摘要:
Virtual navigation (2255) and examination of virtual objects are enhanced using methods of insuring that an entire surface to be examined has been properly viewed. A user interface (FIG. 23) identifies regions which have not been subject to examination and provides a mechanism (2250) to route the user to these regions in the 3D display. Virtual examination is further improved by the use of measuring disks (905) to enhance quantitative measurements such as diameter, distance, volume and angle. Yet another enhancement to the virtual examination of objects is a method of electronic segmentation, or cleaning, which corrects for partial volume effects occurring in an object.
摘要:
A computer-assisted detection method is provided for detecting suspicious locations of lesions in the volumetric medical images. The method includes steps of features extraction and fusion. The first step is computing gradient feature for extraction of the layer of Partial Volume Effect (LPVE) between different tissues that related to specific organs. The LPVE will combine with the result of voxel classification to fulfill the task of tissue classification. After tissue classification, the contour of tissue boundary is determined. The gradient feature is also used to determine the direction that intensity changes. This direction that intensity changes most dramatically serves as the normal vector for voxel on the contour of the tissue boundary. The second step is to determine a local surface patch on the contour for each voxel on the contour. A local landmark system is then created on that patch and the so-called Euclidean Distance Transform Vector (EDTV) is computed based on those landmarks. The EDTV is the basic shape feature for lesion detection whose development and invasion results abnormal shape change on the tissue boundary. A vector classification algorithm for pattern recognition based on EDTVs is also provided. The voxel on the contour of tissue boundary can be grouped into areas based on similar pattern to form lesion patch and local lesion volume. That area will further be analyzed for estimation of the likelihood of lesion.
摘要:
An apparatus and method are provided for motion artifact detection and correction, where an apparatus includes a scanning device for receiving two-dimensional image slices of an object, a rendering device in signal communication with the scanning device for rendering a three-dimensional volume representation of the two-dimensional image slices, and a correction device in signal communication with the rendering device for correcting motion artifacts within the three-dimensional volume representation; and a corresponding method for detecting motion artifacts within scan data of a region comprising an object includes creating a three-dimensional representation with volume elements of the region based on the scan data, analyzing the volume elements along a boundary of the object, and determining the existence of a motion artifact in response to the analyzing.
摘要:
A system (300, 400, 800) and method (100, 200) are provided for building a digital sample library of lesions or cancers from medical images, the system (300) including an image scanner (310), image visualization or reviewing equipment (320) in signal communication with the image scanner, a digital sample library database (332), and a network for data communication connected between the library, the reviewing equipment, and the at least one scanner; and the method (100) including acquiring patient medical images (112), detecting target lesions in the acquired patient medical images (114, 116, 118), extracting digital samples (120) of the detected target lesions, collecting pathological and histological results (124, 126) of the detected target lesions, collecting diagnostic results of the detected target lesions (128), performing model selection and feature extraction (122) for each digital sample of a lesion, and storing (130) each extracted digital sample for library evolution.
摘要:
A system (100) and corresponding method for vessel segmentation are provided, the system having an adapter (112, 128, 130) for receiving image data, a processor (102) in signal communication with the input adapter, a pre-processing unit (170) in signal communication with the processor for pre-processing the received image data, and a vessel segmentation unit (180) in signal communication with the processor for segmenting vessels using pre-processed data; and the corresponding method including receiving image data, pre-processing the received data, and segmenting vessels responsive to the pre-processed data.
摘要:
A system (100) and corresponding method for vessel visualization are provided, the system having an input adapter (112, 128, 130) for receiving segmented vessel data, a processor (102) in signal communication with the input adapter, a vessel visualization unit (170) in signal communication with the processor for visualizing the vessel, and a calcium cleansing unit (180) in signal communication with the processor for removing the influences of calcium deposits from the visualized vessel; and the corresponding method including receiving segmented vessel data, visualizing a vessel in correspondence with the segmented vessel data, and cleansing calcium by removing the influences of calcium deposits from the visualized vessel.
摘要:
An imaging system for automated segmentation and visualization of medical images (100) includes an image processing module (107) for automatically processing image data using a set of directives (109) to identify a target object in the image data and process the image data according to a specified protocol, a rendering module (105) for automatically generating one or more images of the target object based on one or more of the directives (109) and a digital archive (110) for storing the one or more generated images. The image data may be DICOM-formatted image data (103), wherein the imaging processing module (107) extracts and processes meta-data in DICOM fields of the image data to identify the target object. The image processing module (107) directs a segmentation module (108) to segment the target object using processing parameters specified by one or more of the directives (109).