Image Analysis in Acute Stroke

From 2011 through 2020, DIAG has developed methods to analyze CT scans of the head, mainly for diagnosis of acute stroke. Deep learning solutions for non-contrast CT, contrast-enhanced CT and 4D CT scans were implemented and validated.

Funding

People

Rashindra Manniesing

Rashindra Manniesing

Ajay Patel

Ajay Patel

Coordinator RTC Deep Learning

RTC Deep Learning

Sil van de Leemput

Sil van de Leemput

Research Software Engineer

RTC Deep Learning

Midas Meijs

Midas Meijs

PhD Candidate

 Anton Meijer

Anton Meijer

Mathias Prokop

Mathias Prokop

Professor

Radboudumc

Publications

  • S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-contrast CT from Spatiotemporal 4D CT", IEEE Transactions on Medical Imaging, 2020;39(4):985-996.
  • M. Meijs, "Automated Image Analysis and Machine Learning to Detect Cerebral Vascular Pathology in 4D-CTA", 2020.
  • R. Becks, R. Manniesing, J. Vister, S. Pegge, S. Steens, E. van Dijk, M. Prokop and F. Meijer, "Brain CT Perfusion Improves Intracranial Vessel Occlusion Detection on CT Angiography", Journal of Neuroradiology, 2019;46(2):124-129.
  • S. van de Leemput, J. Teuwen, B. van Ginneken and R. Manniesing, "MemCNN: A Python/PyTorch package for creating memory-efficient invertible neural networks", JOSS, 2019;4(39):1576.
  • A. Patel, F. Schreuder, C. Klijn, M. Prokop, B. van Ginneken, H. Marquering, Y. Roos, M. Baharoglu, F. Meijer and R. Manniesing, "Intracerebral haemorrhage segmentation in non-contrast CT", Nature Scientific Reports, 2019;9(1):17858.
  • S. van de Leemput, M. Meijs, A. Patel, F. Meijer, B. van Ginneken and R. Manniesing, "Multiclass Brain Tissue Segmentation in 4D CT using Convolutional Neural Networks", IEEE Access, 2019;7(1):51557-51569.
  • M. Meijs, S. Pegge, K. Murayama, H. Boogaarts, M. Prokop, P. Willems, R. Manniesing and F. Meijer, "Color mapping of 4D-CTA for the detection of cranial arteriovenous shunts", American Journal of Neuroradiology, 2019;40(9):1498-1504.
  • A. Patel, S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT", IEEE Access, 2019;7(1):92355-92364.
  • M. Meijs, F. de Leeuw, H. Boogaarts, R. Manniesing and F. Meijer, "Circle of Willis collateral flow in carotid artery occlusion is depicted by 4D-CTA", World Neurosurgery, 2018;114:421-426.
  • S. van de Leemput, A. Patel and R. Manniesing, "Full Volumetric Brain Tissue Segmentation in Non-contrast CT using Memory Efficient Convolutional LSTMs", Medical Imaging meets NeurIPS, 2018.
  • A. Patel and R. Manniesing, "A convolutional neural network for intracranial hemorrhage detection in non-contrast CT", Medical Imaging, 2018;10575.
  • S. van de Leemput, M. Prokop, B. van Ginneken and R. Manniesing, "Stacked Bidirectional Convolutional LSTMs for 3D Non-contrast CT Reconstruction from Spatiotemporal 4D CT", Medical Imaging with Deep Learning, 2018.
  • M. Meijs, A. Patel, S. van de Leemput, M. Prokop, E. van Dijk, F. de Leeuw, F. Meijer, B. van Ginneken and R. Manniesing, "Robust Segmentation of the Full Cerebral Vasculature in 4D CT Images of Suspected Stroke Patients", Nature Scientific Reports, 2017;7.
  • A. Patel, B. van Ginneken, F. Meijer, E. van Dijk, M. Prokop and R. Manniesing, "Robust Cranial Cavity Segmentation in CT and CT Perfusion Images of Trauma and Suspected Stroke Patients", Medical Image Analysis, 2017;36:216-228.
  • R. Manniesing, M. Oei, L. Oostveen, J. Melendez, E. Smit, B. Platel, C. S├ínchez, F. Meijer, M. Prokop and B. van Ginneken, "White Matter and Gray Matter Segmentation in 4D Computed Tomography", Nature Scientific Reports, 2017;7(119).
  • R. Manniesing, M. Oei, B. van Ginneken and M. Prokop, "Quantitative Dose Dependency Analysis of Whole-Brain CT Perfusion Imaging", Radiology, 2016;278(1):190-197.
  • R. Manniesing, C. Brune, B. van Ginneken and M. Prokop, "A 4D CT Digital Phantom of an Individual Human Brain for Perfusion Analysis", PeerJ, 2016;4:e2683.