Post-doctoral Researcher

About

I am a research associate in the department of Computing at Imperial College London, UK. My general interests are in machine learning, deep learning, reinforcement learning, medical imaging, and computer vision. My primary expertise is in applying deep learning to medical image analysis tasks such as image segmentation, landmark detection, motion compensation, surface reconstruction and super-resolution.

Recent Publications

2016 (2)
  • Amir Alansary, Konstantinos Kamnitsas, Alice Davidson, Rostislav Khlebnikov, Martin Rajchl, Christina Malamateniou, Mary Rutherford, Joseph V Hajnal, Ben Glocker, Daniel Rueckert, others, Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.589–597, 2016

  • Martin Rajchl, Matthew CH Lee, Franklin Schrans, Alice Davidson, Jonathan Passerat-Palmbach, Giacomo Tarroni, Amir Alansary, Ozan Oktay, Bernhard Kainz, Daniel Rueckert, Learning under Distributed Weak Supervision, arXiv preprint arXiv:1606.01100, 2016

2015 (2)
  • Bernhard Kainz, Amir Alansary, Christina Malamateniou, Kevin Keraudren, Mary Rutherford, Joseph V Hajnal, Daniel Rueckert, Flexible reconstruction and correction of unpredictable motion from stacks of 2D images, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.555–562, 2015

  • Amir Alansary, Matthew Lee, Kevin Keraudren, Bernhard Kainz, Christina Malamateniou, Mary A. Rutherford, Joseph V. Hajnal, Ben Glocker, Daniel Rueckert, Automatic Brain Localization in Fetal MRI Using Superpixel Graphs, ICML Workshop on Machine Learning meets Medical Imaging, volume 9487, pp.13–22, 2015

Address
Room 344, Huxley Building
Department of Computing
Imperial College London
180 Queen's Gate
London SW7 2AZ, UK
Email
a.alansary14 at imperial.ac.uk
Twitter
https://twitter.com/amiralansary
LinkedIn
https://uk.linkedin.com/in/amiralansary
GitHub
https://github.com/amiralansary
External link
https://www.doc.ic.ac.uk/~aa16914/