Computer system for trabecular connectivity recovery of skeletal images reconstructed by artificial neural network through node-link graph-based bone microstructure representation, and method thereof

Patent metadata

Field	Value
Publication number	US-2023122282-A1
Application number	US-202217573762-A
Country	US
Kind code	A1
Filing date	Jan 12, 2022
Priority date	Oct 15, 2021
Publication date	Apr 20, 2023
Grant date	—

Abstract

Various embodiments relate to a computer apparatus for the bone microstructure connectivity recovery of a skeletal image reconstructed through an artificial neural network using the representations of a node-link graph-based bone microstructure and a method thereof. The computer apparatus and the method may be configured to represent a node-link graph from a bone microstructure of an input skeletal image, reinforce a connectivity of the bone microstructure in the node-link graph, and change the node-link graph into a skeletal image.

First claim

1 . A method of a computer apparatus, comprising:
representing a node-link graph from a bone microstructure of an input skeletal image; reinforcing a connectivity of the bone microstructure in the node-link graph; and changing the node-link graph into a skeletal image.

2 . The method of claim 1 , wherein the representing of the node-link graph comprises:
representing trabeculae of the bone microstructure as a plurality of links; and representing, as a plurality of nodes, points at which the links are connected and an open end of at least one of the links.

3 . The method of claim 2 , wherein the representing of the node-link graph further comprises:
obtaining a binarization image by performing image binarization on the inputted skeletal image; and obtaining a centerline image by performing centerline extraction in the binarization image, wherein the links are represented based on the centerline image.

4 . The method of claim 1 , wherein the computer apparatus reconstructs the skeletal image from the inputted skeletal image reconstructed through an artificial neural network.

5 . The method of claim 1 , wherein the reinforcing of the connectivity of the bone microstructure comprises adjusting, as an adjacent element, a location of an open node in the node-link graph.

6 . The method of claim 5 , wherein the open node is a node having a node degree of 1.

7 . The method of claim 5 , wherein the adjacent element comprises at least one of a link, a node, or a boundary.

8 . The method of claim 1 , wherein the changing of the node-link graph into the skeletal image comprises:
searching for bone mineral density (BMD) of each of the plurality of links of the node-link graph; and representing a thickness of each of trabeculae by using the BMD while representing the trabeculae corresponding to the links, respectively.

9 . The method of claim 8 , wherein the searching for the BMD comprises searching for BMD of a central portion of a mask, while moving, in a direction perpendicular to each link, the mask having a shape identical with a shape of a link element composed of pixels belonging to the link in the inputted skeletal image.

10 . The method of claim 9 , wherein the searching for the BMD comprises:
if pixels adjacent to the link element are present as a plurality of layers, searching for BMD of a current layer; searching for BMD of a next layer while setting the BMD of the current layer when the BMD of the current layer is greater than a predetermined value; and excluding the BMD of the current layer when the BMD of the current layer is equal to or smaller than the predetermined value.

11 . A computer apparatus comprising:
a memory; and a processor connected to the memory and configured to execute at least one instruction stored in the memory, wherein the processor is configured to: represent a node-link graph from a bone microstructure of an input skeletal image, reinforce a connectivity of the bone microstructure in the node-link graph, and change the node-link graph into a skeletal image.

12 . The computing apparatus of claim 11 , wherein the processor is configured to:
represent trabeculae of the bone microstructure as a plurality of links, and represent, as a plurality of nodes, points at which the links are connected and an open end of at least one of the links.

13 . The computing apparatus of claim 12 , wherein the processor is configured to:
obtain a binarization image by performing image binarization on the inputted skeletal image, obtain a centerline image by performing centerline extraction in the binarization image, and represent the links and the nodes based on the centerline image.

14 . The computing apparatus of claim 11 , wherein the processor is configured to reconstruct the skeletal image from the inputted skeletal image reconstructed through an artificial neural network.

15 . The computing apparatus of claim 11 , wherein the processor is configured to adjust, as an adjacent element, a location of an open node in the node-link graph.

16 . The computing apparatus of claim 15 , wherein the adjacent element comprises at least one of a link, a node, or a boundary.

17 . The computing apparatus of claim 11 , wherein the processor is configured to:
search for bone mineral density (BMD) of each of the plurality of links of the node-link graph, and represent a thickness of each of trabeculae by using the BMD while representing the trabeculae corresponding to the links, respectively.

18 . The computing apparatus of claim 17 , wherein the processor is configured to search for BMD of a central portion of a mask, while moving, in a direction perpendicular to each link, the mask having a shape identical with a shape of a link element composed of pixels belonging to the link in the inputted skeletal image.

19 . The computing apparatus of claim 18 , wherein the processor is configured to:
if pixels adjacent to the link element are present as a plurality of layers, search for BMD of a current layer, search for BMD of a next layer while setting the BMD of the current layer when the BMD of the current layer is greater than a predetermined value, and exclude the BMD of the current layer when the BMD of the current layer is equal to or smaller than the predetermined value.

20 . A non-transitory computer-readable recording medium on which one or more programs for executing a method in a computer apparatus are recorded, the method comprising:
representing a node-link graph from a bone microstructure of an input skeletal image; reinforcing a connectivity of the bone microstructure in the node-link graph; and changing the node-link graph into a skeletal image.

Assignees

• Korea Advanced Inst Sci & Tech

Inventors

• Jang Ingwun
• Koh Hyukjin
• Chun Bongju

Classifications

• G06T2211/416

  Exact reconstruction · CPC title

• G06T7/11

  Region-based segmentation · CPC title

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T7/13

  Edge detection · CPC title

• G06T2207/30008

  Bone · CPC title