This document provides an overview of research topics in artificial intelligence and deep learning for medical image analysis and radiation treatment. It first introduces artificial intelligence and deep learning, including how artificial neural networks use deep learning to perform tasks by learning from large amounts of data. It then discusses specific deep learning techniques like convolutional neural networks. The document concludes by describing several of the author's research topics, including using deep learning for chest X-ray analysis, low-dose CT reconstruction, segmentation of organs from CT and MR images for radiation treatment planning, and isotope identification from gamma-ray spectra.

1. Radiological Physics Lab
Seoul National University
Jimin Lee

2. Contents
2
1. Artificial Intelligence & Deep Learning
2. Research Topics

3. Artificial Intelligence
& Deep Learning
3

4. Artificial Intelligence
4
1.
http://smartfutures.net/02/seeding-the-ai-in-your-life/
https://www.paysa.com/blog/2018/02/01/how-ai-is-revolutionizing-medical-diagnosis/

5. Artificial Intelligence
 To develop a model to do a specific task by learning from big data
5
1.
https://adgefficiency.com

6. Artificial Intelligence
6
1.
https://medium.com/aws-activate-startup-blog/adapting-deep-learning-to-medicine-with-behold-ai-e60c37eb966a
?
 To develop a model to do a specific task by learning from big data

7. Deep Learning
 Artificial Intelligence, Machine Learning and Deep Learning
7
1.
https://www.gettingsmart.com/2017/03/the-technologies-reshaping-life-and-livelihood/

8. Deep Learning
 Artificial Neural Networks (인공 신경망)
8
1.
cs231n: Convolutional Neural Networks for Visual Recognition
The number of hidden layers
= Depth of the network
How can we learn the optimal 𝝎𝒊,𝒋,𝒌?

9. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
9
1.

10. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
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11. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
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1.

12. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
12
1.

13. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
13
1.

14. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
14
1.

15. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
15
1.

16. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
16
1.

17. Deep Learning
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1.

18. Deep Learning
18
1.

19. Deep Learning
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1.

20. Deep Learning
20
1.

21. Deep Learning
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22. Deep Learning
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1.

23. Deep Learning
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1.

24. Deep Learning
24
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25. Deep Learning
 Artificial Neural Networks (인공 신경망) learning process
25
1.
https://theclevermachine.wordpress.com/tag/backpropagation , http://sebastianraschka.com/Articles/2015_singlelayer_neurons.html

26. Deep Learning
 Artificial Neural Networks (인공 신경망) = “Deep” Learning
26
1.

27. Deep Learning
 Convolutional Neural Networks (CNN)
27
1.
cs231n: Convolutional Neural Networks for Visual Recognition

28. Deep Learning
 Convolutional Neural Networks (CNN)
28
1.
cs231n: Convolutional Neural Networks for Visual Recognition

29. Deep Learning
 Convolutional Neural Networks (CNN)
29
1.
cs231n: Convolutional Neural Networks for Visual Recognition

30. Deep Learning
 Convolutional Neural Networks (CNN)
30
1.
cs231n: Convolutional Neural Networks for Visual Recognition

31. Deep Learning
 Convolutional Neural Networks (CNN)
31
1.
cs231n: Convolutional Neural Networks for Visual Recognition

32. Deep Learning
 Vision
32
적용 분야
1.
cs231n: Convolutional Neural Networks for Visual Recognition

33. Deep Learning
 Autonomous driving (자율 주행)
33
1.
https://www.youtube.com/watch?v=HbPhvct5kvs

34. Deep Learning
 Neural Style Transfer
34
1.
Leon, et al. Image Style Transfer Using Convolutional Neural Networks

35. Deep Learning
 Natural language processing (자연어 처리)
• Translation
• Chat bot
• Caption generation
• Document summarization
• Voice synthesis
 http://tv.naver.com/v/2292650 (35:00 ~ )
 https://carpedm20.github.io/tacotron/en.html
35
1.

