Method for processing 3d image data and 3d ultrasonic imaging method and system

Patent metadata

Field	Value
Publication number	US-2017367685-A1
Application number	US-201715678985-A
Country	US
Kind code	A1
Filing date	Aug 16, 2017
Priority date	Feb 16, 2015
Publication date	Dec 28, 2017
Grant date	—

Abstract

A method for display processing of 3D image data includes obtaining 3D volume data of the head of a target body; detecting a transverse section at an anatomical position from the 3D volume data according to image characteristic of the head of the target body in a transverse section related to the anatomical position; and displaying the transverse section.

First claim

What is claimed is:

1 . A method for processing 3D image data, comprising:
obtaining 3D volume data of a head of a target body; obtaining a transverse section image at an anatomical position of the head from the 3D volume data according to image characteristic of a transverse section of the head of the target body at the anatomical position; and displaying the transverse section image.

2 . The method of claim 1 , wherein the image characteristic is image grayscale characteristic.

3 . The method of claim 1 , wherein obtaining the transverse section image at the anatomical position from the 3D volume data according to the image characteristic of the transverse section of the head of the target body at the anatomical position comprises:
extracting candidate transverse section image set from the 3D volume data; obtaining a transverse section template image generated according to collected images at the anatomical position of at least one sample body; calculating a similarity index between each candidate transverse section image of the candidate transverse section image set and the transverse section template image to obtain a set of similarity indexes; selecting a similarity index which satisfies an image characteristic condition from the set of similarity indexes; and obtaining the candidate transverse section image corresponding to the selected similarity index as the transverse section image.

4 . The method of claim 1 , wherein obtaining the transverse section image at the anatomical position from the 3D volume data according to image characteristic of the transverse section of the head of the target body at the anatomical position comprises:
obtaining a median sagittal section image of the head from the 3D volume data; and obtaining the transverse section image from the 3D volume data based on the median sagittal section image.

5 . The method of claim 4 , wherein obtaining the transverse section image based on the median sagittal section image comprises:
extracting candidate transverse section image set from the 3D volume data based on the median sagittal section image; obtaining a transverse section template image generated according to collected images at the anatomical position of at least one sample body; calculating a similarity index between each candidate transverse section image of the candidate transverse section image set and the transverse section template image to obtain a set of similarity indexes; selecting a similarity index which satisfies an image characteristic condition from the set of similarity indexes; and obtaining a candidate transverse section image corresponding to the selected similarity index as the transverse section image.

6 . The method of claim 5 , wherein extracting candidate transverse section image set from the 3D volume data based on the median sagittal section image comprises:
extracting a reference target area from the median sagittal section image; and extracting transverse section images which are perpendicular to the median sagittal section image and pass through the reference target area to form the candidate transverse section image set, or, extracting a 3D volume data part containing the reference target area from the 3D volume data based on the transverse section images perpendicular to the median sagittal section image to obtain the candidate transverse section image set.

7 . The method of claim 5 , wherein calculating the similarity index between each candidate transverse section image of the candidate transverse section image set and the transverse section template image to obtain the set of similarity indexes comprises:
extracting image characteristic from the transverse section template image to obtain a first characteristic quantity; respectively extracting an image characteristic from each candidate transverse section image of the candidate transverse section image set as a second characteristic to obtain a set of second characteristic quantities; and respectively calculating a likelihood between each second characteristic quantity of the set of second characteristic quantities and the first characteristic quantity to obtain the set of similarity indexes.

8 . The method of claim 5 , wherein calculating a similarity index between each candidate transverse section image of the candidate transverse section image set and the transverse section template image to obtain a set of similarity indexes comprises:
constructing an image classification model, and training the image classification model by utilizing the transverse section template image to obtain a trained image classification model; and respectively inputting each candidate transverse section image of the candidate transverse section image set to the trained image classification model to obtain a classification tag corresponding to each candidate transverse section image to obtain the set of similarity indexes.

9 . The method of claim 5 , wherein extracting the candidate transverse section image set from the 3D volume data based on the median sagittal section image comprises:
extracting a straight line in a preset interval or extracting a straight line passing through a specific target area based on a linear equation on the median sagittal section image; and obtaining from the 3D volume data a transverse section image which contains the straight line and is perpendicular to the median sagittal section image to construct the candidate transverse section image set; or extracting a tangent on a boundary of a specific target area based on a linear equation on the median sagittal section image; and obtaining a 3D volume data part containing the specific target area from the 3D volume data by utilizing a transverse section image which contains the tangent and is perpendicular to the median sagittal section image to obtain the transverse candidate section image set.

10 . The method of claim 5 , wherein, prior to calculating the similarity index between each candidate transverse section image of the candidate transverse section image set and the transverse section template image, the method further comprises:
adjusting the candidate transverse section image set and/or the transverse section template image such that the candidate transverse section image set and the transverse section template image have a same scale.

11 . The method of claim 10 , wherein adjusting the candidate transverse section image set and/or the transverse section template image such that the candidate transverse section image set and the transverse section template image have a same scale comprises:
detecting an object of interest of the candidate transverse section image of the candidate transverse section image set; and adjusting the candidate transverse section image set to the same scale with the transverse section template image according to a size of the object of interest.

12 . A method for 3D ultrasonic imaging, comprising:
transmitting ultrasound waves to a head of a target body; receiving ultrasonic echoes to obtain ultrasonic echo signals; obtaining 3D volume data of the head of the target body based on the ultrasonic echo signals; obtaining a transverse section image at an anatomical position of the head from the 3D volume data according to image characteristic of a transverse section of the head of the target body at the anatomical position; and displaying the transverse section image.

13 . The method of claim 12 , wherein the image characteristic is image grayscale characteristic of image.

14 . The method of claim 12 , wherein obtaining the transverse section image at the anatom

Assignees

• Shenzhen Mindray Biomedical Electronics Co Ltd

Inventors

• Zou Yaoxian
• Brennan Kyle
• Lin Muqing
• Chen Zhijie

Classifications

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06F18/22

  Matching criteria, e.g. proximity measures · CPC title

• G06F18/24

  Classification techniques · CPC title

• G06T7/0014

  using an image reference approach · CPC title

• A61B8/483

  involving the acquisition of a 3D volume of data · CPC title