Score-based diffusion models for accelerated MRI.pptx

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Chung Hyung Jin

Slide for the paper Chung & Ye, "Score-based diffusion models for accelerated MRI"

Health & Medicine

Score-based diffusion models for accelerated MRI
Hyungjin Chung and Jong Chul Ye
Hyungjin Chung

Inverse problems: examples
3 / 45
𝐲
𝐱
• Inpainting
⨀
• Deblurring (Deconvolution)
𝐱 𝐲
∗
• CS-MRI
𝓕
⨀

Inverse problems: examples
4 / 45
• CS-MRI (multi-coil)
https://ajiljalal.github.io/DeepMRI.html

Inverse problems: examples
• Computed tomography
𝐱
𝑹 𝑷
𝑹𝑷𝐲
5 / 45

What we want: sampling from the posterior
𝐱 ∼ 𝑝(𝐱|𝐲)
𝐲 = 𝒜𝐱 + 𝜼
6 / 45

Score-based diffusion models for accelerated MRI
Chung & Ye. MeDIA 2022
7 / 45

Score-based diffusion models for accelerated MRI
• Agnostic to forward model
(sub-sampling pattern)
• Superior performance,
especially high-frequency
detail
8 / 45
Chung & Ye. MeDIA 2022

Score-based diffusion models for accelerated MRI
• Trained on DICOM (magnitude) images
• Able to reconstruct complex-valued image data at inference time
• Even extends to parallel imaging by reconstructing coil-wise
• Very high generalization capacity
9 / 45
Chung & Ye. MeDIA 2022

Score-based diffusion models for accelerated MRI
Trained only on knee images, generalizes to other anatomy & contrast
10 / 45
Chung & Ye. MeDIA 2022

Score-based diffusion models for accelerated MRI
Trained only on knee images, generalizes to other anatomy & contrast
11 / 45
Chung & Ye. MeDIA 2022

Multiple posterior samples - uncertainty
12 / 45
Chung & Ye. MeDIA 2022

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Score-based diffusion models for accelerated MRI.pptx

1. Score-based diffusion models for accelerated MRI Hyungjin Chung and Jong Chul Ye Hyungjin Chung

2. Introduction

3. Inverse problems: examples 3 / 45 𝐲 𝐱 • Inpainting ⨀ • Deblurring (Deconvolution) 𝐱 𝐲 ∗ • CS-MRI 𝓕 ⨀

4. Inverse problems: examples 4 / 45 • CS-MRI (multi-coil) https://ajiljalal.github.io/DeepMRI.html

5. Inverse problems: examples • Computed tomography 𝐱 𝑹 𝑷 𝑹𝑷𝐲 5 / 45

6. What we want: sampling from the posterior 𝐱 ∼ 𝑝(𝐱|𝐲) 𝐲 = 𝒜𝐱 + 𝜼 6 / 45

7. Score-based diffusion models for accelerated MRI Chung & Ye. MeDIA 2022 7 / 45

8. Score-based diffusion models for accelerated MRI • Agnostic to forward model (sub-sampling pattern) • Superior performance, especially high-frequency detail 8 / 45 Chung & Ye. MeDIA 2022

9. Score-based diffusion models for accelerated MRI • Trained on DICOM (magnitude) images • Able to reconstruct complex-valued image data at inference time • Even extends to parallel imaging by reconstructing coil-wise • Very high generalization capacity 9 / 45 Chung & Ye. MeDIA 2022

10. Score-based diffusion models for accelerated MRI Trained only on knee images, generalizes to other anatomy & contrast 10 / 45 Chung & Ye. MeDIA 2022

11. Score-based diffusion models for accelerated MRI Trained only on knee images, generalizes to other anatomy & contrast 11 / 45 Chung & Ye. MeDIA 2022

12. Multiple posterior samples - uncertainty 12 / 45 Chung & Ye. MeDIA 2022

Score-based diffusion models for accelerated MRI.pptx

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