Dr. Yannick Suter is a PostDoc with extensive expertise in the field of medical imaging and artificial intelligence (AI). His work focuses on the development and application of AI methods for the analysis and processing of medical image data, especially for tumor assessment and automated segmentation. His significant publications include contributions to the creation of large medical datasets such as MedShapeNet, the development of radiomics-based approaches for glioblastoma patients and the application of deep learning for automated quantification of liver volumes.
2024
Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging
npj Digital Medicine
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22 Jul 2024
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doi:10.1038/s41746-024-01190-w
2023
Evaluating automated longitudinal tumor measurements for glioblastoma response assessment
Frontiers in Radiology
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07 Sep 2023
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doi:10.3389/fradi.2023.1211859
A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data
Scientific Data
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14 Apr 2023
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doi:10.1038/s41597-023-02123-0
PyRaDiSe: A Python package for DICOM-RT-based auto-segmentation pipeline construction and DICOM-RT data conversion
Computer Methods and Programs in Biomedicine
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01 Apr 2023
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doi:10.1016/j.cmpb.2023.107374
2022
The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation
Scientific Data
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15 Dec 2022
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doi:10.1038/s41597-022-01881-7
2020
Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques
Cancer Imaging
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05 Aug 2020
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doi:10.1186/s40644-020-00329-8
Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning
Lecture Notes in Computer Science
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01 Jan 2020
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doi:10.1007/978-3-030-66843-3_13
2018
Fast and uncertainty-aware cerebral cortex morphometry estimation using random forest regression
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
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01 Apr 2018
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doi:10.1109/isbi.2018.8363752
2017
Automated connectivity-based groupwise cortical atlas generation: Application to data of neurosurgical patients with brain tumors for cortical parcellation prediction
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
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01 Apr 2017
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doi:10.1109/isbi.2017.7950633
2016
Automated white matter fiber tract identification in patients with brain tumors.
NeuroImage. Clinical
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25 Nov 2016
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pmid:27981029