Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging.

Abstract

Authors

• Melissa Yeo
  Melbourne Medical School, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia melissayeoxw@gmail.com.
• Bahman Tahayori
  Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia.
• Hong Kuan Kok
  Interventional Radiology Service, Department of Radiology, Beaumont Hospital, Dublin, Ireland.
• Julian Maingard
  School of Medicine, Deakin University Faculty of Health, Burwood, Victoria, Australia.
• Numan Kutaiba
  Department of Radiology, Austin Health, Heidelberg, Victoria, Australia.
• Jeremy Russell
  Department of Neurosurgery, Austin Health, Heidelberg, Victoria, Australia.
• Vincent Thijs
  Stroke Theme, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia.
• Ashu Jhamb
  Department of Radiology, St Vincent's Hospital Melbourne Pty Ltd, Fitzroy, Victoria, Australia.
• Ronil V Chandra
  5 Interventional Neuroradiology Service, Monash Imaging, Monash Health, Clayton, Australia.
• Mark Brooks
  5 Interventional Neuroradiology Service, Monash Imaging, Monash Health, Clayton, Australia.
• Christen D Barras
  School of Medicine, The University of Adelaide, Adelaide, South Australia, Australia.
• Hamed Asadi
  Neurointerventional Service, Department of Radiology, Beaumont Hospital, Dublin, Ireland; School of Medicine, Faculty of Health, Deakin University, Waurn Ponds, Australia. Electronic address: asadi.hamed@gmail.com.

Keywords

External Resources