Patents by Inventor Stefan Kluckner
Stefan Kluckner has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 10186038Abstract: A system and method includes creation of a combined network comprising an image segmentation network and an image representation network, the combined network to generate an image descriptor based on an input query image, training of the combined network based on a plurality of first images and a segmentation mask associated with each of the plurality of first images, reception of a first input query image, use of the combined network to generate an image descriptor based on the first input query image, determination of a matching image descriptor from a plurality of stored image descriptors, determination of a camera pose associated with the matching image descriptor, registration of the first input query image with image data based on the determined camera pose, generation of a composite image based on the registered first input query image and image data, and presentation of the composite image.Type: GrantFiled: July 18, 2017Date of Patent: January 22, 2019Assignee: Siemens Healthcare GmbHInventors: Stefan Kluckner, Vivek Kumar Singh, Shanhui Sun, Oliver Lehmann, Kai Ma, Jiangping Wang, Terrence Chen
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Publication number: 20190012806Abstract: The present embodiments relate to localizing a mobile device in a complex, three-dimensional scene. By way of introduction, the present embodiments described below include apparatuses and methods for using multiple, independent pose estimations to increase the accuracy of a single, resulting pose estimation. The present embodiments increase the amount of input data by windowing a single depth image, using multiple depth images from the same sensor, and/or using multiple depth image from different sensors. The resulting pose estimation uses the input data with a multi-window model, a multi-shot model, a multi-sensor model, or a combination thereof to accurately estimate the pose of a mobile device.Type: ApplicationFiled: July 6, 2017Publication date: January 10, 2019Inventors: Oliver Lehmann, Stefan Kluckner, Terrence Chen
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Publication number: 20190007671Abstract: A system and method includes generation of a first map of first descriptors based on pixels of a first two-dimensional depth image, where a location of each first descriptor in the first map corresponds to a location of a respective pixel of a first two-dimensional depth image, generation of a second map of second descriptors based on pixels of the second two-dimensional depth image, where a location of each second descriptor in the second map corresponds to a location of a respective pixel of the second two-dimensional depth image, upsampling of the first map of descriptors using a first upsampling technique to generate an upsampled first map of descriptors, upsampling of the second map of descriptors using a second upsampling technique to generate an upsampled second map of descriptors, generation of a descriptor difference map based on differences between descriptors of the upsampled first map of descriptors and descriptors of the upsampled second map of descriptors, generation of a geodesic preservation mType: ApplicationFiled: June 28, 2017Publication date: January 3, 2019Inventors: Vivek Kumar Singh, Stefan Kluckner, Yao-jen Chang, Kai Ma, Terrence Chen
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Publication number: 20180372715Abstract: A model-based method of inspecting a specimen for presence of an interferent (H, I, and/or L). The method includes capturing images of the specimen at multiple different exposures times and at multiple spectra having different nominal wavelengths, selection of optimally-exposed pixels from the captured images to generate optimally-exposed image data for each spectra, identifying a serum or plasma portion of the specimen, and classifying whether an interferent is present or absent within the serum or plasma portion. Testing apparatus and quality check modules adapted to carry out the method are described, as are other aspects.Type: ApplicationFiled: January 24, 2017Publication date: December 27, 2018Applicant: Siemens Healthcare Diagnostics Inc.Inventors: Stefan Kluckner, Yao-Jen Chang, Terrence Chen, Benjamin S. Pollack, Patrick Wissmann
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Publication number: 20180364268Abstract: A model-based method of classifying a specimen in a specimen container. The method includes capturing images of the specimen and container at multiple different exposures times, at multiple different spectra having different nominal wavelengths, and at different viewpoints by using multiple cameras. From the captured images, 2D data sets are generated. The 2D data sets are based upon selection of optimally-exposed pixels from the multiple different exposure images to generate optimally-exposed image data for each spectra. Based upon these 2D data sets, various components are classified using a multi-class classifier, such as serum or plasma portion, settled blood portion, gel separator (if present), tube, air, or label. From the classification data and 2D data sets, a 3D model can be generated. Specimen testing apparatus and quality check modules adapted to carry out the method are described, as are other aspects.Type: ApplicationFiled: January 24, 2017Publication date: December 20, 2018Applicant: Siemens Healthcare Diagnostics Inc.Inventors: Stefan Kluckner, Yao-Jen Chang, Terrence Chen, Benjamin S. Pollack
