activity
20172023
most citedMedical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging

16 citations · 24 across the 7 of their papers we have counts for

collaborators

7 papers

q-bio.QM2023★ 3 cited

Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering

Zhijian Yang, Junhao Wen, Ahmed Abdulkadir +25

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multipl…

eess.IV2022★ 4 cited

CorticalFlow: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability

Rodrigo Santa Cruz, Léo Lebrat, Darren Fu +4

The problem of Cortical Surface Reconstruction from magnetic resonance imaging has been traditionally addressed using lengthy pipelines of image processing techniques like FreeSurf…

eess.IV2020★ 1 cited

DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction

Rodrigo Santa Cruz, Leo Lebrat, Pierrick Bourgeat +3

The study of neurodegenerative diseases relies on the reconstruction and analysis of the brain cortex from magnetic resonance imaging (MRI). Traditional frameworks for this task li…

eess.IV2020★ 16 cited

Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging

Vishnu M. Bashyam, Jimit Doshi, Guray Erus +24

Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and…

eess.IV2020

Going deeper with brain morphometry using neural networks

Rodrigo Santa Cruz, Léo Lebrat, Pierrick Bourgeat +5

Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases. Recent advances in this domain indicate that deep convoluti…

eess.IV2020

Generalisable 3D Fabric Architecture for Streamlined Universal Multi-Dataset Medical Image Segmentation

Siyu Liu, Wei Dai, Craig Engstrom +4

Data scarcity is common in deep learning models for medical image segmentation. Previous works proposed multi-dataset learning, either simultaneously or via transfer learning to ex…

cs.CV2017

3D Scanning System for Automatic High-Resolution Plant Phenotyping

Chuong V Nguyen, Jurgen Fripp, David R Lovell +4

Thin leaves, fine stems, self-occlusion, non-rigid and slowly changing structures make plants difficult for three-dimensional (3D) scanning and reconstruction -- two critical steps…