Research Assistant - Digital Therapy, Data Analytics & Mobile Computing - CSS Health Lab.

Applicant: Chen-Hsuan (Iris), Shih 

Iris Shih 

iris.cshih@gmail.com

Iris Shih 

iris.cshih@gmail.com

About Me

Iris Shih

 M.S Computer Science at Technical University of Munich

Enjoy doing research in Healthcare field

From Taiwan

Love to go hiking and do sports

Where I obtained my bachelor degree in computer science.

Gain knowledge, Practical projects, Organizing events and started to get interest in research.

Master thesis on the topic of improving current device navigation system for diagnosis.

Besides school work, go hiking or play squash with friends are the best!

Iris Shih 

iris.cshih@gmail.com

About Me

Education 

Iris Shih

2012 - 2015

2008 - 2012

 B.S Computer Science

Major in Business Informatics

Tamkang University, Taipei, Taiwan

 M.S Computer Science

Major in Computer Vision (Biomedical Computing)

Technical University of Munich, Munich, Germany

Iris Shih 

iris.cshih@gmail.com

About Me

Projects

Iris Shih

Student Software Developer

Adesso Profile & Game App.

An IOS mobile app. for the consultant company - Adesso.

Master Thesis

Inside-Out Tracking for Medical Application 

Using a single optical camera to improve current  device navigation system.

IDP Project

Analyzation Toolkit for 3D Lookup Tables

An UI application for analyzing gamma camera acquisition.

Independent Project

BioJavaScript 2.0.

An open-source JS library for visualizing biological data.

Iris Shih 

iris.cshih@gmail.com

About Me

Outside University

Iris Shih

Co-Founder

Co-Organizer

Deep Learning Meetup Munich

ACM Munich Student Club

 Founding chair of ACM Student chapter in Munich.

 Organizing regular meetups to discuss about machine learning/deep learning.

President

TKU Student Council

Leader of the Department of Innovative Information and Technology council. 

Iris Shih 

iris.cshih@gmail.com

About Me

Some Interests

Iris Shih

Language

CS Skills

C++, JavaScript, Matlab

Learning German

... still in action! Currently A1.2 level!

Love Github and Sublime

Sports

Basketball, Badminton, Squash, ...

Basically I love all kinds of sports! 

Iris Shih 

iris.cshih@gmail.com

 @ TUM

Research Project 

Marker-based Inside-out Tracking for Medical Applications
Using a Single Optical Camera 

Student: Chen-Hsuan, Shih (Iris)

Supervisor: Prof. Dr. Nassir Navab

Master of Biomedical Computing
Computer Aided Medical Procedure(CAMP),
Technical University of Munich, Germany

Advisor: Philipp Matthies

Motivation

Motivation

Outside-in Tracking

2

doctor

patient

nurse

line of sight problem ! -> Miss Tracking

Motivation

3

doctor

patient

doctor

patient

nurse

Motivation

4

Inside-out Tracking

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion 

  • Future Works 

Road Map

5

Road Map

6

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion 

  • Future Works 

State of the art tracking technology

Inside-out Tracking

Similar application for solving line-of-sight

State-of-the-Art: Marker-Based Tracking 

Really Robustness in Occlusion ,Wrapping , Lens Distorsion 

[1]Olson, E., AprilTag: A robust and flexible visual fiducial system, ICRA, 2011

[2] S. Garrido-Jurado, Automatic generation and detection of highly reliable fiducial markers under occlusion, Pattern Recognition, 2014

7

AprilTags [1]

ArUco [2]

Inside-out Tracking Application 

8

ClearGuide [4]

Panorama ultrasound for

[4]Clear Guide Medical. http://clearguidemedical.com/ (accessed 3/6/2015).

