MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH Creating and Simulating Skeletal Muscle from the Visible Human Data Set Authors: Joseph Teran Eftychios

MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R.

CROUCH

Creating and Simulating Skeletal Muscle from the Visible Human Data Set

Authors:•Joseph Teran• Eftychios Sifakis• Silvia S. Blemker•Victor Ng-Thow-Hing•Cynthia Lau• Ronald Fedkiw

Presented By: Federico Bermudez

21 Mar 2007 1

PROBLEM

• Create anatomically realistic simulations of the human musculoskeletal system.

• Create visually accurate simulations of the interactions between muscles and bones.

• This paper present a method for creating such simulations using the visible human data set.

21 Mar 2007MSIM 842 VISUALIZATION II

INSTRUCTOR: JESSICA R. CROUCH

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MOTIVATION

• Anatomically and visually accurate simulations of the musculoskeletal system are critical in:

• biomechanics• biomedical engineering• surgery simulation• computer graphics



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APPROACH

PRIOR & RELATED WORK• Prior work

– Simple less accurate models encompassing many muscles.– Complex models that only simulate a few number of muscles.– These models are less visually accurate.

• Related work– Seems to be concentrated on the use of the Finite Element Method

(FEM), the Finite Volume Method (FVM), and tetrahedral meshes



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APPROACH

MODEL CREATIONThe Visible Human Data Set

Run by the U.S. National Library Of MedicineConsists of MRI, CT, and anatomical Images

Male data set released in Nov 1994– Joseph Paul Jernigan (38-year-old Texas murderer executed 5 Aug 1993) – cadaver was frozen and cut (1871 axial slices at 1 millimeter intervals)– Photographed and digitized – 15 GB

Female data set released in Nov 1995– 59-year-old Maryland housewife who died from a heart attack– cadaver was frozen and cut (5189 axial slices at 0.33 millimeter intervals)– Photographed and digitized – 40 GB



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APPROACH


Problems with the data set– Male brain slightly swollen by the freezing process– Small blood vessels were collapsed by the freezing process – His inner ear ossicles were lost during preparation

Site: http://www.nlm.nih.gov/research/visible/



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APPROACH




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CT Scan Color Cryosections

Thorax subset

APPROACH




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APPROACH

MODEL CREATIONRepairing Errors



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APPROACH

MODEL CREATIONMeshing Bone and Muscle



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APPROACH

MODEL CREATIONMeshing Bone and Muscle



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APPROACH

MODEL CREATIONTendon and Bone Attachment Designation

assign tendon, bone attachments, and muscle properties to sections of the mesh



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APPROACH

MODEL CREATIONB-Spline Fiber Representation

Use B-spline solids to assign fiber directions to individual tetrahedrons.



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APPROACH

MODEL CREATIONSkeletal Motion

– Contraction of the muscles drives the motion of bones.– In this model, the skeleton drives the motion and contraction of muscles, tendons, and

surrounding tissue.– A realistic model involves intricate knowledge of bones and joints interaction , often

requiring multiple degrees of freedom to describe their movements.– The Obstacle-set Method was used to modeled the paths of the muscles.– Cylinders and spheres were used to compute muscles and bones collisions.



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APPROACH




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APPROACH




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APPROACH

FINITE VOLUME METHOD• FVM more intuitive than the finite element method (FEM)• FVM reduces the stress inside a tetrahedron to a simple multidimensional

force pushing on each face.• The inverting FVM algorithm developed from the FVM facilitates the

simulation of objects that must undergo deformation and return to their original or partial shape.

• Video – 01 & 02 show simulations using the inverting FVM.



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APPROACH

CONSTITUTIVE MODEL FOR MUSCLE• An strain energy function is used to model the

contracting of the muscles.• Model includes only what is necessary to produce

bulk length-based contraction along the muscle fiber direction.

• As we will see on the video, the bulk deformations of the muscles are very subtle.



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APPROACH

EMBEDDING FRAMEWORK• The complete model of the upper limb consist of over 30 muscles

constructed with over 10 million tetrahedra.• A dynamic Free Form Deformation embedding scheme was used to

reduce the computational cost.• The BCC grid size used resulted in a tenfold reduction in the size of the

simulation mesh.• Time step restriction for stability was relaxed by a factor of 25.• These factors enabled the full finite element simulation at rates of 4

minutes per frame on a Xeon 3.06 GHz CPU.• A nonmanifold simulation mesh is obtained by collapsing equivalent

vertices.



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APPROACH

FASCIA AND CONNECTIVE TISSUES• Muscles are enclosed in a network of connective tissue that keep them in

close contact during motion.• Model enforces a state of frictionless contact between the muscles.• In essence the intersection between different muscles is determined and

recalculated each time during motion in order to maintain the muscle tissues in close contact.

• Video – 03 shows the simulation without fascia.



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APPROACH

SIMULATING SKELETAL MUSCLE



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Run videos1. Video – 04 - Frontal View2. Video – 05 - Side View

Evaluation

• The construction of the muscles, tendons, and bones seems to be correct.

• I think the simulation shows the compression and relaxation if the muscles visually accurate.



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Conclusion & Future Work

• The authors successfully created a visually accurate simulation of the interaction of the bones, muscle, and underlying tissue of the human right upper limb.

• Current hardware and algorithm technology still too complex to achieve whole body simulations.

• Create subject-specific models with MRI and CT data.• Morph VHP data set to match specific subject or body type

using anatomical landmarks.



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Questions

• How much more complex would be to simulate the whole body.

• Can this technique be use to simulate the involuntary muscles such the hear heart?

• Can this technique be applied to the design of artificial limbs.



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Documents

MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH Creating and Simulating Skeletal Muscle from the Visible Human Data Set Authors: Joseph Teran Eftychios