Ge Precision Healthcare LLC

Yanran Xu

Yu Huang

Fanbo Meng

Bingjie Zhao

Tiegong Zheng

Raghu Prasad

Mingyang Yang

Ziyu Liu

Jingyi Yang

Kiran Panchal

Yuting Dou

Hsieh Jiang

Adam G Pautsch

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.

Apparatus and method for configuring scan parameters

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.

Imaging system and method

A method for generating an object 3D point cloud in a medical imaging system comprising a machine table and a scanning device comprises: extracting a valid 3D point cloud in a valid region where the machine table is located from a global 3D point cloud based on a current height of the machine table and boundary information of the machine table, wherein the global 3D point cloud comprises 3D point clouds of an object and a surrounding environment thereof, and the object 3D point cloud is comprised in the valid 3D point cloud; and removing an environment 3D point cloud of the surrounding environment from the valid 3D point cloud to obtain the object 3D point cloud, wherein the surrounding environment comprises at least part of the machine table. In some embodiments, a moving path of the machine table in the medical imaging system is planned using the object 3D point cloud. In some embodiments, collision prediction of the object is performed in the medical imaging system using the object 3D point cloud.

Method and system for generating object 3D point cloud in medical imaging system

The present invention relates to a system and a method for calibration between coordinate systems of a 3D camera and a medical imaging apparatus. The calibration system includes a calibration tool having markers and a reference point that is aligned with a center of the medical imaging apparatus to serve as an origin of the coordinate system. Positions of the markers in the coordinate system of the medical imaging apparatus are calculated according to relative positions of the markers with respect to the reference point. A 3D camera captures images to determine positions of the markers in the coordinate system of the 3D camera. A calculation device calibrates the coordinate system of the 3D camera and the coordinate system of the medical imaging apparatus using the positions of the markers in the coordinate system of the 3D camera and the p in the coordinate system of the medical imaging apparatus.

System and method for calibration between coordinate systems of 3D camera and medical imaging apparatus and application thereof

The present invention relates to a system and a method for calibration between coordinate systems of a 3D camera and a medical imaging apparatus and an application thereof. The calibration system comprises: a calibration tool arranged on a scanning table, wherein the calibration tool is provided with markers and a reference point, the reference point is aligned with a center of the medical imaging apparatus to serve as an origin of the coordinate system of the medical imaging apparatus, and positions of the markers in the coordinate system of the medical imaging apparatus are calculated according to relative positions of the markers with respect to the reference point; a 3D camera for capturing images of the markers and determining positions of the markers in the coordinate system of the 3D camera based on the captured images; and a calculation device for calculating a calibration matrix using the positions of the markers in the coordinate system of the 3D camera and the positions of the markers in the coordinate system of the medical imaging apparatus, and performing calibration between the coordinate system of the 3D camera and the coordinate system of the medical imaging apparatus using the calibration matrix. The method corresponds to the aforementioned system. The present invention further relates to an application of the calibration and a computer-readable storage medium capable of implementing the method and the application.

The present invention relates to a method and system for automatically setting a scan range. The method comprises: receiving an RGB image and a depth image of an object positioned on a scan table, respectively, by an RGB image prediction model and a depth image prediction model; generating an RGB prediction result based on the RGB image and a depth prediction result based on the depth image with respect to predetermined key points of the object, respectively, by the RGB image prediction model and the depth image prediction model; selecting a prediction result for setting the scan range from the RGB prediction result and the depth prediction result; and automatically setting the scan range based on the selected prediction result.

Method and system for automatically setting scan range

The present invention relates to a 3D perspective indicator and a generation method therefor and an application thereof. The present invention specifically provides a 3D perspective indicator for a CT system and a generation method therefor as well as a method and an apparatus for controlling a scanning range in a CT system. The method for generating a 3D perspective indicator comprises: generating an upper boundary plane and a lower boundary plane perpendicular to a scanning direction and an auxiliary plane perpendicular to the upper boundary plane and the lower boundary plane in a coordinate system space of the CT system, the auxiliary plane being located above a to-be-scanned part of a patient; and identifying an upper contour line intersecting the upper boundary plane and a lower contour line intersecting the lower boundary plane in a point cloud generated based on a depth image of the patient, wherein the 3D perspective indicator comprises the upper contour line and the lower contour line, the upper boundary plane and the lower boundary plane, and the auxiliary plane. The present invention further provides a CT system using the apparatus and a computer-readable storage medium capable of implementing the method.

3D perspective indicator and generation method therefor and application thereof

Methods and systems are provided for estimating patient structure prior to a scan by a medical imaging system. As one example, a method may include acquiring depth images of a patient positioned on a table of the medical imaging system, correcting the depth images based on histogram data from the depth images, and extracting a three-dimensional structure of the patient based on the corrected depth images.

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Beijing, China

Yanran Xu