Members

Alexandra Degeest

Contact Information

Alexandra Degeest
PhD Student
UCL / ICTEAM
Avenue Hippocrate 55 box B1.54.07
1348 Louvain-la-Neuve
Belgium

Office: -
Phone: -
Email: umair [period] javaid [snail] uclouvain [period] be
Personal home page?

Biography

Alexandra Degeest

I am a Pakistani national and have an engineering background with signal processing (Machine Learning) as a main research interest. I did my master’s project at the Medical Image Processing Lab at EPFL, Switzerland where the topic of my thesis was « Advanced Machine Learning tools to uncover characteristics of dynamic functional brain connectivity ». My phd topic here is Deep Learning for automatic segmentation of medical images with applications in the Oncology.



Publications

Article de périodique (Journal article)
2019
  • Javaid, Umair ; Souris, Kevin ; Dasnoy-Sumell, Damien ; Huang, Sheng ; Lee, John Aldo. Mitigating inherent noise in Monte Carlo dose distributions using dilated U?Net. In: Medical Physics, Vol. 46, no.12, p. 5790-5798 (2019). doi:10.1002/mp.13856. http://hdl.handle.net/2078.1/226746

  • Communication à un colloque (Conference Paper)
  • Javaid, Umair ; Dasnoy-Sumell, Damien ; Lee, John Aldo. Semantic segmentation of computed tomography for radiotherapy with deep learning: compensating insufficient annotation quality using contour augmentation. Image Processing (San Diego, United States, du 16/2/2019 au 21/2/2019). In: Medical Imaging 2019: Image Processing, SPIE, 2019. 9781510625457. doi:10.1117/12.2512461. http://hdl.handle.net/2078.1/226527

  • Brion, Eliott ; Léger, Jean ; Javaid, Umair ; Lee, John Aldo ; De Vleeschouwer, Christophe ; Macq, Benoît. Using planning CTs to enhance CNN-based bladder segmentation on Cone Beam CT. SPIE Medical Imaging 2019 (San Diego, California, United States, du 16/02/2019 au 21/02/2019). In: Proceedings of SPIE Medical Imaging 2019, Vol. Image-Guided Procedures, Robotic Interventions, and Modeling (Accepté/Sous presse). http://hdl.handle.net/2078.1/212402

  • 2018
  • Javaid, Umair ; Lee, John Aldo. Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks. European Symposium on Artificial Neural Networks - ESANN'18 (Bruges, Belgium, du 25/04/2018 au 27/04/2018). In: ESANN 2018 proceedings, 2018. 978-287587047-6. http://hdl.handle.net/2078.1/209418

  • Léger, Jean ; Brion, Eliott ; Javaid, Umair ; Lee, John Aldo ; De Vleeschouwer, Christophe ; Macq, Benoît. Contour Propagation in CT Scans with Convolutional Neural Networks. Advanced Concepts for Intelligent Vision Systems (France, du 24/09/2018 au 27/09/2018). In: Proceedings of ACIVS, in Lecture Notes in Computer Science book series., 2018. 978-3-030-01449-0. doi:10.1007/978-3-030-01449-0_32. http://hdl.handle.net/2078.1/203221

  • Javaid, Umair ; Lee, John Aldo. Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet. Advanced Concepts for Intelligent Vision Systems - ACIVS'18 (Poitiers, France, du 24/09/2018 au 27/09/2018). In: LNCS 11182 Advanced Concepts for Intelligent Vision Systems, collab. Dasnoy-Sumell, Damien, 2018. 978-3-030-01449-0. doi:10.1007/978-3-030-01449-0. http://hdl.handle.net/2078.1/209687