Patent application number | Description | Published |
20100080434 | Method and System for Hierarchical Parsing and Semantic Navigation of Full Body Computed Tomography Data - A method and apparatus for hierarchical parsing and semantic navigation of a full or partial body computed tomography CT scan is disclosed. In particular, organs are segmented and anatomic landmarks are detected in a full or partial body CT volume. One or more predetermined slices of the CT volume are detected. A plurality of anatomic landmarks and organ centers are then detected in the CT volume using a discriminative anatomical network, each detected in a portion of the CT volume constrained by at least one of the detected slices. A plurality of organs, such as heart, liver, kidneys, spleen, bladder, and prostate, are detected in a sense of a bounding box and segmented in the CT volume, detection of each organ bounding box constrained by the detected organ centers and anatomic landmarks. Organ segmentation is via a database-guided segmentation method. | 04-01-2010 |
20110002520 | Method and System for Automatic Contrast Phase Classification - A method and system for classifying a contrast phase of a 3D medical image, such as a computed tomography (CT) image or a magnetic resonance (MR) image, is disclosed. A plurality of anatomic landmarks are detected in a 3D medical image. A local volume of interest is estimated at each of the plurality of anatomic landmarks, and features are extracted from each local volume of interest. The contrast phase of the 3D volume is determined based on the extracted features using a trained classifier. | 01-06-2011 |
20110007954 | Method and System for Database-Guided Lesion Detection and Assessment - A method and system for automatically detecting lesions in a 3D medical image, such as a CT image or an MR image, is disclosed. Body parts are detected in the 3D medical image. Anatomical landmarks, organs, and bone structures are detected in the 3D medical image based on the detected body parts. Search regions are defined in the 3D medical image based on the detected anatomical landmarks, organs, and bone structures. Lesions are detected in each search region using a trained region-specific lesion detector. | 01-13-2011 |
20110064291 | Method and System for Detection 3D Spinal Geometry Using Iterated Marginal Space Learning - A method and apparatus for automatic detection and labeling of 3D spinal geometry is disclosed. Cervical, thoracic, and lumbar spine regions are detected in a 3D image. Intervertebral disk candidates are detected in each of the spine regions using iterative marginal space learning (MSL). Using a global probabilistic spine model, a separate one of the intervertebral disk candidates is selected for each of a plurality of labeled intervertebral disk locations. | 03-17-2011 |
Patent application number | Description | Published |
20110116698 | Method and System for Segmentation of the Prostate in 3D Magnetic Resonance Images - A method and system for fully automatic segmentation the prostate in multi-spectral 3D magnetic resonance (MR) image data having one or more scalar intensity values per voxel is disclosed. After intensity standardization of multi-spectral 3D MR image data, a prostate boundary is detected in the multi-spectral 3D MR image data using marginal space learning (MSL). The detected prostate boundary is refined using one or more trained boundary detectors. The detected prostate boundary can be split into patches corresponding to anatomical regions of the prostate and the detected prostate boundary can be refined using trained boundary detectors corresponding to the patches. | 05-19-2011 |
20110222751 | Method and System for Automatic Detection and Segmentation of Axillary Lymph Nodes - A method and system for automatically detecting and segmenting lymph nodes in a 3D medical image, such as a CT image, is disclosed. A plurality of lymph node center point candidates are detected in the 3D medical image. A lymph node candidate is segmented for each of the detected lymph node center point candidates. Lymph nodes are detected from the segmented lymph node candidates by verifying the segmented lymph node candidates using a trained lymph node classifier. | 09-15-2011 |
20120014559 | Method and System for Semantics Driven Image Registration - A method and system for automatic semantics driven registration of medical images is disclosed. Anatomic landmarks and organs are detected in a first image and a second image. Pathologies are also detected in the first image and the second image. Semantic information is automatically extracted from text-based documents associated with the first and second images, and the second image is registered to the first image based the detected anatomic landmarks, organs, and pathologies, and the extracted semantic information. | 01-19-2012 |
