Feature-based registration method

US2017263009A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2017263009-A1
Application numberUS-201715602867-A
CountryUS
Kind codeA1
Filing dateMay 23, 2017
Priority dateJun 3, 2008
Publication dateSep 14, 2017
Grant date

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

Methods for registering a three-dimensional model of a body volume to a real-time indication of a sensor position that involve analyzing scanned and sensed voxels and using parameters or thresholds to identify said voxels as being either tissue or intraluminal fluid. Those voxels identified as fluid are then used to construct a real-time sensed three-dimensional model of the lumen which is then compared to a similarly constructed, but previously scanned model to establish and update registration.

First claim

Opening claim text (preview).

1 - 20 . (canceled) 21 . A method for registering a three-dimensional model to an image of a sensor, the method comprising: inserting a sensor into a body lumen to acquire location data of the sensor; assigning a density value to each voxel of a plurality of voxels of a three-dimensional model based on the acquired location data; determining a voxel of the plurality of voxels, which is closest to the sensor, based on a plurality of parameters, each of which has a predefined threshold; and registering the closest voxel to the acquired location data. 22 . The method of claim 21 , wherein the density value is based on an advancement speed of the sensor. 23 . The method of claim 21 , wherein an advancement speed is inversely proportional to the density value is. 24 . The method of claim 21 , wherein the density value is a Hounsfield number. 25 . The method of claim 21 , wherein the density value to each voxel is proportional to a probability that the sensor occupies each voxel. 26 . The method of claim 21 , further comprising determining whether a voxel is tissue or air. 27 . The method of claim 26 , wherein a voxel is determined as tissue when the density value is higher than a threshold. 28 . The method of claim 26 , wherein a voxel is determined as airway when the density value is lower than a threshold. 29 . The method of claim 21 , wherein registering the voxel includes determining whether the density value of the voxel falls within a predetermined range. 30 . The method of claim 21 , wherein registering the voxel includes determining whether the voxel falls within a predefined proximity from a recently registered voxel. 31 . The method of claim 21 , wherein registering the closest voxel includes determining whether the density value fits with a template. 32 . The method of claim 31 , wherein the template is a group of continuous densities corresponding to air next to a plurality of densities corresponding to a blood vessel. 33 . The method of claim 21 , wherein registering the closest voxel includes: making a guess based on a known landmark; temporally registering a voxel to the acquired location data based on the guess; and determining the closest voxel that matches the plurality of parameters. 34 . The method of claim 33 , further comprising calculating a difference between the temporally registered voxel and the acquired location data. 35 . The method of claim 34 , wherein the closest voxel is determined based on the guess and the difference. 36 . A method for registering a three-dimensional model to a sensing volume of a sensor, the method comprising: segmenting a plurality of voxels of the three-dimensional model; inserting a sensor into a body lumen to acquire sensing volume voxels from the sensor; assigning a density value for each voxel of the sensing volume voxels; and segmenting the sensing volume voxels based on a threshold; and registering a first portion of the plurality of voxels of the three-dimensional model to the sensing volume voxels. 37 . The method of claim 36 , wherein the density value is based on an advancement speed of the sensor. 38 . The method of claim 36 , wherein an advancement speed is inversely proportional to the density value. 39 . The method of claim 36 , wherein the density value is a Hounsfield number. 40 . The method of claim 36 , wherein the density value of a voxel is proportional to a probability that the sensor occupies the voxel. 41 . The method of claim 36 , wherein a voxel is considered as tissue when a density value of the voxel is higher than the threshold. 42 . The method of claim 36 , wherein a voxel is considered as airway when a density value of the voxel is lower than the threshold. 43 . The method of claim 36 , wherein registering the first portion includes: calculating a difference between a value of each segmented voxel of the first portion and a value of a corresponding segmented voxel of the sensing volume voxels; and summing differences between the first portion and the sensing volume voxels to obtain a total value. 44 . The method of claim 43 , wherein registering the first portion further includes: determining the first portion, which gives a minimum total value; and registering the first portion, which gives the minimum total value, to the sensing volume voxels.

Assignees

Inventors

Classifications

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

  • Determination of transform parameters for the alignment of images, i.e. image registration · CPC title

  • Transmission computed tomography [CT] · CPC title

  • Blood vessel; Artery; Vein; Vascular · CPC title

  • using computed tomography systems [CT] · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US2017263009A1 cover?
Methods for registering a three-dimensional model of a body volume to a real-time indication of a sensor position that involve analyzing scanned and sensed voxels and using parameters or thresholds to identify said voxels as being either tissue or intraluminal fluid. Those voxels identified as fluid are then used to construct a real-time sensed three-dimensional model of the lumen which is then…
Who is the assignee on this patent?
Covidien Lp
What technology area does this patent fall under?
Primary CPC classification G06T7/337. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Sep 14 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).