# US 12,182,956 B2 · Systems and methods of using three-dimensional image reconstruction to aid in assessing bone or soft tissue aberrations for orthopedic surgery

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- Number: US 12,182,956 B2
- Document ID: US12182956B2
- Status: Granted
- Kind: B2
- Application number: 17/835,894
- Filed: 2022-06-08
- Published: 2023-01-05
- Granted: 2024-12-31
- Earliest claimed: 2021-07-01
- Assignees: MicroPort Orthopedics Holdings Inc.
- Applicants: MicroPort Orthopedics Holdings Inc.
- Inventors: Brian R. Harris, Jr.
- Web page: https://patentgrep.com/patent/US12182956B2

## CPC

- G06T 19/20: Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts
- A61B 6/466: {adapted to display 3D data}
- A61B 6/505: {for diagnosis of bone}
- A61B 6/582: {Calibration}
- A61B 34/10: Computer-aided planning, simulation or modelling of surgical operations
- B29C 64/386: Data acquisition or data processing for additive manufacturing
- B33Y 50/00: Data acquisition or data processing for additive manufacturing
- G06F 3/011: {Arrangements for interaction with the human body, e.g. for user immersion in virtual reality (blind teaching G09B21/00)}
- G06N 3/0464: Convolutional networks [CNN, ConvNet]
- G06T 7/0014: {using an image reference approach}
- G16H 30/40: for processing medical images, e.g. editing
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/50: for simulation or modelling of medical disorders
- A61B 17/155: {Cutting femur}
- A61B 2034/105: {Modelling of the patient, e.g. for ligaments or bones}
- A61B 2034/107: {Visualisation of planned trajectories or target regions}
- A61B 2034/2048: {using an accelerometer or inertia sensor}
- A61B 2090/365: {augmented reality, i.e. correlating a live optical image with another image}
- A61B 2090/367: {creating a 3D dataset from 2D images using position information}
- A61B 2090/376: {using X-rays, e.g. fluoroscopy}
- B29K 2077/00: Use of {PA, i.e.} polyamides, e.g. polyesteramides {or derivatives thereof}, as moulding material
- B29L 2031/40: Test specimens {; Models, e.g. model cars (mannequins B29L2031/7028); Probes}
- B33Y 80/00: Products made by additive manufacturing
- G06N 3/045: Combinations of networks
- G06N 3/0475: Generative networks
- G06N 3/048: Activation functions
- G06N 3/094: Adversarial learning
- G06N 3/096: Transfer learning
- G06T 2207/10116: X-ray image
- G06T 2207/20084: Artificial neural networks [ANN]
- G06T 2207/30008: Bone
- G06T 2210/44: Morphing
- G06T 2219/2021: Shape modification
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- B29C: SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING (making preforms B29B11/00; making laminated products by combining previously unconnected layers which become one product whose layers will remain together B32B37/00 - B32B41/00)
- B33Y: ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- B29K: INDEXING SCHEME ASSOCIATED WITH SUBCLASSES B29B, B29C OR B29D, RELATING TO MOULDING MATERIALS OR TO MATERIALS FOR {MOULDS, } REINFORCEMENTS, FILLERS OR PREFORMED PARTS, e.g. INSERTS
- B29L: INDEXING SCHEME ASSOCIATED WITH SUBCLASS B29C, RELATING TO PARTICULAR ARTICLES

## Abstract

Systems and methods for calculating external bone loss for alignment of pre-diseased joints comprising: generating a three-dimensional (“3D”) computer model of an operative area from at least two two-dimensional (“2D”) radiographic images, wherein at least a first radiographic image is captured at a first position, and wherein at least a second radiographic image is captured at a second position, and wherein the first position is different than the second position; identifying an area of bone loss on the 3D computer model; and applying a surface adjustment algorithm to calculate an external missing bone surface fitting the area of bone loss.

