Shanghai United Imaging Healthcare Co., Ltd.

Shenzhen United Imaging Healthcare Co., Ltd.

Wenjun Yu

Ce Wang

Wei Wang

Yang Hu

Hongwei Chen

Xiangcui Jin

Haifeng Xiao

Lei Zhang

Xu Wang

Xiaodong Wang

Peng Zhao

Ke Wu

Yufei Mao

Chunlin Zhao

Fenggang Jia

Chuanfeng Lv

The present disclosure directs to a method for image processing. The method may include obtaining scanning data of a spine of a subject, determining one or more centrum parameters of each of a plurality of centrums of the spine based on the scanning data, and identifying at least one intervertebral disc based on the one or more centrum parameters. Each of the at least one intervertebral disc may be between a pair of neighboring centrums of the plurality of centrums. The method may include determining an intervertebral disc reconstruction protocol of each of the at least one intervertebral disc, determining a target intervertebral disc of the at least one intervertebral disc, and reconstructing one or more images of the target intervertebral disc based on an intervertebral disc reconstruction protocol of the target intervertebral disc. The intervertebral disc reconstruction protocols may relate to MPR.

System and method for medical imaging of intervertebral discs

A method for determining a centerline of a blood vessel in an image associated with a subject is provided. The method includes obtaining a centerline model used for identifying a centerline of a blood vessel and identifying the centerline of the blood vessel based on the centerline model.

Methods and systems for extracting blood vessel

The present disclosure provides computer-aided diagnosis systems and methods. The method may include obtaining multiple medical images of one or more bones; for at least one of the multiple medical images, detecting one or more bone fracture regions of the one or more bones in the medical image; causing a management list to be displayed for managing the one or more bones; receiving an instruction related to selecting at least one of the one or more bones, the instruction being generated through the management list; and upon receiving the instruction, causing the following to be displayed: at least one of one or more reconstructed bone images related to the at least one selected bone; or a marker of the one or more detected bone fracture regions related to the at least one selected bone.

Systems and methods for image processing

The present disclosure directs to a system and method for image processing. The method for image processing comprises acquiring a plurality of original computed tomography (CT) images of a spine of a subject; generating CT value images of the spine of the subject by processing the plurality of original CT images. The method further includes identifying an optimal sagittal image in which a centerline of the spine is located based on the CT value images. The method further includes identifying the centerline of the spine within the optimal sagittal image. The method further includes identifying a center point and a direction of at least one intervertebral disc along the centerline of the spine. The method still further includes reconstructing an image of the at least one intervertebral disc based on the center point and the direction of the at least one intervertebral disc.

Methods and systems for image processing are provided. Image data may be obtained. The image data may include a plurality of voxels corresponding to a first plurality of ribs of an object. A first plurality of seed points may be identified for the first plurality of ribs. The first plurality of identified seed points may be labelled to obtain labelled seed points. A connected domain of a target rib of the first plurality of ribs may be determined based on at least one rib segmentation algorithm. A labelled target rib may be obtained by labelling, based on a hit-or-miss operation, the connected domain of the target rib, wherein the hit-or-miss operation may be performed using the labelled seed points to hit the connected domain of the target rib.

System and method for image segmentation

The present disclosure provides computer-aided diagnosis systems and methods for detecting bone fracture. The method may include obtaining one or more medical images related to one or more bones. The method may also include obtaining a fracture detection model generated based on a machine learning model. The method may also include detecting, for at least one of the one or more medical images, one or more bone fracture regions of the one or more bones in the medical image using the fracture detection model.

Methods and systems for determining a region of interest (ROI) in an image associated with a subject are provided. Slice information of multiple slices of an image are identified and multiple slice ranges are determined based on the slice information. Based on the slice ranges, multiple sub-images of the image are then determined. For each sub-image, a template and a corresponding probability graph are acquired, a registration result is determined by registering the sub-image with the template, and a ROI in the sub-image is identified based on the registration result. A ROI of the image can be determined by combining the ROIs of the sub-images.

A system and method for obtaining a composite image by combining multiple sub-images are provided. In some embodiments, the method may include retrieving overlapping images corresponding to sub-images including 3D volume data, generating two-dimensional (2D) projection images and pixel maps based on the overlapping images, performing one or more registrations based on the 2D projection images and the pixel maps, calibrating the sub-images based on the results of the registration(s), and fusing the sub-images to produce a composite image. In some embodiments, the method may include setting a plurality of parameters relating to an X-radiation source or a radiation detector based on a preliminary number of exposures and a preliminary exposure region, controlling, based on at least one of the plurality of parameters, a motion of the X-radiation source or a motion of the radiation detector to capture a plurality of sub-images, and combining the plurality of sub-images.

System and method for image composition

The present disclosure relates to a method, system and non-transitory computer readable medium. In some embodiments, the method includes: acquiring a plurality of image slices related to a vertebral column, the vertebral column including a plurality of vertebrae; obtaining a classifier for verterbrae identification; identifying, by a processor, one or more vertebral foramina in the plurality of image slices using the classifier; and determining, by the processor, the plurality of vertebrae based on the one or more vertebral foramina.

Systems and methods for automatic vertebrae segmentation and identification in medical images

A method for extracting a blood vessel is provided. An image relating to a blood vessel may be acquired. The image may include multiple slices. A region of interest in the image may be determined. A blood vessel model may be obtained. The blood vessel may be extracted from the region of interest based on the blood vessel model.

A system and method for obtaining a composite image by combining multiple sub-images are provided. In some embodiments, the method may include retrieving overlapping images corresponding to sub-mages including 3D volume data, generating two-dimensional (2D) projection images and pixel maps based on the overlapping images, performing one or more registrations based on the 2D projection images and the pixel maps, calibrating the sub-images based on the results of the registration(s), and fusing the sub-images to produce a composite image. In some embodiments, the method may include setting a plurality of parameters relating to an X-radiation source or a radiation detector based on a preliminary number of exposures and a preliminary exposure region, controlling, based on at least one of the plurality of parameters, a motion of the X-radiation source or a motion of the radiation detector to capture a plurality of sub-images, and combining the plurality of sub-images.

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Shanghai, China

Wenjun Yu