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Publication number: 20180365530Abstract: A model-based method of determining characteristics of a specimen container. The method includes providing a specimen container, capturing images of the specimen container at different exposures times and at different spectra having different nominal wavelengths, selecting optimally-exposed pixels from the images at different exposure times at each spectra to generate optimally-exposed image data for each spectra, and classifying the optimally-exposed pixels as at least being one of tube, label or cap, and identifying a width, height, or width and height of the specimen container based upon the optimally-exposed image data for each spectra. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are other aspects.Type: ApplicationFiled: January 24, 2017Publication date: December 20, 2018Applicant: Siemens Healthcare Diagnostics Inc.Inventors: Stefan Kluckner, Yao-Jen Chang, Terrence Chen, Benjamin S. Pollack
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Patent number: 10073848Abstract: A database stores reference photographs of an assembly. The reference photographs are from different orientations relative to the assembly. By matching the query photograph to one or more of the reference photographs, the pose of the assembly in the query photograph is determined. Based on the pose, the pixels of the two-dimensional query photograph are related to a three-dimensional representation from engineering data. Using labeled parts from the engineering data, the parts represented in the query photograph are identified, and part information (e.g., segmentation, number, or other metadata) is provided relative to the query photograph.Type: GrantFiled: March 17, 2015Date of Patent: September 11, 2018Assignee: Siemens AktiengesellschaftInventors: Stefan Kluckner, Arun Innanje, Jan Ernst, Terrence Chen
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Publication number: 20180242946Abstract: Multi-source, multi-type image registration is provided. Images are received from a plurality of image devices, and images are received from a medical imaging device. A pre-existing diagram of a probe of the medical imaging device is received. A four-dimensional model is determined based on the received images from the image devices. A pose of the probe of the medical imaging device is determined based on the pre-existing diagram of the probe and the received images from the image devices. The plurality of images from the medical imaging device are registered with the four-dimensional model based on a common coordinate system and the determined pose of the probe.Type: ApplicationFiled: September 3, 2015Publication date: August 30, 2018Inventors: Sasa Grbic, Tommaso Mansi, Stefan Kluckner, Charles Henri Florin, Terrence Chen, Dorin Comaniciu
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Publication number: 20180239936Abstract: Barcode tag conditions on sample tubes are detected utilizing side view images of sample tubes for streamlining handling in clinical laboratory automation systems. The condition of the tags may be classified into classes, each divided into a list of additional subcategories that cover individual characteristics of the tag quality. According to an embodiment, a tube characterization station (TCS) is utilized to obtain the side view images. The TCS enables the simultaneous or near-simultaneous collection of three images for each tube, resulting in a 360 degree side view for each tube. The method is based on a supervised scene understanding concept, resulting in an explanation of each pixel into its semantic meaning. Two parallel low-level cues for condition recognition, in combination with a tube model extraction cue, may be utilized. The semantic scene information is then integrated into a mid-level representation for final decision making into one of the condition classes.Type: ApplicationFiled: February 16, 2016Publication date: August 23, 2018Applicant: Siemens Healthcare Diagnostics Inc.Inventors: Stefan Kluckner, Yao-Jen Chang, Wen Wu, Benjamin Pollack, Terrence Chen
