Matthew Baugh

According to our database, Matthew Baugh authored at least 16 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

JVID: Joint Video-Image Diffusion for Visual-Quality and Temporal-Consistency in Video Generation.

Hadrien Reynaud, Matthew Baugh, Mischa Dombrowski, Sarah Cechnicka, Qingjie Meng, Bernhard Kainz

CoRR, 2024

Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection.

Sergio Naval Marimont, Vasilis Siomos, Matthew Baugh, Christos Tzelepis, Bernhard Kainz, Giacomo Tarroni

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis.

Liu Li, Hanchun Wang, Matthew Baugh, Qiang Ma, Weitong Zhang, Cheng Ouyang, Daniel Rueckert, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

URCDM: Ultra-Resolution Image Synthesis in Histopathology.

Sarah Cechnicka, James Ball, Matthew Baugh, Hadrien Reynaud, Naomi Simmonds, Andrew P. T. Smith, Catherine Horsfield, Candice Roufosse, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Image-Conditioned Diffusion Models for Medical Anomaly Detection.

Matthew Baugh, Hadrien Reynaud, Sergio Naval Marimont, Sarah Cechnicka, Johanna P. Müller, Giacomo Tarroni, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024

DISYRE: Diffusion-Inspired Synthetic Restoration for Unsupervised Anomaly Detection.

Sergio Naval Marimont, Matthew Baugh, Vasilis Siomos, Christos Tzelepis, Bernhard Kainz, Giacomo Tarroni

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Trade-Offs in Fine-Tuned Diffusion Models between Accuracy and Interpretability.

Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Zero-Shot Anomaly Detection with Pre-trained Segmentation Models.

Matthew Baugh, James Batten, Johanna P. Müller, Bernhard Kainz

CoRR, 2023

Pay Attention: Accuracy Versus Interpretability Trade-off in Fine-tuned Diffusion Models.

Mischa Dombrowski, Hadrien Reynaud, Johanna P. Müller, Matthew Baugh, Bernhard Kainz

CoRR, 2023

MoCoSR: Respiratory Motion Correction and Super-Resolution for 3D Abdominal MRI.

Weitong Zhang, Berke Doga Basaran, Qingjie Meng, Matthew Baugh, Jonathan K. Stelter, Phillip Lung, Uday Patel, Wenjia Bai, Dimitrios C. Karampinos, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Confidence-Aware and Self-supervised Image Anomaly Localisation.

Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

Many Tasks Make Light Work: Learning to Localise Medical Anomalies from Multiple Synthetic Tasks.

Matthew Baugh, Jeremy Tan, Johanna P. Müller, Mischa Dombrowski, James Batten, Bernhard Kainz

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models.

Mischa Dombrowski, Hadrien Reynaud, Matthew Baugh, Bernhard Kainz

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Zero-Shot Object Segmentation through Concept Distillation from Generative Image Foundation Models.

Mischa Dombrowski, Hadrien Reynaud, Matthew Baugh, Bernhard Kainz

CoRR, 2022

Adnexal Mass Segmentation with Ultrasound Data Synthesis.

Clara Lebbos, Jen Barcroft, Jeremy Tan, Johanna P. Müller, Matthew Baugh, Athanasios Vlontzos, Srdjan Saso, Bernhard Kainz

Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022

nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods.

Matthew Baugh, Jeremy Tan, Athanasios Vlontzos, Johanna P. Müller, Bernhard Kainz

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2022