Methods and systems for producing an implant

• US 9,672,617 B2
• Filed: 03/17/2016
• Issued: 06/06/2017
• Est. Priority Date: 08/11/1999
• Status: Expired due to Fees

• Current Assignee: Osteoplastics, LLC
• Original Assignee: Osteoplastics, LLC
• Inventors: Subramanyan, Krishnamoorthy, MOULLAS, ALEXANDROS T., Ratcheson, Robert A., DEAN, H. DAVID
• Primary Examiner(s): LAURITZEN, AMANDA L
• Application Number:
  US15/072,607
• Publication Number:
  US 20160196651A1
• Time in Patent Office: 446 Days
• CPC Class Codes: A61B 2576/00 Medical imaging apparatus involving image processing or analysis A61B1/00009, A61B6/52 and A61B8/52 take precedence; image processing per se G06T; details of algorithms for analysing medical images G06T7/0012
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/1075 for measuring dimensions by non-invasive methods, e.g. for determining thickness of tissue layer A61B8/0858 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 6/03 Computed tomography [CT] echo-tomography A61B8/14
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/501 for diagnosis of the head, e.g. neuroimaging or craniography
• CPC Class Codes: A61B 6/505 for diagnosis of bone
• CPC Class Codes: A61F 2/28 Bones joints A61F2/30
• CPC Class Codes: A61F 2/2875 Skull or cranium A61F2/2803 and A61F2/3099 take precedence
• CPC Class Codes: A61F 2/30942 for designing or making customized prostheses, e.g. using templates, CT or NMR scans, finite-element analysis or CAD-CAM techniques
• CPC Class Codes: A61F 2002/2835 Bone graft implants for filling a bony defect or an endoprosthesis cavity, e.g. by synthetic material or biological material
• CPC Class Codes: A61F 2002/30943 using mathematical models
• CPC Class Codes: B33Y 50/00 Data acquisition or data processing for additive manufacturing
• CPC Class Codes: B33Y 80/00 Products made by additive manufacturing
• CPC Class Codes: G06F 18/2137 based on criteria of topology preservation, e.g. multidimensional scaling or self-organising maps
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 15/08 Volume rendering
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 : Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/20084 : Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30008 : Bone
• CPC Class Codes: G06T 2207/30016 : Brain
• CPC Class Codes: G06T 2207/30052 : Implant; Prosthesis
• CPC Class Codes: G06T 2207/30108 : Industrial image inspection
• CPC Class Codes: G06T 2207/30201 : Face
• CPC Class Codes: G06T 2210/41 : Medical
• CPC Class Codes: G06T 7/00 : Image analysis
• CPC Class Codes: G06T 7/0002 : Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/001 : using an image reference approach
• CPC Class Codes: G06T 7/0012 : Biomedical image inspection
• CPC Class Codes: G06T 7/0014 : using an image reference approach
• CPC Class Codes: G06T 7/10 : Segmentation; Edge detection motion-based segmentation G06T7/215
• CPC Class Codes: G06T 7/11 : Region-based segmentation
• CPC Class Codes: G06T 7/143 : involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/174 : involving the use of two or more images
• CPC Class Codes: G06T 7/50 : Depth or shape recovery
• CPC Class Codes: G06T 7/564 : from contours
• CPC Class Codes: G06T 7/68 : of symmetry
• CPC Class Codes: G06V 2201/03 : Recognition of patterns in medical or anatomical images
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/20 : for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 : for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: Y10S 128/922 : including image analysis
• CPC Class Codes: Y10S 623/914 : Bone

Abstract

A computer implemented method for determining the 3-dimensional shape of an implant to be implanted into a subject includes obtaining a computer readable image including a defective portion and a non-defective portion of tissue in the subject, superimposing on the image a shape to span the defective portion, and determining the 3-dimensional shape of the implant based on the shape that spans the defective portion.

Claims

1. A computer implemented method of obtaining data for determining a three-dimensional shape of a medical device, the method comprising:

rendering a computer-generated three-dimensional representation of a target tissue from computer readable image data of the target tissue wherein the target tissue comprises two portions, a portion with a defect and a portion without a defect;

mapping an external three-dimensional surface of the computer-generated three-dimensional representation of the target tissue;

superimposing onto the mapped external surface a three-dimensional template to span the defective portion by deforming the three-dimensional template to match at least a portion of the mapped external surface; and

determining the three-dimensional shape of the medical device based on the shape of the deformed three-dimensional template that spans the defective region.

2. The method of claim 1, further comprising registering data from the mapped external surface of the non-defective portion of the target tissue to normative data for the target tissue prior to superimposing the template on the mapped external surface.

3. The method as set forth in claim 1, wherein the three-dimensional image data is obtained from image slices of the target tissue.

4. The method as set forth in claim 1, wherein the three-dimensional image data is obtained as one or more voxels of the target tissue.

5. The method of claim 1, wherein the medical device is an implant to be implanted in a subject.

6. The method of claim 1, further comprising fabricating the 3-dimensional shape of the medical device.

7. The method of claim 1, further comprising generating the computer-readable image data of the target tissue.

8. The method of claim 7, further comprising fabricating the 3-dimensional shape of the medical device.