[3] Hedyeh Rafii-Tari. Panorama ultrasound for guiding epidural anesthesia: a feasibility study. IPCAI’11 2011

guiding epidural anesthesia [3]

Marker-based tracking setup

Extract information from tracking

Multi-marker tracking model

Get the detector transformation matrix

Complete transformation for reconstruction

Road Map

9

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion 

  • Future Works 

Technical Setup

GoPro Camera

Calibrator 

3D Marker Cube

10

(Reference Target)

Gamma Camera

Marker-Based Tracking

Gamma Camera

Tracking System

?

Calibrator 

patient

Image reconstruction

11

 Cube Target

Tracking Transformation T1
camera --> marker cube  

GoPro Camera

Gamma Camera

12

Tracking System

 Cube Target

Tracking Transformation T2
camera --> calibrator  

GoPro Camera

13

Tracking System

T1

 Cube Target

Tracking Transformation T3  calibrator --> Detector   

GoPro Camera

Gamma Camera

Tracking Transformation T3  calibrator --> Detector   

T2

14

Tracking System

T1

 Cube Target

GoPro Camera

Gamma Camera

T

T1

T2

T3   x

T1

T2  x

Ttarget = 

14

Tracking System

detector

-1

-1

 Cube Target

GoPro Camera

Gamma Camera

T

T1

T2

 Cube Target

15

Tracking System

-1

patient

Volume of interest

Ttarget

detector

GoPro Camera

Gamma Camera

T

T1

T2

T

 Cube Target

16

Tracking System

-1

patient

Volume of interest 

-1

Tdetector 

voi

Multi-Marker Model + ArUco Tracking Framework

(voi)

Normal 2D Marker Tracking - Individual Coordinate

17

Tracking Model

Applied Multi-Marker Model

18

Tracking Model

s = 1/2 marker size

c = 1/2 cube size

Translation Extracted from Tracking Alg. with 3D Multi-Marker Model

19

3 markers were tracked:

red: #marker 1

green: #maker 2

blue: #marker 3

Tracking Model

20

Marker-Based Tracking

Calibrated Camera 

Reference Points

(Intrinsic parameters)

Tcamera (Extrinsic parameters) :

Mean of all detected transformations (single markers)

Tcamera

target

target

ArUco

20

Marker-Based Tracking - ArUco

Input Image

Camera Captured

1

20

Marker-Based Tracking - ArUco

Input Image

Camera Captured

1

2

Gray-Scale Image

Image Segmentation 

20

Marker-Based Tracking - ArUco

Input Image

Camera Captured

1

2

Gray-Scale Image

Image Segmentation 

3

Contour extraction

20

Marker-Based Tracking - ArUco

Input Image

Camera Captured

1

2

3

Contour extraction

Filter Polygon

4

4-vertex Polygon

Gray-Scale Image

Image Segmentation 

20

Marker-Based Tracking - ArUco

Input Image

Camera Captured

1

2

3

Contour extraction

Filter Polygon

4

4-vertex Polygon

Gray-Scale Image

Image Segmentation 

5

Marker Identification

Perspective Reprojection

Binarized Image :

0: black, 1: white

Road Map

21

Inside-out Tracking & Outside-in Tracking   

Reconstruction Tool

AR Visualization

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion

  • Future Works 

Multi-Tracker-App.

22

Threshold Setting

Reconstruction Tool

GammaProbe Acquisition

Augmented Reality Visualization

1

3

2

Switch View

Multi-Tracker-App.

23

Threshold Setting

Reconstruction Tool

GammaProbe Acquisition

Augmented Reality Visualization

1

3

2

Road Map

24

Lymph node phantom 

Thyroid phantom

Breast cancer patient scan

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion

  • Future Works 

System Setup - Breast lymph node phantom scan 

25

Inside-out Tracking

Outside-in Tracking (NDI Tracker)

System Setup - Breast lymph node phantom scan 

25

Two hollow spheres in a water-bath:

  • volumes of 3:5ml & 0:6ml each

  • filled with a 3MBq solution of 99mTc

System Setup - Thyroid phantom scan 

26

Inside-out Tracking

Outside-in Tracking (NDI Tracker)

System Setup - Thyroid phantom scan 

26

  • simulate hot or cold nodules

Custom-printed thyroid phantom :

  • contains 4 chambers of different sizes

  • filled with radioactivity or water

Inside-out Workflow

27

Multi-Tracker-App.

