Seoul National University Movement Research Lab.
Seoul National University Bundang Hospital
2013. 4. 6
Jiwon Jeong
Motivation (1/2)
 Find the best surgical plan and minimization of unexpected side effects
 Focus on the surgery which cause transformation of bone geometry
 Care about the complex side effects of single-stage multi-level surgery
Personal Data
(X-Ray)
Automatic
3D Reconstruction
Manual
Simulation
• By person
• Using simulator
• Lower limb bone
(Femur, Tibia)
• 3D mesh model
Find Best Solution
• Variables
Automatic
Simulation
(position, angle,
wedge, etc.)
• By simulator
• Need policy
Movement Research Lab. SNU
Perform
Surgery
1/8
Motivation (2/2)
 What is an important criterion when developing the surgical plan?
 Clinical measurements (neck-shaft angle, femoral version, shaft bowing etc.)
 Lower limb alignment (mechanical axis, anatomical axis, etc.)
[Clinical measurements]
Movement Research Lab. SNU
[Lower limb alignment]
2/8
Approach
 Full Process
 3D reconstruction of lower limb using X-ray images (2 biplanar X-ray images)
 Find the feature points in lower limb using 3D geometry model
 Calculate the parameters which are related with lower limb posture
 Find the best surgical plan (below is an example of FVDO)

Input : patient’s current posture (feature points and parameters pair)
predefined ideal posture (parameters)

Output : wedge angle, cutting position, rotation angle and expected posture

Processing : minimization of error between patient’s posture and ideal posture
Movement Research Lab. SNU
3/8
Process #1
 3D Reconstruction of lower limb using X-ray images
 Input : 2 biplanar X-ray images
 Output : 3D geometry model of femur and tibia
 Development approach

Femur : already done (be sure to check it is working accurately to abnormal bone)

Tibia : development approach is as same as femur reconstruction
[Process of femur reconstruction]
Movement Research Lab. SNU
4/8
Process #2 & #3
 Find the feature points of lower limb using 3D geometry model
 Using vertex level processing, find the feature points
 Calculate the parameters which are related with lower limb posture
 Using the feature points, calculate the axes, planes, and parameters
Parameters
Neck-shaft angle
Femoral version
Hip-knee-ankle angle
Condylar-tibia angle
Mechanical axis deviation
[Lower limb feature points & axes example]
Movement Research Lab. SNU
[Parameters example]
5/8
Process #4 (1/2)
 Find the best surgical plan (in case of FVDO)
 3 variables for surgical plan (wedge angle, rotation angle, cutting position)
 2 rotation transformation by surgery
 Minimization of error between patient’s posture and ideal posture

variables  transformation matrix  feature points processing : 𝑝 = 𝑅𝑝
𝑝 : postoperative feature points set,
𝑝 : preoperative feature points set
𝑅 : Transform matrix by 3 variables

If there are ideal feature points set 𝑝𝑖𝑑
𝑎𝑟𝑔𝑚𝑖𝑛 𝑝𝑖𝑑 − 𝑅𝑝
2
we can find the best values of 3 variables by 𝑅

But, is it possible to find the ideal feature points set?
𝑛𝑜𝑟𝑚𝑎𝑙 𝑟𝑎𝑛𝑔𝑒 𝑜𝑟 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑝𝑎𝑟𝑎𝑚𝑡𝑒𝑟𝑠
ℎ𝑜𝑤?
Movement Research Lab. SNU
𝑖𝑑𝑒𝑎𝑙 𝑓𝑒𝑎𝑡𝑢𝑟𝑒 𝑝𝑜𝑖𝑛𝑡𝑠 𝑠𝑒𝑡
[FVDO]
6/8
Process #4 (2/2)
 Find the best surgical plan (in case of FVDO)
 Approach #1 (naïve and discrete)

Calculate all the feature points set correspond to whole combination of 3 variables

Calculate expected parameters using calculated feature points set

Evaluate the expected parameters with normal range or value of that parameters

Select the combination of 3 variables that result in minimum difference
 Approach #2 (continuous)

Error minimization between the 2 parameters set (postoperative and ideal)
𝑎𝑟𝑔𝑚𝑖𝑛
𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑖𝑑 − 𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑝𝑜
2

Postoperative parameters should be represented by 3 variables

Consider the correlation with parameters and feature points
(some feature points are related with multiple parameters)

Consider the weight factor for each parameters (the order of priority)
Movement Research Lab. SNU
7/8
Action Plan
 Set the feature points and parameters
 Define important parameters for surgical plan or lower limb posture
 Define axes, planes, and points for calculation of parameters
 Formulation
 Tibia reconstruction
 Make a training set for tibia reconstruction
 Check the accuracy of femur reconstruction solution for an abnormal bone
 Develop a tibia reconstruction
Movement Research Lab. SNU
8/8
Crouch Posture 논문 동영상
 주요 스토리라인
구분
Introduction
주요 내용
• Crouch posture 특성을 보여주는 다양한 케이스 소개
• Question & Hypothesis 소개
• Crouch posture 장비 및 착용 영상 (crouch 각도 표시 포함)
Experiment 소개
• Crouch 실험 전반에 대한 소개 (미는 부분, 밀린 거리 측정 부분 설명)
• Crouch 실험 카테고리 소개 (속도/보폭, 방향, posture, crouch)
Experiment 결과 및
분석 방향 소개
• 실험 결과 영상 (촬영 영상 및 이에 대응하는 motion viewer 영상)
• 분석 시 제외한 조건에 대한 설명 (2걸음 이상 밀린 케이스 panic mode)
• Crouch 각도에 따른 통계 분석 결과
• Stride에 따른 통계 분석 결과
통계 분석 결과
• Speed에 따른 통계 분석 결과
• Push timing에 따른 통계 분석 결과
• 통계 분석 결과 Summary
• Further exploration (gait simulation 적용 내용)
추가 진행 사항
Movement Research Lab. SNU
9/8