Yannick Suter
Overview
Explore the profile of Yannick Suter including associated specialties, affiliations and a list of published articles.
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17
Citations
171
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Recent Articles
1.
Li J, Zhou Z, Yang J, Pepe A, Gsaxner C, Luijten G, et al.
Biomed Tech (Berl)
. 2024 Dec;
70(1):71-90.
PMID: 39733351
Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface...
2.
Bregy L, Nussbaumer-Ochsner Y, Martinez-Lozano Sinues P, Garcia-Gomez D, Suter Y, Gaisl T, et al.
Clin Mass Spectrom
. 2024 Aug;
7:29-35.
PMID: 39193555
Background: New mass spectrometry (MS) techniques analysing exhaled breath have the potential to better define airway diseases. Here, we present our work to profile the volatile organic compounds (VOCs) in...
3.
Pahud de Mortanges A, Luo H, Shu S, Kamath A, Suter Y, Shelan M, et al.
NPJ Digit Med
. 2024 Jul;
7(1):195.
PMID: 39039248
Explainable artificial intelligence (XAI) has experienced a vast increase in recognition over the last few years. While the technical developments are manifold, less focus has been placed on the clinical...
4.
Suter Y, Notter M, Meier R, Loosli T, Schucht P, Wiest R, et al.
Front Radiol
. 2023 Sep;
3:1211859.
PMID: 37745204
Automated tumor segmentation tools for glioblastoma show promising performance. To apply these tools for automated response assessment, longitudinal segmentation, and tumor measurement, consistency is critical. This study aimed to determine...
5.
Zbinden L, Catucci D, Suter Y, Hulbert L, Berzigotti A, Bronnimann M, et al.
Eur J Radiol
. 2023 Sep;
167:111047.
PMID: 37690351
Purpose: To evaluate the effectiveness of automated liver segmental volume quantification and calculation of the liver segmental volume ratio (LSVR) on a non-contrast T1-vibe Dixon liver MRI sequence using a...
6.
Ocana-Tienda B, Perez-Beteta J, Villanueva-Garcia J, Romero-Rosales J, Molina-Garcia D, Suter Y, et al.
Sci Data
. 2023 Apr;
10(1):208.
PMID: 37059722
Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malignancy of the central nervous system. Imaging studies of BMs are routinely used for...
7.
Rufenacht E, Kamath A, Suter Y, Poel R, Ermis E, Scheib S, et al.
Comput Methods Programs Biomed
. 2023 Feb;
231:107374.
PMID: 36738608
Background And Objective: Despite fast evolution cycles in deep learning methodologies for medical imaging in radiotherapy, auto-segmentation solutions rarely run in clinics due to the lack of open-source frameworks feasible...
8.
Zbinden L, Catucci D, Suter Y, Berzigotti A, Ebner L, Christe A, et al.
Sci Rep
. 2022 Dec;
12(1):22059.
PMID: 36543852
We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe...
9.
Suter Y, Knecht U, Valenzuela W, Notter M, Hewer E, Schucht P, et al.
Sci Data
. 2022 Dec;
9(1):768.
PMID: 36522344
Publicly available Glioblastoma (GBM) datasets predominantly include pre-operative Magnetic Resonance Imaging (MRI) or contain few follow-up images for each patient. Access to fully longitudinal datasets is critical to advance the...
10.
Suter Y, Knecht U, Alao M, Valenzuela W, Hewer E, Schucht P, et al.
Cancer Imaging
. 2020 Aug;
20(1):55.
PMID: 32758279
Background: This study aims to identify robust radiomic features for Magnetic Resonance Imaging (MRI), assess feature selection and machine learning methods for overall survival classification of Glioblastoma multiforme patients, and...