20120070055 | Method and System for Liver Lesion Detection - A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification. | 03-22-2012 |
20120183193 | Method and System for Automatic Detection of Spinal Bone Lesions in 3D Medical Image Data - A method and system for automatic detection and volumetric quantification of bone lesions in 3D medical images, such as 3D computed tomography (CT) volumes, is disclosed. Regions of interest corresponding to bone regions are detected in a 3D medical image. Bone lesions are detected in the regions of interest using a cascade of trained detectors. The cascade of trained detectors automatically detects lesion centers and then estimates lesion size in all three spatial axes. A hierarchical multi-scale approach is used to detect bone lesions using a cascade of detectors on multiple levels of a resolution pyramid of the 3D medical image. | 07-19-2012 |
20120220855 | Method and System for MR Scan Range Planning - A method and system for determining a scan range for a magnetic resonance (MR) scan is disclosed. A plurality of 2D localizer images are received. A most likely position is detected in each localizer image for each of a plurality of anatomical landmarks associated with a target organ in each localizer image. A scan range is determined based on the detected most likely positions of each anatomic landmark in the localizer images. | 08-30-2012 |
20130223715 | IMAGE DATA DETERMINATION METHOD, IMAGE PROCESSING WORKSTATION, TARGET OBJECT DETERMINATION DEVICE, IMAGING DEVICE, AND COMPUTER PROGRAM PRODUCT - A second form of image data is determined from a first form of image data of an examination object in a radiological imaging system. A set of a defined plurality of input pixels in the image data of the first form is determined. In addition, a set of target form parameters of a target form model with a defined plurality of target form parameters is prognostically determined by way of a data-driven regression method from the plurality of input pixels. The number of target form parameters is smaller than the number of input pixels. The second form of image data is determined from the set of target form parameters. There is also described a method in radiological imaging for determining the geometric position of a number of target objects in a second form of image data and an image processing workstation for determining a second form of image data from a first form of image data as well as an imaging device. | 08-29-2013 |
20140219548 | Method and System for On-Site Learning of Landmark Detection Models for End User-Specific Diagnostic Medical Image Reading - A method and system for on-line learning of landmark detection models for end-user specific diagnostic image reading is disclosed. A selection of a landmark to be detected in a 3D medical image is received. A current landmark detection result for the selected landmark in the 3D medical image is determined by automatically detecting the selected landmark in the 3D medical image using a stored landmark detection model corresponding to the selected landmark or by receiving a manual annotation of the selected landmark in the 3D medical image. The stored landmark detection model corresponding to the selected landmark is then updated based on the current landmark detection result for the selected landmark in the 3D medical image. The landmark selected in the 3D medical image can be a set of landmarks defining a custom view of the 3D medical image. | 08-07-2014 |
20140243654 | METHOD AND APPARATUS FOR GENERATION OF IMAGE DATA BASED ON MR THERMOMETRY DATA - In a method, apparatus and medical imaging system to generate image data based on magnetic resonance (MR) thermometry data, planning data of a region of an examination subject that is to be depicted thermometrically are provided to a processor. Through the processor, segmentation data based on the planning data are generated MR thermometry data are provided to the processor, which generates image data on the basis of the MR thermometry data, using the segmentation data. | 08-28-2014 |
20140254910 | IMAGING DEVICE, ASSIGNMENT SYSTEM AND METHOD FOR ASSIGNMENT OF LOCALIZATION DATA - A method of assigning first localization data of a breast of a patient derived from first image data of the breast, the first image data being the result of a first radiological data acquisition process, to second localization data of the same breast derived from second image data, the second image data being the result of a second radiological data acquisition process, or vice versa. Thereby, the first localization data are assigned to the second localization data by intermediately mapping them into breast model data representing a patient-specific breast shape of the patient and then onto the second image data—or vice versa, thereby deriving assignment data. An assignment system performs the above-described method. | 09-11-2014 |