence of images includes generating a dictionary based on object locations in a first image included in the sequence of images. One or more object landmark candidates are identified in the sequence of images and a plurality of tracking hypothesis for the object landmark candidates are generated. A first tracking hypothesis is selected from the plurality of tracking hypothesis based on the dictionary.

Abstract: The invention relates to a method for evaluating treatment-relevant spatial anatomical information among different data sets of the heart, the method comprising the steps of:—determining a reference anatomical 3 dimensional data set of the heart,—providing a first anatomical 3 dimensional data set of the heart, the first anatomical 3 dimensional data set comprising first treatment-relevant spatial anatomical information,—providing a second anatomical 3 dimensional data set of the heart, the second anatomical 3 dimensional data set comprising second treatment-relevant spatial anatomical information,—registering the reference data set to the first and the second data sets,—transferring the treatment relevant spatial anatomical information of the first and the second data set to the reference data set in order to generate a first transferred treatment-relevant spatial anatomical information on the reference data set and a second transferred treatment-relevant spatial anatomical information on the reference data

Abstract: A method for model based motion tracking of a catheter during an ablation procedure includes receiving a training series of biplanar fluoroscopic images of a catheter acquired under conditions that will be present during an ablation procedure, segmenting and processing the series of biplanar images to produce a distance transform image for each biplanar image at each acquisition time, minimizing, for each pair of biplanar images at each acquisition time, a cost function of the distance transform image for each pair of biplanar images to yield a translation parameter that provides a best fit for a model of the catheter to each pair of biplanar images at each acquisition time, and calculating an updated catheter model for each acquisition time from said translation parameter.

Abstract: A method and system for detecting and tracking multiple catheters in a fluoroscopic image sequence in an integrated central processing unit and graphics processing unit framework is disclosed. A catheter electrode model is initialized in a first frame of the fluoroscopic image sequence. The catheter landmark candidates are detected, by a graphics processing unit, in the first frame of the fluoroscopic image sequence. The catheter electrode model is tracked, by a central processing unit, and is detected by the graphics processing unit, in subsequent frames of the fluoroscopic image sequence by detecting catheter landmark candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained catheter landmark detector, and outputting the catheter model tracking and landmark detection results of for each frame of the fluoroscopic image sequence.

Abstract: A method for compensating cardiac and respiratory motion in atrial fibrillation ablation procedures includes (a) simultaneously determining a position of a circumferential mapping (CFM) catheter and a coronary sinus (CS) catheter in two consecutive image frames of a series of first 2-D image frames; (b) determining a distance between a virtual electrode on the CS catheter and a center of the CFM catheter for a first image frame of the two consecutive image frames, and for a second image frame of the two consecutive image frames; and (c) if an absolute difference of the distance for the first image frame and the distance for the second image frame is greater than a predetermined threshold, compensating for motion of the CFM catheter in a second 2-D image.

Abstract: A method (200, 300) and system (100) for performing real-time, dynamic overlays on fluoroscopic images to aid in navigation and localization during medical procedures.

Abstract: A method for visualizing the quality of an ablation process with a processing and display unit is provided. A 3D dataset of an anatomical object and a 3D image model of an ablation instrument are provided, wherein the 3D image model models at least the surface of the ablation instrument. A position and an alignment of the 3D image model of the ablation instrument within the anatomical object is specified, wherein the 3D image model of the ablation instrument is incorporated into the 3D dataset of the anatomical object. At least a part of the incorporated 3D image model of the ablation instrument and of the 3D dataset of the anatomical object is presented and at least one characteristic quality value is determined as a function of the location of the 3D image model of the ablation instrument in relation to the anatomical object.

Abstract: A method and system for tracking an ablation catheter and a circumferential mapping catheter in a fluoroscopic image sequence is disclosed. Catheter electrode models for the ablation catheter and the circumferential mapping catheter are initialized in a first frame of a fluoroscopic image sequence based on user inputs. The catheter electrode models for the ablation catheter and the circumferential mapping catheter are then tracked in each remaining frame of the fluoroscopic image sequence. In each remaining frame, candidates of catheter landmarks such as the catheter tip, electrodes and body points are detected for the ablation catheter and the circumferential mapping catheter, tracking hypotheses for the catheter electrode models are generated, and for each of the ablation catheter and the circumferential mapping catheter, the catheter electrode model having the highest probability score is selected from the generated tracking hypotheses.

Abstract: A method for the detection of a balloon catheter within a fluoroscopic image, including: removing noise from a fluoroscopic image; detecting edges of a balloon catheter in the fluoroscopic image, wherein the detected edges include subsets of connected edges; extracting an edge subset from the subsets of connected edges; fitting a model to the extracted edge subset; removing outliers of the extracted edge subset based on the fitting of the model; adding the extracted edge subset without the outlier to a data set; repeating the extracting, fitting, removing and adding steps for the remainder of the subsets of connected edges; and fitting the model to the data set, wherein the data set is indicative of the balloon catheter.

Abstract: A method and system for motion estimation modeling for cardiac and respiratory motion compensation is disclosed. Specifically, a coronary sinus catheter is tracked in a plurality of frames of a fluoroscopic image sequence; and cardiac and respiratory motion of a left atrium is estimated in each of the plurality of frames based on tracking results of the coronary sinus catheter using a trained motion estimation model.

Abstract: A method and system for detecting and tracking coronary sinus (CS) catheter electrodes in a fluoroscopic image sequence is disclosed. An electrode model is initialized in a first frame of the fluoroscopic image sequence based on input locations of CS sinus catheter electrodes in the first frame. The electrode model is tracked in subsequent frames of the fluoroscopic image sequence by detecting electrode position candidates in the subsequent frames of the fluoroscopic image sequence using at least one trained electrode detector, generating electrode model candidates in the subsequent frames based on the detected electrode position candidates, calculating a probability score for each of the electrode model candidates, and selecting an electrode model candidate based on the probability score.

Abstract: A method for registering a two-dimensional image of a cardiocirculatory structure and a three-dimensional image of the cardiocirculatory structure includes acquiring a three-dimensional image including the cardiocirculatory structure using a first imaging modality. The acquired three-dimensional image is projected into two-dimensions to produce a two-dimensional projection image of the cardiocirculatory structure. A structure of interest is segmented either from the three-dimensional image prior to projection or from the projection image subsequent to projection. A two-dimensional image of the cardiocirculatory structure is acquired using a second imaging modality. The structure of interest is segmented from the acquired two-dimensional image. A first distance map is generated based on the two-dimensional projection image and a second distance map is generated based on the acquired two-dimensional image.