36. Research Topics
36

37. Research Topics
 Chest X-ray
• Lunit Insight : https://www.youtube.com/watch?v=ZkWBVyNuE3A (1:20 - )
• Diagnosis of major lung diseases (식약처 의료기기 허가)
37
Medical Images
2.
기흉 폐결핵 폐암
https://insight.lunit.io/#examples

38. Research Topics
 X-ray
• VUNO-MED BoneAge
• Software for measuring age of bones (식약처 의료기기 허가)
38
Medical Images
2.
https://www.youtube.com/watch?v=cI9nCVL40LM

39. Research Topics
 Low-Dose CT
39
Medical Images
2.
Kang, et al. A Deep Convolutional Neural Network using Directional Wavelets for Low-dose X-ray CT Reconstruction

40. Research Topics
 Low-Dose CT
40
Medical Images
2.
Kang, et al. A Deep Convolutional Neural Network using Directional Wavelets for Low-dose X-ray CT Reconstruction

41. Research Topics
 Low-Dose CT
41
Medical Images
2.
Kang, et al. A Deep Convolutional Neural Network using Directional Wavelets for Low-dose X-ray CT Reconstruction

42. Research Topics
 CT
• Liver and liver tumor segmentation
42
Medical Images
2.
Li, et al. H-DenseUNet: Hybrid densely connected UNet for liver and liver tumor segmentation from CT volumes

43. Research Topics
 CT
• Liver and liver tumor segmentation
43
Medical Images
2.
Li, et al. H-DenseUNet: Hybrid densely connected UNet for liver and liver tumor segmentation from CT volumes

44. Research Topics
 CT
• Liver and liver tumor segmentation
44
Medical Images
2.
Li, et al. H-DenseUNet: Hybrid densely connected UNet for liver and liver tumor segmentation from CT volumes

45. Research Topics
 CT
• Liver and liver tumor segmentation
45
Medical Images
2.
Li, et al. H-DenseUNet: Hybrid densely connected UNet for liver and liver tumor segmentation from CT volumes
𝐷𝑆𝐶 𝐴, 𝐵 =
2 × |𝐴 ∩ 𝐵|
𝐴 + |𝐵|

46. Research Topics
 Segmentation of the prostate and OAR in CT
46
Radiation Treatment
2.
Samaneh, et al. Segmentation of the prostate and organs at risk in male pelvic CT images using deep learning
bladder
prostate
rectum

47. Research Topics
 Segmentation of the prostate and OAR in CT
• Prostate segmentation results
47
Radiation Treatment
2.
Samaneh, et al. Segmentation of the prostate and organs at risk in male pelvic CT images using deep learning

48. Research Topics
 Segmentation of the prostate and OAR in CT
• Bladder, rectum segmentation results
48
Radiation Treatment
2.
Samaneh, et al. Segmentation of the prostate and organs at risk in male pelvic CT images using deep learning

49. Research Topics
 MR-only Radiotherapy (MR-LINAC)
49
Radiation Treatment
2.
https://avaloninnovation.com/en/mr-linac-en

50. Research Topics
 MR-only Radiotherapy (MR-LINAC)
• Pseudo CT generation from MR images
50
Radiation Treatment
2.
Matteo, et al. Fast synthetic CT generation with deep learning for general pelvis MR-only Radiotherapy

51. Research Topics
 MR-only Radiotherapy (MR-LINAC)
• Difference of dose calculation results from real CT and pseudo CT : -3 ~ 3 %
51
Radiation Treatment
2.
Matteo, et al. Fast synthetic CT generation with deep learning for general pelvis MR-only Radiotherapy

52. Research Topics
 Isotope identification
• Input : Gamma-ray spectra (Contains up to 5 random isotopes among 33 isotopes in total)
• Target : Relative count contributions from each radioisotope
52
Radiation Detection
2.
M. Kamuda, et al. Automated Isotope Identification Algorithm Using Artificial Neural Networks

53. Q & A
53

54. Thank you.
54