Shanghai United Imaging Healthcare Co., Ltd.

Shanghai Zerun Biotechnology Co., Ltd.

Montage Technology (shanghai) Co., Ltd.

China Flash Co., Ltd.

Chiphomer Technology Limited

Ke Wu

Yufei Mao

Xu Wang

Xiaodong Wang

Wenjun Yu

Ce Wang

Peng Zhao

Chuanfeng Lv

Jieyan Ma

Menghua Zhang

Qiong Shen

Jianqiang Lei

Jingyu Yuan

Qianli Zhang

Yinghua Xiong

Roger Wei

Hong Nie

Xiong Yang

Jiantao Cheng

Saisai Su

Zhong Zhang

Hongjun Sun

Xiaodong Huang

Cheng-Tie Chen

Weijuan Li

Binxuan Sun

Goaxia Zhang

Yefen Wu

Xiang Su

Gaoxia Zhang

Chaoqun Wu

Weijian Zou

Systems and methods for image processing are provided. The systems may include obtaining an initial image relating to a blood vessel. The system may include determining a centerline of the blood vessel based on the initial image. The system may also include determining one or more images to be segmented of the blood vessel based on the centerline and the initial image. The system may also include determining a boundary of the lumen of the blood vessel and a boundary of the wall of the blood vessel in the each image for each of the one or more images. The system may further include analyzing the blood vessel based on the one or more boundaries of the lumen and the one or more boundaries of the wall.

Systems and methods for vascular image processing

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

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 method for generating semantic information may include obtain a scanning image. The scanning image may include a plurality of pixels representing an anatomical structure. The method may also include obtain a trained segmentation model. The method may further include determine a location probability distribution of the anatomical structure in the scanning image based on the trained segmentation model. The method may also include generate a segmentation result related to the anatomical structure based on the location probability distribution. The method may further include save the segmentation result into a tag of a digital imaging and communications in medicine (DICOM) file.

Systems and methods for generating semantic information for scanning image

The present disclosure provides methods and devices for determining liver segments in a medical image. The methods may be implemented on the devices. The method may include: obtaining a scan image; obtaining a segmentation protocol; obtaining segmentation information associated with the scan image; determining one or more marked points based on the segmentation information and the segmentation protocol; determining one or more segmentation surfaces based on the one or more marked points; and determining a segmentation result of at least part of a liver in the scan image based on the one or more segmentation surfaces.

Method and device for determining liver segments in a medical image

The present disclosure may provide a method for segmenting an image. The method may include obtaining an image and related information. The image may include a tumor region. The method may also include determining a region of interest in the image. The region of interest may include the tumor region. The method may also include performing a first segmentation of the region of interest to obtain a first segmentation result. The first segmentation may include: determining tumor morphology relating to the tumor region; performing a second segmentation of the region of interest to obtain a second segmentation result; and optimizing, based on the tumor morphology, the second segmentation result to obtain the first segmentation result.

Systems and methods for image segmentation

The present disclosure provides a method for modeling, including: S): designing a test key having a source, a drain, and a gate, and testing the test key to obtain test data; S): extracting a model parameter according to the test data; S): verifying reasonableness of a physical characteristic of the model parameter based on a relationship between a source-drain voltage and a drain current, if the reasonableness passes the verification, a model file is established and the method proceeds to S), if the reasonableness fails the verification, the method returns to S) to adjust the model parameter, until the reasonableness passes the verification; S): performing quality assurance on the model file, if the model file passes the quality assurance, the modeling is completed, if the model file fails the quality assurance, the method returns to S) to adjust the model parameter until the model file passes the quality assurance.

Method for modeling

A method and system for extracting vasculature. The method may include obtaining an image including a part representing a vessel, and obtaining a first image by extracting bone tissue in the image. The method may also include obtaining a second image by performing a region growing operation on the image. The method may further include generating a subtraction image based on the first image and the second image. The subtraction image may include at least a portion of the part representing the vessel in the image. The method may also include obtaining at least one vessel seed group based on a first condition and the subtraction image, and determining at least one vessel threshold based on at least one boundary distance field of the subtraction image. The method may further include obtaining a target vessel image by performing, based on the vessel seed group and the at least one vessel threshold, a region growing operation on the image.

Method and system for extracting vasculature

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.

According to a method in the present invention, first whether an inter-frame difference for each pixel in predetermined first region and second region in the dynamic image exceeds a predetermined threshold is judged to determine whether the pixel is a static information point, and when, in the second region, pixels in regions not overlapping with the first region are determined as non-static information points, judgment on the inter-frame difference and the predetermined threshold is stopped; and then static characteristic information in the dynamic image is determined based on the static information points in the first region. Preferably, the inter-frame difference for each pixel in the first region may be re-judged based on an adjusted predetermined threshold, to further determine the static characteristic information in the dynamic image, so that static opaque static characteristic information or static characteristic information with arbitrary degrees of transparency in the dynamic image can be detected.

Full-automatic detection method and system for static characteristic information in dynamic image

The present invention discloses a codon-optimized gene encoding major capsid protein L1 of human papilloma virus, which is capable, after transduced into a yeast cell, of efficiently expressing the major capsid protein L1 of human papilloma virus. The present invention also discloses an immunogenic macromolecule which is essentially produced by expression of said codon-optimized gene encoding the major capsid protein L1 of human papilloma virus in a yeast cell. The present invention further discloses the use of said immunogenic macromolecule and a composition comprising said immunogenic macromolecule.

Genes encoding major capsid protein L1 of human papilloma virus

An adaptive capacitive touch sense control circuit includes a voltage buffer, a current setting resistor, a current mirror, a capacitor, a start comparator, an end comparator and a time-to-digital converter. The capacitor is connected with the current setting resistor. The circuit further includes a latch with a first control switch and a second control switch. The current setting resistor is switched between the ground and a voltage source through a switching element, so that when the current setting resistor is grounded, the first control switch is closed and the second control switch is opened, and when the current setting resistor is connected with the voltage source, the second control switch is closed and the first control switch is opened. An adaptive charging mode is adopted to sense a capacitance variation with a great ability of interference recognition, a simple structure, low power consumption and real time processing.

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Shanghai, China

Ke Wu