Abstract: Embodiments of the present application provide a tissue boundary determination apparatus and method. The tissue boundary determination method includes acquiring multiple slice images of multiple positions of a tissue to be examined, determining, with regard to at least one first selected slice image of the multiple slice images, a tissue boundary on the first selected slice image, and determining, according to the tissue boundary on the first selected slice image, tissue boundaries on a predetermined number of other slice images adjacent to the first selected slice image. Therefore, an accurate tissue (such as malignant tumor) boundary may be acquired efficiently so as to provide a reference basis for analysis on internal and external tissue of a tumor.

Abstract: The present disclosure relates to an imaging system and method. Specifically, an imaging system comprises: a positioning image acquisition unit, configured to acquire a positioning image of a scanning object; a monitoring slice image acquisition unit, configured to determine a key point corresponding to the position of a target region of interest in the positioning image by using a neural network, and acquire a monitoring slice image of the scanning object at the position of the key point; and a target region-of-interest segmentation unit, configured to segment the monitoring slice image to obtain the target region of interest. The present disclosure can accurately acquire the position of the monitoring slice, and can accurately obtain the target region of interest through segmentation by a cascaded coarse segmentation and fine segmentation.

Abstract: Embodiments of the present application provide a medical imaging method and apparatus. The method includes acquiring a region of interest on a scout image of a subject using a deep learning method, determining a geometric center of an organ of interest of the subject according to the region of interest, and, according to the geometric center of the organ of interest and a geometric rotation center of a medical imaging device, driving a table to move. According to the embodiments of the present application, automatic movement of the table is achieved so that the geometric center of the organ of interest is close to the geometric rotation center of the medical imaging device, enabling diagnostic images to have higher image quality, including a higher image resolution. In addition, rays passing through the geometric rotation center of the medical imaging device are fully utilized, improving the dose efficiency of the rays.

Abstract: A Computed Tomography (CT) image generating method and an image data reconstruction device are provided. The method includes acquiring projection measurement data of a subject scanned by a CT device, reconstructing an initial scan image on the basis of the projection measurement data, wherein the initial scan image includes a plurality of slice images, and at least one of the slice images includes a main region image within a scan field of view and a truncated region image out of the scan field of view, determining whether a particular type of substance is present in the plurality of slice images, and performing artifact removal reconstruction on at least one of the slice images in response to determining that the substance is present in a truncated region image of the slice images, the artifact removal reconstruction being used to remove, from the slice images, artifacts caused by the substance.

Abstract: Embodiments of the present application provide a computed tomography imaging method and apparatus. The method includes pre-scanning an examined site by using an incomplete detector at a pitch factor of greater than 3 to obtain first data, axially scanning the examined site using the incomplete detector to obtain second data, stitching the first data and the second data to obtain third data; compensating the third data to obtain compensated third data, and performing image reconstruction by using the compensated third data to obtain a scanned image. Therefore, by performing two scans using an incomplete detector, stitching and compensating data obtained by the two scans, while reducing the total dose of X-rays, the integrity of the obtained data is ensured, and the image quality of the final obtained scanned image is maintained.

Abstract: Embodiments of the present application provide a medical image processing method and apparatus and a medical device, the medical image processing apparatus including an acquisition unit, configured to acquire raw local projection data obtained by a detector after an object to be examined is scanned, a processing unit, configured to recover the raw local projection data to estimate first global data, a determination unit, configured to determine second global data according to the raw local projection data and the first global data, and a reconstruction unit, configured to reconstruct the second global data to obtain a diagnostic image.

Abstract: Embodiments of the present invention provide a computed tomography (CT) imaging method and apparatus. The CT imaging method includes performing a three-dimensional scan of an examined site to obtain a three-dimensional scan image of the examined site and attenuation information of the examined site, the three-dimensional scan image being used to position a scan range. The method further includes calculating the tube current profile of an X-ray radiation dose for the examined site according to the three-dimensional scan image and attenuation information, and performing a main scan of the examined site according to the tube current profile to obtain a main scan image.

Abstract: Provided in embodiments of the present application are a medical image processing method, apparatus, and system. The medical image processing apparatus includes an acquisition unit, which acquires a first scout image obtained after a scout scan is performed on a subject to be examined, a first determination unit, which determines, according to a preset correspondence between a scout image and a section image, a predicted section image corresponding to a first region of interest in the first scout image, and a display unit, which displays in real time an updated predicted section image and scanning parameters corresponding to the updated predicted section image.