28

  1. System Setup

  2. Gamma camera start acquisition

  3. Switching view to make sure the tracking validation

Multi-Tracker-App.

28

  1. System Setup

  2. Gamma camera start acquisition

  3. Switching view to make sure the tracking validation

  4. Stop acquisition

  5. Choose inside-out tracker info. for reconstruction 

  6. Thresholding the visualization  

 

29

Road Map

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion 

  • Future Works 

Inside-out Tracking  vs. Outside-in Tracking 

Reconstruction  & AR

22

Video!!!!!

Phantom Experiment Result

30

Real distance: 5.5cm

Real distance: 3.3cm

Real distance: 5.5cm

Real distance: 3.3cm

Phantom Experiment Result

30

 Mean                                       5.45            5.75

 Mean                                3.22            3.26

Patient Experiment Result

31

32

Tracking Accuracy

ArUco (Guppy) vs. Outside-in (NDI)

Distance between two sets of tracking points

Marker cube limitation

33

Multi-Marker Model Accuracy

34

35

Road Map

  • State-of-The-Art

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Results & Evaluation

  • Discussion 

  • Future Works 

Inside-out Tracking  vs. Outside-in Tracking 

Reconstruction  & AR

Discussion

Reduced Line-of-sight issue ! 

Reference target (marker cube) can be easily positioned & tracked!

Simple, Easy, Low cost system setup with comparable accuracy!

Patient & surgeon friendly

36

Discussion

How to deal: operator's handshake that leads to bad tracking?

What are the constrains for the reference target? Is it necessary?

Can the system auto-detect the error if happened during real scan?

Is the system reliably applicable in real clinical practice?

37

38

Road Map

  • Literature research

  • Tracking System

  • Multi-Tracker-App.

  • Experiment

  • Evaluation & Results 

  • Future Works 

Tracking Accuracy & Stabilization 

Mechanical Tracking as ground truth 

Next Steps...

Marker-based Tracking:

  • Tracking Algorithm

    • Accuracy assurance & Standard deviation

    • Discard outliers : Error threshold

    • Compare to ground truth. (e.g. Mechanical tracking)

39

Next Steps...

Marker-based Tracking:

  • Tracking Algorithm

    • Accuracy assurance & Standard deviation

    • Discard outliers : Error threshold

    • Compare to ground truth. (e.g. Mechanical tracking)

  • Reference Marker Design

    • ​Size & Positioning 

    • Cube vs. Plane 

40

Next Steps...

Reference Marker Design : Cube vs. Plane 

41

Next Steps...

Inside-out Tracking System:

  • Hardware setup

    • Dedicated combined optical-/gamma-camera

    • Custom printed the marker cube

    • Dedicated holder for marker cube  

  • Clinical workflow

    • ​Address clinical integration issue

42

Next Steps...

Inside-out Tracking System:

  • Decomposed Transformation vs. Projection Matrix

  • Motion Tracking  without Markers: 

    • Project Tango from Google

    • Direct SLAM for RGB-D Cameras

43

Thank You for Your Attention! 

Thank you Philipp & Thank you Prof. Navab

Thanks for a lot of people who support this project!

Iris Shih 

iris.cshih@gmail.com

So much we can do by knowing and applying 
the correct Technology!

Iris Shih 

iris.cshih@gmail.com

Why I'm here...

Computer Science 

Healthcare Problem 

Iris Shih 

iris.cshih@gmail.com

Why I'm here...

Computer Science 

Healthcare Problem 

  • Diagnosis Improvement

  • Treatment Improvement 

  • Earlier Diseases Detection/Prediction

  • more

"Change Health Behavior through Technology", Health-IS

Iris Shih 

iris.cshih@gmail.com

Thank you

Presentation @ ETH

By iriscshih

Presentation @ ETH

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