# PFEE GE Healthcare: Deep Learning Inpainting

# How to get a volume ?
* Turn around the patient
* X ray acquisition in different angles

# Artifacts
Different types of artefact:
* Motion artifact
* Metal artifact
* Ring artifacts (detector)

# State of the art
* Where
* Correction applied on volumes

# Inpainting
* Fill selected image area
* Requires having the mask of the missing parts

# Methods
## Interpolation 2D

Interpolation algorithm from skimage to create a basline:
* Nearest neighbor
* Linear

## U-NET 2D

# Improvements ?
* Conv2D/3D do not consider the mask
* Losses (MSE/MAE) do not consider the mask

# Partial convolution
* Presented by Nvidia in 2018
* Mask area is much less visible and overall results are improves

## Keras ?


# Loss improvement
* Using a train VGG
* deep learning classifier
* Layers used: 3rd, 6th and 10th

# Data

# Experiments
## Goal
* 2D
* Perfomance machine learning
* Added value

* 3D
* Adding temporal gives best results
* Can we be more memory efficient using patches ?

# Evaluation method
* Quantitative evaluation
* MSE
* MAE
* SSIM
* Structural similarity
* PSNR
* Peak To Signal Noise Ratio
* More quantitative than qualitative
* Quality eval
* Eval by human eye

# Results

## Qualitative 2D

### Ribs reconstruction

## Qualitative 2D+T

## Analysis
* Machine learning can be used for this task
* PConv and VGG loss are the best improvements

# Conclusion
* Implementation of PConv2D and PConv3D
* Promising resultls
* Kickstarted GE exploration and gave them insights on their future work
* Had fun with advance machine learning

# Questions
## Guillaume Tochon
Le papier a ete utilise sur des images de scan ?
> Non sur des images naturelles

Expliquer 'smoothing loss'
> Dilatation verticale et horizontale des resultats

## Elodie Puybareau
Generation des artefacts: probleme avec modele 2D+T, pourquoi blanc alors que modele 2D noir ?
> Les modeles 2D sont aussi blanc sur les images

## Eleves
Exemple d'applications concretes ?
> Application de corrections permet d'avoir des images pouvant etre travaillees pour un medecin

Genration des artefacts aleatoires ?
> Oui pour la position et rotation en 3D mais sinon non, pas de perte de temps a generer de la donnee

Tester avec des formes differentes ?
> Oui avec des coins et des aiguilles

Generer un nombre infini de donnees, probleme de fit ?
> Oui

Interpolation lineaire plus simple ?
> Oui mais beaucoup de stries et n'arrive pas a reconstruire certaines parties

# Retour GE Healthcare
Bonne organisation, bon avancement des projets mais baisse d'activite lors d'examens, groupe autonome