Abstract: The present application provides a method for obtaining a tube current value, a medical imaging system, and a non-transitory computer-readable storage medium. The example method for obtaining a tube current value includes obtaining a scanning protocol, performing a scout scan to obtain a scout image of a subject under examination, and obtaining a tube current value on the basis of a trained machine learning model, according to the scout image, the scanning protocol, and a preset image noise parameter.

Abstract: Described herein are an imaging system and method. Specifically, the imaging system includes a positioning image acquisition unit configured to acquire positioning images of a scanned object from a plurality of angles, a contour estimation unit configured to estimate a contour of the object in each positioning image in a scanning direction when truncation is present in at least one positioning image, and a display field of view determination unit configured to select a maximum value of an estimated contour as a display field of view of the image. A contour of a scanned object in each positioning image in a scanning direction is estimated when truncation is present in at least one positioning image, thereby determining a suitable display field of view. An appropriate display field of view can be set, so that a reconstructed image can cover the entire contour of the object and have a higher resolution.

Abstract: Embodiments of the present application provide a tissue boundary determination apparatus and method. The tissue boundary determination method includes acquiring multiple slice images of multiple positions of a tissue to be examined, determining, with regard to at least one first selected slice image of the multiple slice images, a tissue boundary on the first selected slice image, and determining, according to the tissue boundary on the first selected slice image, tissue boundaries on a predetermined number of other slice images adjacent to the first selected slice image. Therefore, an accurate tissue (such as malignant tumor) boundary may be acquired efficiently so as to provide a reference basis for analysis on internal and external tissue of a tumor.

Abstract: The present disclosure relates to an imaging system and method. Specifically, an imaging system comprises: a positioning image acquisition unit, configured to acquire a positioning image of a scanning object; a monitoring slice image acquisition unit, configured to determine a key point corresponding to the position of a target region of interest in the positioning image by using a neural network, and acquire a monitoring slice image of the scanning object at the position of the key point; and a target region-of-interest segmentation unit, configured to segment the monitoring slice image to obtain the target region of interest. The present disclosure can accurately acquire the position of the monitoring slice, and can accurately obtain the target region of interest through segmentation by a cascaded coarse segmentation and fine segmentation.

Abstract: An apparatus and method for configuring scan parameters for an imaging system are described. The method for configuring scan parameters includes acquiring an RGB image and a depth image of a scan object, computing physical parameters of the scan object according to the RGB image and the depth image of the scan object, and configuring, according to the physical parameters, scan parameters for scanning the scan object. In this way, the scan parameters for scanning the scan object can be automatically configured, which improves the efficiency and standardization of a scan process. Moreover, an appropriate configuration of scan parameters can further avoid rescanning and poor-quality scout images resulting from manual errors. An example apparatus that may be used to perform the method includes an acquisition unit for acquiring the RGB image, a first computation unit for computing the physical parameters, and a configuration unit for configuring the scan parameters.

Abstract: The present application provides an imaging method and system, and a non-transitory computer-readable storage medium. The imaging method comprises preprocessing projection data to obtain a predicted image of a truncated portion; performing forward projection on the predicted image to obtain predicted projection data of the truncated portion; and performing image reconstruction using the projection data obtained by forward projection and projection data of an untruncated portion.

Abstract: The present application provides a method and device for obtaining a predicted image of a truncated portion, an imaging method and system, and a non-transitory computer-readable storage medium. The method for obtaining a predicted image of a truncated portion comprises preprocessing projection data to obtain, by reconstruction, an initial image of the truncated portion; and calibrating the initial image based on a trained learning network to obtain the predicted image of the truncated portion.

Abstract: The present application provides an imaging method and system, and a non-transitory computer-readable storage medium. The imaging method comprises preprocessing projection data to obtain a predicted image of a truncated portion; performing forward projection on the predicted image to obtain predicted projection data of the truncated portion; and performing image reconstruction using the projection data obtained by forward projection and projection data of an untruncated portion.

Abstract: The present application provides a method and device for obtaining a predicted image of a truncated portion, an imaging method and system, and a non-transitory computer-readable storage medium. The method for obtaining a predicted image of a truncated portion comprises preprocessing projection data to obtain, by reconstruction, an initial image of the truncated portion; and calibrating the initial image based on a trained learning network to obtain the predicted image of the truncated portion.

Abstract: A power generation performance evaluation method and an apparatus thereof for a generator set are provided according to the embodiments of the present invention, which are related to the technical field of power apparatuses and are able to provide an accurate evaluation for the power generation performance of the generator set in combination with historical operation data of the generator set.