AI for the detection of gastrointestinal motility in 3D cine MR

Develop a deep learning method to automatically quantify gastrointestinal motion using dynamic 2D and 3D MRI of the abdomen.

FINISHED

2019

 

 | 

2024

 

RESEARCH AREAS

About project

Dynamic MRI allows detection and quantification of motility in the complete gastrointestinal tract without harm for the patient. This has been demonstrated to be valuable in inflammatory bowel disease and may be valuable in the evaluation of other gastrointestinal pathologies. In spite of possibilities offered by imaging, an automatic, fast, robust and reproducible method for motility quantification, especially exploiting dynamic 3D MR data, is currently lacking. Hence, the goal of this project is to develop a deep learning method to automatically quantify gastrointestinal motion using dynamic 2D and 3D MRI of the abdomen.

 

Our publications & software

Journal articlesL. D. van Harten, C, S. de Jonge, F. Struik, J. Stoker, I. Išgum, "Quantitative Analysis of Small Intestinal Motility in 3D Cine-MRI Using Centerline-Aware Motion Estimation", Journal of Magnetic Resonance Imaging, 2024.
L. D. Van Harten, J. Stoker; I. Išgum, "Robust deformable image registration using cycle-consistent implicit representations", IEEE Transactions on Medical Imaging, 2023; 43 (2): 784-793.
L.D. van Harten, C.S. de Jonge, K.J. Beek, J. Stoker, I. Isgum, "Untangling and segmenting the small intestine in 3D cine-MRI using deep learning", Medical Image Analysis, 2022; 78: 102386.
InproceedingsL. van Harten, R. L. M. Van Herten, I. Isgum, "REINDIR: Repeated Embedding Infusion for Neural Deformable Image Registration", Medical Imaging with Deep Learning, 2024; 250: 577-595.
L. van Harten, R.L.M. van Herten, J. Stoker and I. Isgum, "Deformable Image Registration with Geometry-informed Implicit Neural Representations", Medical Imaging with Deep Learning, 2023; 227: 730-742.
L. van Harten, C. de Jonge, J. Stoker, I. Isgum, "Untangling the small intestine in 3D cine-MRI using deep stochastic tracking", Medical Imaging with Deep Learning (MIDL 2021), 2021.
PHD thesesL. D. van Harten, "Motion analysis in 4D MRI of the small intestine using neural networks", 2024.