CSI 7109:
Topics in Medical Imaging Analysis

Course Information

Lecture Dates: Wed 14:00 - 16:50

Class Location: A542

Instructor:

• Seong Jae Hwang (seongjae@yonsei.ac.kr) - 공학원 449d

Course Policies

Grading (Tentative)

1. Paper Presentation in English

Presentation

• 20~25 mins (including Q&A)

• Topics: Anything related to medical imaging (CV, ML, NLP,  etc.)

  1. Conference papers or journal papers

  2. Medical papers

  3. Pretty much anything

  4. Not overlapping with last semester's presentation list

Where to find papers

Conferences

1. MICCAI

2. IPMI

3. ISBI

4. MIDL

5. SPIE

6. CVPR 등 CV/ML/AI 학회에서 의료영상 주제 검색 가능

Journals

1. TMI

2. MIA

3. Medical Physics

4. NeuroImage

5. And many others

Papers from previous (non-deep learning) medical imaging seminar

1. Effects of spatial smoothing on fMRI group inferences (Mikl et al., 2008) 

2. An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images. (Coupe et al., 2008) 

3. White Matter Hyperintensity segmentation (Muschelli et al., 2017) 

4. Amyloid burden and neural function in people at risk for Alzheimer's Disease (Johnson et al., 2013) 

5. Cortical thickness analysis in autism with heat kernel smoothing (Chung et al., 2005) 

6. Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging (Kim et al., 2016) 

7. A Network Diffusion Model of DiseaseProgression in Dementia (Raj et al., 2012) 

8. A survey on deep learning in medical image analysis (Litjens et al., 2017) 

9. Generating Patient-like Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks (Chen et al., 2019) 

10. Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer’s Disease (Parisot et al., 2018) 

11. BrainNetCNN: Convolutional Neural Networks for Brain Networks; Towards Predicting Neurodevelopment (Kawaharaa et al., 2017) 

12. Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks (Ktena et al., 2017) 

13. Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks (Dvornek et al., 2017) 

14. Brain decoding from functional MRI using long short-term memory recurrent neural networks (Li et al.) 

15. Transfusion: Understanding Transfer Learning for Medical Imaging (Raghu et al., 2019) 

16. Domain adaptation for Alzheimer's disease diagnostics (Wachinger et al., 2016) 

17. Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation (Ghafoorian et al., 2017) 

18. Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation (Jungo et al., 2018)