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Method and system for semantic segmentation in laparoscopic and endoscopic 2D/2.5D image data

A semantic segmentation and image technology, applied in image data processing, image analysis, image enhancement, etc., can solve problems such as 3D splicing difficulties

Inactive Publication Date: 2018-01-23
SIEMENS AG
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Problems solved by technology

However, accurate 3D stitching is difficult due to the complexity of camera and organ motions, as such 3D stitching requires stable estimation of the correspondence between consecutive frames of a laparoscopic or endoscopic image sequence.

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  • Method and system for semantic segmentation in laparoscopic and endoscopic 2D/2.5D image data
  • Method and system for semantic segmentation in laparoscopic and endoscopic 2D/2.5D image data
  • Method and system for semantic segmentation in laparoscopic and endoscopic 2D/2.5D image data

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Embodiment Construction

[0013] The present invention relates to a method and system for semantic segmentation in laparoscopic and endoscopic image data and 3D object stitching based on semantic segmentation. Embodiments of the present invention are described herein to give a visual understanding of methods of semantic segmentation and 3D object stitching. A digital image usually consists of a digital representation of one or more objects (or shapes). Digital representations of objects are generally described herein in terms of identifying and manipulating objects. Such operations are virtual operations implemented in the memory or other circuits / hardware of the computer system. Accordingly, it should be understood that embodiments of the invention may be implemented within a computer system using data stored within the computer system.

[0014] According to one embodiment of the invention, a sequence of 2D laparoscopic or endoscopic images is supplemented with a 2.5D image date (depth date) as inpu...

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Abstract

A method and system for semantic segmentation laparoscopic and endoscopic 2D / 2.5D image data are disclosed. Statistical image features that integrate a 2D image channel and a 2.5D depth channel of a 2D / 2.5 laparoscopic or endoscopic image are extracted for each pixel in the image. Semantic segmentation of the laparoscopic or endoscopic image is then performed using a trained classifier to classifyeach pixel in the image with respect to a semantic object class of a target organ based on the extracted statistical image features. Segmented image masks resulting from the semantic segmentation ofmultiple frames of a laparoscopic or endoscopic image sequence can be used to guide organ specific 3D stitching of the frames to generate a 3D model of the target organ.

Description

technical field [0001] The present invention relates to semantic segmentation of anatomical objects in laparoscopic or endoscopic image data, in particular, to segmentation of 3D models of target anatomical objects with 2D / 2.5D laparoscopic or endoscopic image data. Background technique [0002] During minimally invasive surgical procedures, the acquired image sequence is used to guide laparoscopic or endoscopic images of the surgical procedure. Multiple 2D images can be acquired and stitched together to generate useful 3D models for viewing organs. However, due to the complexity of camera and organ motion, accurate 3D stitching is difficult, as such 3D stitching requires stable estimation of correspondences between consecutive frames of a laparoscopic or endoscopic image sequence. SUMMARY OF THE INVENTION [0003] The present invention provides a method and system for semantic segmentation of intraoperative images, such as laparoscopic or endoscopic images. Embodiments ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11
CPCG06T2207/10028G06T2207/10068G06T2207/30004G06T7/11G06T7/344G06T7/13
Inventor 斯特凡·克卢克纳阿里·卡门陈德仁
Owner SIEMENS AG
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