37 results about "Semi automatic segmentation" patented technology

The invention discloses a segmentation method and system for an abdomen soft tissue nuclear magnetism image. The segmentation method comprises the steps that pre-segmentation is conducted on an area to be segmented through an area growing algorithm, then a morphological operator is adopted to conduct expansion and corrosion operations to carry out further processing on the pre-segmentation result, so that the pre-segmentation result forms an original segmentation outline. After rectification is conducted between a shape template set and the original segmentation outline, kernel principal component analysis is conducted, and prior shape information is obtained through a statistics model. The prior shape information is combined with data items of an energy function of a nuclear magnetism image segmentation model, and an energy function is built; a kernel graph cuts algorithm is used for carrying out segmentation on the original segmentation outline and an objective outline is obtained. The segmentation method and system can achieve semi-automatic segmentation, the system is simple, the robustness of the nuclear magnetism image segmentation algorithm is effectively improved so as to enable the segmentation result to be more accurate, and the segmentation method and system for the abdomen soft tissue nuclear magnetism image can be applied to nuclear magnetism image segmentation.

A system and method for segmenting and editing anatomical objects from medical images is disclosed. The system may be a medical diagnostic imaging system. A computer unit may execute computer software for segmenting anatomical objects from medical images. The computer software may extract an anatomical object from planar curves. The computer software may extract an anatomical object by computing the centerline of the anatomical object. A set of reformatted images may then be derived based on the centerline of the object. A user may then provide input in the form of user drawn contours on a plurality of reformatted images. In an embodiment the reformatted images may include a reformatted longitudinal view, a curved reformatted view, or a lumen view. The user drawn contours may correspond to the boundaries of the anatomical object to be segmented. The anatomical object may then be extracted based on the user drawn contours.

The embodiment of the invention provides an image segmentation annotation method and device, and the method comprises the steps: intercepting an image block from a to-be-segmented image, and enablingthe image block to comprise a to-be-segmented target object; segmenting the image block by using a trained segmentation model to obtain a segmentation result of the target object; wherein the segmentation model is used for predicting segmentation results of different types of objects and endowing the segmentation results of different types of objects with the same true value; and receiving an annotation instruction, and setting the true value of the segmentation result of the target object as the true value specified by the annotation instruction. The embodiment of the invention provides a semi-automatic segmentation annotation tool, and annotation time and labor cost can be reduced under the condition that the same precision as manual annotation is guaranteed.

A system and method for segmenting and editing anatomical objects from medical images is disclosed. The system may be a medical diagnostic imaging system. A computer unit may execute computer software for segmenting anatomical objects from medical images. The computer software may extract an anatomical object from planar curves. Additionally, the computer software may correct the shape of an existing three-dimensional anatomical object from planar curves. The planar curves may be orthogonal to each other. A user may contour of an anatomical object on a plurality of slices, such as an axial slice a sagittal slice, a coronal slice, or some combination thereof. The contour may be drawn using a tracing pen on a display unit. The display unit may receive touch screen input from the tracing pen. The display unit may display the three-dimensional segmented anatomical object.

In a method and apparatus for automatic or semi-automatic segmentation of a 3D image data set, acquired by a medical imaging apparatus, of an examination region that includes an organ, the 3D image data set is provided to a computer / processor, which is also provided with information with designating the type of organ imaged in the examination region. The 3D image data set is automatically segmented in the computer / processor using a model-based segmentation algorithm, wherein the designated type of organ is used as a basis of the model. The 3D data set is also automatically or semi-automatically segmented using a greyscale value-based segmentation algorithm. At least one of the segmentation results is displayed.

The invention is suitable for the technical field of image processing, and particularly relates to an ultrasound image segmentation method and system. The method includes the following steps that coarse registration is conducted on a statistical shape model and collected three-dimensional ultrasound data of a specified organ to obtain initialized coordinate transformation parameters; according to the initialized coordinate transformation parameters, an image segmentation algorithm based on particle filter is used for conducting iteration segmentation on the three-dimensional ultrasound data, wherein the statistical shape model is a combination of an average value obtained by training manual segmentation results of a plurality of high-definition three-dimensional data and a group of feature vectors of a representation change mode. Therefore, the problem that more artificial participation is needed in manual segmentation and semi-automatic segmentation is solved. Compared with an existing full-automatic segmentation method, the ultrasound image segmentation method and system solve the problems of low image resolution and segmentation accuracy under the image fuzzy condition.

The method for semi-automatic segmentation of lung CT image lesions disclosed in the present invention firstly divides the lung area, bone area and muscle area according to the data of all CT tomographic images of the patient's chest read by CT equipment, and initially determines the approximate location and range of the lesion to limit The region growing method segmented the lesion area of ​​other slices, and then enhanced the image of the segmented lesion area. The method of the present invention extracts data from each tomographic lesion based on the inherent characteristics that the same tissue has similar CT values ​​and the lesion body has continuity in three-dimensional space. The method is accurate and efficient for lesion segmentation, and has good practicability .

Apparatus, systems, and methods to generate an edge aware brush for navigation and segmentation of images via a user interface are disclosed. An example processor is to at least: construct a brush for segmentation of image data; provide an interactive representation of the brush with respect to the image data via a user interface, the interactive representation to be displayed and made available for interaction in each of a plurality of viewports provided for display of views of the image data in the user interface; enable update of the viewports based on manipulation of the representation; facilitate display of a preview of a segmentation of the image data corresponding to a location of the representation; and, when the segmentation is confirmed, facilitate generation of an output based on the segmentation.

The invention discloses a semi-automatic brain image segmentation method, in particular comprising the following steps: firstly, a map registration and a template selection method are used to obtain shape prior information of a target tissue and generate a segmentation template; Secondly, the template optimization method is used to reduce the error in the process of map registration and generate the initial active contour. Finally, the active contour model is used to segment the target tissue. The invention combines the advantages of the atlas registration method and the active contour segmentation method, and realizes the semi-automatic segmentation of the brain image. The method of the invention effectively utilizes shape prior information of the atlas, and can obtain smooth and continuous target tissue outline.