Mark S. Graham

Orcid: 0000-0002-4170-1095

According to our database1, Mark S. Graham authored at least 22 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Latent Transformer Models for out-of-distribution detection.
Medical Image Anal., December, 2023

Generative AI for Medical Imaging: extending the MONAI Framework.
CoRR, 2023

Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

A 3D Generative Model of Pathological Multi-modal MR Images and Segmentations.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

Self-Supervised Anomaly Detection from Anomalous Training Data via Iterative Latent Token Masking.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Denoising diffusion models for out-of-distribution detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Transformer-based out-of-distribution detection for clinically safe segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Morphology-Preserving Autoregressive 3D Generative Modelling of the Brain.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2022

Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Correction of Susceptibility Distortion in EPI: A Semi-supervised Approach with Deep Learning.
Proceedings of the Computational Diffusion MRI - 13th International Workshop, 2022

Can Segmentation Models Be Trained with Fully Synthetically Generated Data?
Proceedings of the Simulation and Synthesis in Medical Imaging, 2022

2020
Accessible Data Curation and Analytics for International-Scale Citizen Science Datasets.
CoRR, 2020

Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE.
CoRR, 2020

Test-Time Unsupervised Domain Adaptation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Hierarchical Brain Parcellation with Uncertainty.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020

2019
Disease classification of macular Optical Coherence Tomography scans using deep learning software: validation on independent, multi-centre data.
CoRR, 2019

2018
A supervised learning approach for diffusion MRI quality control with minimal training data.
NeuroImage, 2018

Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data.
NeuroImage, 2018

2017
Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement.
NeuroImage, 2017

2016
Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques.
NeuroImage, 2016

Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images.
NeuroImage, 2016

2015
A Simulation Framework for Quantitative Validation of Artefact Correction in Diffusion MRI.
Proceedings of the Information Processing in Medical Imaging, 2015


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