## Claims

### Claim 1

A product comprising a physical 3D model of a bone aberration produced by a process comprising:
calibrating a radiographic imaging machine to determine a mapping relationship between radiographic image points and corresponding space coordinates to define spatial data;
using a radiographic imaging technique to capture a first radiographic image of a subject orthopedic element, wherein the first radiographic image defines a first reference frame;
using the radiographic imaging technique to capture a second radiographic image of the subject orthopedic element, wherein the second radiographic image defines a second reference frame, and wherein the first reference frame is offset from the second reference frame at an offset angle;
projecting spatial data from the first radiographic image of the subject orthopedic element and spatial data from the second radiographic image of the subject orthopedic element to define volume data;
using a deep learning network to detect the subject orthopedic element using the volume data, the volume data defining an anatomical landmark on or in the subject orthopedic element;
using the deep learning network to detect a bone aberration on or in the subject orthopedic element using the volume data;
applying the deep learning network to the volume data to generate the 3D model of the bone aberration; and
using a manufacturing technique to produce a physical 3D model of the bone aberration.

### Claim 2 (depends on 1)

The product of claim 1, wherein the physical 3D model of the bone aberration comprises a mating surface that mates with the exposed surface of worn bone.

### Claim 3 (depends on 1)

The product of claim 1, wherein the physical 3D model of the bone aberration comprises a mating surface, and wherein the mating surface further comprises a projection.

### Claim 4

A product comprising a physical 3D model of a bone aberration produced by a process comprising:
calibrating a radiographic imaging machine to determine a mapping relationship between radiographic image points and corresponding space coordinates to define spatial data;
using a radiographic imaging technique to capture a first radiographic image of a subject orthopedic element, wherein the first radiographic image defines a first reference frame;
using the radiographic imaging technique to capture a second radiographic image of the subject orthopedic element, wherein the second radiographic image defines a second reference frame, and wherein the first reference frame is offset from the second reference frame at an offset angle;
projecting spatial data from the first radiographic image of the subject orthopedic element and spatial data from the second radiographic image of the subject orthopedic element;
using a deep learning network to detect the subject orthopedic element using the spatial data, the spatial data defining an anatomical landmark on or in the subject orthopedic element;
using the deep learning network to detect a bone aberration on or in the subject orthopedic element using the spatial data;
applying the deep learning network to the spatial data to generate the 3D model of the bone aberration; and
using a manufacturing technique to produce a physical 3D model of the bone aberration.

### Claim 5 (depends on 4)

The product of claim 4, wherein the physical 3D model of the bone aberration comprises a mating surface that mates with the exposed surface of worn bone.

### Claim 6 (depends on 4)

The product of claim 4, wherein the physical 3D model of the bone aberration comprises a mating surface, and wherein the mating surface further comprises a projection.

### Claim 7 (depends on 1)

The product of claim 1, wherein the manufacturing technique is an additive manufacturing technique and wherein the physical 3D model of the bone aberration is an inverse volume of a negative bone aberration.

### Claim 8 (depends on 1)

The product of claim 1, wherein the physical 3D model of the bone aberration comprises a medical grade polyamide.

### Claim 9 (depends on 1)

The product of claim 1, wherein the process further comprises applying a surface adjustment algorithm to the 3D model of the bone aberration, wherein the surface adjustment algorithm is configured to estimate a topography of a bone surface to correct the bone aberration.

### Claim 10 (depends on 9)

The product of claim 9, wherein the surface adjustment algorithm is a curve-fitting algorithm.

### Claim 11 (depends on 1)

The product of claim 1, wherein the process further comprises displaying a virtual 3D model of the bone on a display.

### Claim 12 (depends on 11)

The product of claim 11, wherein the display is an augmented reality device or a virtual reality device.

### Claim 13 (depends on 4)

The product of claim 4, wherein the manufacturing technique is an additive manufacturing technique and wherein the physical 3D model of the bone aberration is an inverse volume of a negative bone aberration.

### Claim 14 (depends on 4)

The product of claim 4, wherein the physical 3D model of the bone aberration comprises a medical grade polyamide.

### Claim 15 (depends on 4)

The product of claim 4, wherein the process further comprises applying a surface adjustment algorithm to the 3D model of the bone aberration, wherein the surface adjustment algorithm is configured to estimate a topography of a bone surface to correct the bone aberration.

### Claim 16 (depends on 15)

The product of claim 15, wherein the surface adjustment algorithm is a curve-fitting algorithm.

### Claim 17 (depends on 4)

The product of claim 4, wherein the process further comprises displaying a virtual 3D model of the bone on a display.

### Claim 18 (depends on 17)

The product of claim 17, wherein the display is an augmented reality device or a virtual reality device.