100 citations · 289 across the 29 of their papers we have counts for
10 papers · 1 filter
Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration
Bo Li, Wiro J. Niessen, Stefan Klein +4
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this me…
Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease
Esther E. Bron, Stefan Klein, Janne M. Papma +14
This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of…
Learning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI
Bo Li, Wiro J. Niessen, Stefan Klein +3
Analysis of longitudinal changes in imaging studies often involves both segmentation of structures of interest and registration of multiple timeframes. The accuracy of such analysi…
Differential diagnosis and molecular stratification of gastrointestinal stromal tumors on CT images using a radiomics approach
Martijn P. A. Starmans, Milea J. M. Timbergen, Melissa Vos +10
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to it…
WHO 2016 subtyping and automated segmentation of glioma using multi-task deep learning
Sebastian R. van der Voort, Fatih Incekara, Maarten M. J. Wijnenga +14
Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is a time-consuming tas…
Time efficiency analysis for undersampled quantitative MRI acquisitions
Riwaj Byanju, Stefan Klein, Alexandra Cristobal-Huerta +2
To realize Quantitative MRI (QMRI) with clinically acceptable scan time, acceleration factors achieved by conventional parallel imaging techniques are often inadequate. Further acc…