Peter M. Full

Orcid: 0000-0003-4326-8026

According to our database1, Peter M. Full authored at least 18 papers between 2017 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
Beyond rankings: Learning (more) from algorithm validation.
Medical Image Anal., May, 2023


2022
MOOD 2020: A Public Benchmark for Out-of-Distribution Detection and Localization on Medical Images.
IEEE Trans. Medical Imaging, 2022

Accurate Detection of Mediastinal Lesions with nnDetection.
Proceedings of the Lesion Segmentation in Surgical and Diagnostic Applications, 2022

2021
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.
IEEE Trans. Medical Imaging, 2021

Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge.
Medical Image Anal., 2021

How can we learn (more) from challenges? A statistical approach to driving future algorithm development.
CoRR, 2021

Abstract: Studying Robustness of Semantic Segmentation under Domain Shift in Cardiac MRI.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room.
CoRR, 2020

Robust Medical Instrument Segmentation Challenge 2019.
CoRR, 2020

Studying Robustness of Semantic Segmentation Under Domain Shift in Cardiac MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

nnU-Net for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
Improving Surgical Training Phantoms by Hyperrealism: Deep Unpaired Image-to-Image Translation from Real Surgeries.
Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions.
Dataset, June, 2018

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE Trans. Medical Imaging, 2018

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions.
CoRR, 2018


2017
Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features.
Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017


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