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Patent number: 10049301Abstract: A computer-implemented method for identifying an optimal set of parameters for medical image acquisition includes receiving a set of input parameters corresponding to a medical imaging scan of a patient and using a model of operator parameter selection to determine a set of optimal target parameter values for a medical image scanner based on the set of input parameters. The medical imaging scan of the patient is performed using the set of optimal target parameter values to acquire one or more images and feedback is collected from one or more users in response to acquisition of the one or more images. This feedback is used to update the model of operator parameter selection, thereby yielding an updated model of operator parameter selection.Type: GrantFiled: August 1, 2016Date of Patent: August 14, 2018Assignee: Siemens Healthcare GmbHInventors: Stefan Kluckner, Dorin Comaniciu
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Publication number: 20180189966Abstract: Systems and methods for model augmentation include receiving intra-operative imaging data of an anatomical object of interest at a deformed state. The intra-operative imaging data is stitched into an intra-operative model of the anatomical object of interest at the deformed state. The intra-operative model of the anatomical object of interest at the deformed state is registered with a pre-operative model of the anatomical object of interest at an initial state by deforming the pre-operative model of the anatomical object of interest at the initial state based on a biomechanical model. Texture information from the intra-operative model of the anatomical object of interest at the deformed state is mapped to the deformed pre-operative model to generate a deformed, texture-mapped pre-operative model of the anatomical object of interest.Type: ApplicationFiled: May 7, 2015Publication date: July 5, 2018Inventors: Ali Kamen, Stefan Kluckner, Yao-jen Chang, Tommaso Mansi, Tiziano Passerini, Terrence Chen, Peter Mountney, Anton Schick
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Publication number: 20180174311Abstract: A method and system for scene parsing and model fusion in laparoscopic and endoscopic 2D/2.5D image data is disclosed. A current frame of an intra-operative image stream including a 2D image channel and a 2.5D depth channel is received. A 3D pre-operative model of a target organ segmented in pre-operative 3D medical image data is fused to the current frame of the intra-operative image stream. Semantic label information is propagated from the pre-operative 3D medical image data to each of a plurality of pixels in the current frame of the intra-operative image stream based on the fused pre-operative 3D model of the target organ, resulting in a rendered label map for the current frame of the intra-operative image stream. A semantic classifier is trained based on the rendered label map for the current frame of the intra-operative image stream.Type: ApplicationFiled: June 5, 2015Publication date: June 21, 2018Inventors: Stefan Kluckner, Ali Kamen, Terrence Chen
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Publication number: 20180150929Abstract: A method and system for registration of 2D/2.5D laparoscopic or endoscopic image data to 3D volumetric image data is disclosed. A plurality of 2D/2.5D intra-operative images of a target organ are received, together with corresponding relative orientation measurements for the intraoperative images. A 3D medical image volume of the target organ is registered to the plurality of 2D/2.5D intra-operative images by calculating pose parameters to match simulated projection images of the 3D medical image volume to the plurality of 2D/2.5D intra-operative images, and the registration is constrained by the relative orientation measurements for the intra-operative images.Type: ApplicationFiled: May 11, 2015Publication date: May 31, 2018Inventors: Thomas PHEIFFER, Stefan KLUCKNER, Peter MOUNTNEY, Ali KAMEN
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Publication number: 20180108138Abstract: A method and system for semantic segmentation laparoscopic and endoscopic 2D/2.5D image data is disclosed. Statistical image features that integrate a 2D image channel and a 2.5D depth channel of a 2D/2.5 laparoscopic or endoscopic image are extracted for each pixel in the image. Semantic segmentation of the laparoscopic or endoscopic image is then performed using a trained classifier to classify each pixel in the image with respect to a semantic object class of a target organ based on the extracted statistical image features. Segmented image masks resulting from the semantic segmentation of multiple frames of a laparoscopic or endoscopic image sequence can be used to guide organ specific 3D stitching of the frames to generate a 3D model of the target organ.Type: ApplicationFiled: April 29, 2015Publication date: April 19, 2018Inventors: Stefan Kluckner, Ali Kamen, Terrence Chen
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Patent number: 9934566Abstract: A method for reconstructing 3-D vessel geometry of a vessel includes: receiving a plurality of 2-D rotational X-ray images of the vessel; extracting vessel centerline points for normal cross sections of each of the plurality of 2-D images; establishing a correspondence of the centerline points; constructing a 3-D centerline vessel tree skeleton of the vessel; constructing an initial 3-D vessel surface having a uniform radius normal to the 3-D centerline vessel tree skeleton; and constructing a target 3-D vessel surface by deforming the initial vessel surface to provide a reconstructed 3-D vessel geometry of the vessel.Type: GrantFiled: July 12, 2016Date of Patent: April 3, 2018Assignee: Siemens Healthcare GmbHInventors: Shanhui Sun, Stefan Kluckner, Ahmet Tuysuzoglu, Ankur Kapoor, Günter Lauritsch, Terrence Chen
