Program

The workshop will be a full-day event, with invited speakers from the CIFAR fellowship and researchers in medical image analysis and deep learning.

Participants are invited to present their work as a poster presentation and/or as a demo.
Poster and demo presenters will have 2-3 minutes to pitch their work, demo and posters will be available the whole day.

At the end of the day, we will be discussing about grand challenges in medical imaging with a panel of experts in medical imaging and deep learning, talking about the future of intelligent systems in medical imaging and healthcare.

Invited speakers

 
Bram van Ginneken
Diagnostic Image Analysis Group, Radboud University Medical Center
Fraunhofer Mevis
Chief Scientific Officer at Thirona

"Deep learning in medical imaging versus deep learning in computer vision: what's the difference?"

 
Benjamin Graham
Facebook AI research lab

"Spatially Sparse Convolutional networks"
 
Olaf Ronneberger
Google DeepMind
University of Freiburg

"U-Net: Convolutional Networks for Biomedical Image Segmentation"
 
Georg Langs
Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna
Medical Vision Group at CSAIL, Massachusetts Institute of Technology

"Linking Imaging and Semantics to Learn from Large-Scale Medical Imaging Data"
 
Richard Zemel
Department of Computer Science, University of Toronto
Senior CIFAR fellow

"End-to-End Instance Segmentation and Counting"
 
David Fleet
Computer Science Department, University of Toronto
Department of Computer and Mathematical Sciences, University of Toronto Scarborough
Senior CIFAR fellow

"Atomic-Resolution Protein Reconstruction from Cyro-EM"

 
Nicolas Chapados
Chief Science Officer at Imagia

"Heteromodal Image Segmentation with Convolutional Neural Networks"
 
Paul Babyn
Head, Department of Medical Imaging, University of Saskatchewan and Saskatoon Health Region

"Applications of Deep Learning/Machine Learning in Medical Imaging- a radiologist’s perspective"


Program

Coffee and tea will be available during registration.

 8:30 Registration
 9:00  Opening  
 9:05  
 Bram van Ginneken
 "Deep learning in medical imaging versus deep learning in computer vision:  what's the difference?"

 9:50  
 Richard Zemel
 "End-to-End Instance Segmentation and Counting"

 10:35  Pitches
 
 Alle Meije Wink
 "Linear SVM discrimination maps for efficient prediction and classifier storage"

 Arnaud Arindra Adiyoso Setio
 "Automatic pulmonary nodule detection system using deep learning"

 David Tellez
 "Mitotic figure detection in histopathological images using deep learning"

 Gijs van Tulder
 "Representation learning for cross-modality classification"

 Jelmer Wolterink
 "Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities"

 Konstantinos Kamnitsas
 "Deep learning for brain lesion segmentation"

 Majd Zreik
 "Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks"
 10:45  Coffee break
 11:15  
 Olaf Ronneberger
 "U-Net: Convolutional Networks for Biomedical Image Segmentation"

 12:00  
 Nicolas Chapados
 "Heteromodal Image Segmentation with Convolutional Neural Networks"
 
 12:45  Pitches
 
 Mitko Veta
 "Cutting out the middleman: measuring nuclear area in histopathology slides without segmentation"

 Mohammad Havaei
 "Fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs)"

 Nicolas Chapados
 "HeMIS: Hetero-Modal Image Segmentation"

 Nikolas Lessmann
 "Calcium scoring in chest CT using dilated convolutions for candidate detection"

 Pim Moeskops
 "Automatic Segmentation of MR Brain Images With a Convolutional Neural Network"

 Tameem Adel
 "3D Scattering Transforms for Disease Classification in Neuroimaging"

 Thijs Kooi
 "Towards an Independent Reader for Screening Mammography"
 13:00  Lunch
 14:00  
 Georg Langs
 "Linking Imaging and Semantics to Learn from Large-Scale Medical Imaging Data"

 14:45  
 David Fleet
 "Atomic-Resolution Protein Reconstruction from Cyro-EM"

 15:30  Coffee break
 15:45  
 Benjamin Graham
 "Spatially Sparse Convolutional networks"

 16:30  
 Paul Babyn
 "Applications of Deep Learning/Machine Learning in Medical Imaging- a radiologist’s perspective"

 17:15  Panel discussion - ask your question here!
 18:00  Closing