Laura E. M. Wisse

According to our database1, Laura E. M. Wisse authored at least 18 papers between 2016 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Deep label fusion: A generalizable hybrid multi-atlas and deep convolutional neural network for medical image segmentation.
Medical Image Anal., 2023

Regional Deep Atrophy: a Self-Supervised Learning Method to Automatically Identify Regions Associated With Alzheimer's Disease Progression From Longitudinal MRI.
CoRR, 2023

Automated deep learning segmentation of high-resolution 7 T ex vivo MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases.
CoRR, 2023



2021
DeepAtrophy: Teaching a neural network to detect progressive changes in longitudinal MRI of the hippocampal region in Alzheimer's disease.
NeuroImage, 2021

Gray Matter Segmentation in Ultra High Resolution 7 Tesla ex vivo T2w MRI of Human Brain Hemispheres.
CoRR, 2021


Deep Label Fusion: A 3D End-To-End Hybrid Multi-atlas Segmentation and Deep Learning Pipeline.
Proceedings of the Information Processing in Medical Imaging, 2021

2020
DeepAtrophy: Teaching a Neural Network to Differentiate Progressive Changes from Noise on Longitudinal MRI in Alzheimer's Disease.
CoRR, 2020



2019
Facilitating Manual Segmentation of 3D Datasets Using Contour And Intensity Guided Interpolation.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

2018
Characterizing the human hippocampus in aging and Alzheimer's disease using a computational atlas derived from ex vivo MRI and histology.
Proc. Natl. Acad. Sci. USA, 2018

Characterizing Anatomical Variability and Alzheimer's Disease Related Cortical Thinning in the Medial Temporal Lobe Using Graph-Based Groupwise Registration and Point Set Geodesic Shooting.
Proceedings of the Shape in Medical Imaging, 2018

2017
Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.
NeuroImage, 2017

2016
Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

A framework for informing segmentation of in vivo MRI with information derived from ex vivo imaging: Application in the medial temporal lobe.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016


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