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Publication number: 20180082104Abstract: A method for performing cellular classification includes extracting a plurality of local feature descriptors from a set of input images and applying a coding process to covert each of the plurality of local feature descriptors into a multi-dimensional code. A feature pooling operation is applied on each of the plurality of local feature descriptors to yield a plurality of image representations and each image representation is classified as one of a plurality of cell types.Type: ApplicationFiled: March 30, 2015Publication date: March 22, 2018Inventors: Shaohua Wan, Shanhui Sun, Stefan Kluckner, Terrence Chen, Ali Kamen
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Publication number: 20180046883Abstract: Embodiments are directed to classifying barcode tag conditions on sample tubes from top view images to streamline sample tube handling in advanced clinical laboratory automation systems. The classification of barcode tag conditions leads to the automatic detection of problematic barcode tags, allowing for a user to take necessary steps to fix the problematic barcode tags. A vision system is utilized to perform the automatic classification of barcode tag conditions on sample tubes from top view images. The classification of barcode tag conditions on sample tubes from top view images is based on the following factors: (1) a region-of-interest (ROI) extraction and rectification method based on sample tube detection; (2) a barcode tag condition classification method based on holistic features uniformly sampled from the rectified ROI; and (3) a problematic barcode tag area localization method based on pixel-based feature extraction.Type: ApplicationFiled: February 16, 2016Publication date: February 15, 2018Applicant: Siemens Healthcare Diagnostics Inc.Inventors: Khurram Soomro, Yao-Jen Chang, Stefan Kluckner, Wen Wu, Benjamin Pollack, Terrence Chen
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Publication number: 20180032841Abstract: A computer-implemented method for identifying an optimal set of parameters for medical image acquisition includes receiving a set of input parameters corresponding to a medical imaging scan of a patient and using a model of operator parameter selection to determine a set of optimal target parameter values for a medical image scanner based on the set of input parameters. The medical imaging scan of the patient is performed using the set of optimal target parameter values to acquire one or more images and feedback is collected from one or more users in response to acquisition of the one or more images. This feedback is used to update the model of operator parameter selection, thereby yielding an updated model of operator parameter selection.Type: ApplicationFiled: August 1, 2016Publication date: February 1, 2018Inventors: Stefan Kluckner, Dorin Comaniciu
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Publication number: 20170165501Abstract: In order to provide radiation dose estimation during a treatment, one or more characteristics of the patient are used. A camera captures the patient so that the characteristics (e.g., organ position) may be derived. Radiation exposure and/or absorption are determined from the characteristics. A Monte Carlo, machine-learnt, or other model estimates the dosage for different locations in the patient. During the treatment, the dosage may be presented as a warning when exceeding a threshold or other visualization.Type: ApplicationFiled: December 11, 2015Publication date: June 15, 2017Inventors: Saikiran Rapaka, Stefan Kluckner, Carol Novak, Puneet Sharma, Dorin Comaniciu
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Patent number: 9665936Abstract: A computer-implemented method for providing a see-through visualization of a patient includes receiving an image dataset representative of anatomical features of the patient acquired using a medical image scanner and acquiring a body surface model of the patient using an RGB-D sensor. The body surface model is aligned with the image dataset in a canonical/common coordinate system to yield an aligned body surface model. A relative pose of a mobile device is determined with respect to the RGB-D sensor and a pose dependent visualization of the patient is created by rendering the image dataset at a viewpoint corresponding to the relative pose of the mobile device. Then, the pose dependent visualization of the patient may be presented on the mobile device.Type: GrantFiled: September 25, 2015Date of Patent: May 30, 2017Assignee: Siemens Healthcare GmbHInventors: Stefan Kluckner, Vivek Kumar Singh, Kai Ma, Yao-Jen Chang, Terrence Chen, Daphne Yu, John Paulus, Jr.