The BioMedIA Group will have a strong presence at the 1st International Conference on Medical Imaging with Deep Learning (MIDL) to be held in Amsterdam in July. BioMedIA researchers will present some of their latest works on applying artificial intelligence techniques to the analysis of medical images. The group has six full papers and seven abstracts accepted at the conference.
Full Papers:
Evaluating Reinforcement Learning Agents for Anatomical Landmark Detection
Amir Alansary, Ozan Oktay, Yuanwei Li, Loic Le Folgoc, Benjamin Hou, Ghislain Vaillant, Ben Glocker, Bernhard Kainz and Daniel Rueckert
https://openreview.net/forum?id=SyQK4-nsz
Attention-Gated Networks for Improving Ultrasound Scan Plane Detection
Jo Schlemper, Ozan Oktay, Liang Chen, Jacqueline Matthew, Caroline Knight Bernhard Kainz, Ben Glocker, Daniel Rueckert
https://openreview.net/forum?id=BJtn7-3sM
Cascaded Transforming Multi-task Networks For Abdominal Biometric Estimation from Ultrasound
Matthew D. Sinclair, Juan Cerrolaza Martinez, Emily Skelton, Yuanwei Li, Christian F. Baumgartner, Wenjia Bai, Jacqueline Matthew, Caroline L. Knight, Sandra Smith, Jo Hajnal, Andrew P. King, Bernhard Kainz, Daniel Rueckert
https://openreview.net/forum?id=r1ZGQW2if
Attention U-Net: Learning Where to Look for the Pancreas
Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert
https://openreview.net/forum?id=Skft7cijM
NeuroNet: Fast and Robust Reproduction of Multiple Brain Image Segmentation Pipelines
Martin Rajchl, Nick Pawlowski, Daniel Rueckert, Paul M. Matthews, Ben Glocker
https://openreview.net/forum?id=Hks1TRisM
Domain Adaptation for MRI Organ Segmentation using Reverse Classification Accuracy
Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai, Konstantinos Kamnitsas, Eric O. Aboagye, Andrea G. Rockall, Daniel Rueckert, Ben Glocker
https://openreview.net/forum?id=r1t-DYooM
Abstracts:
Unsupervised Lesion Detection in Brain CT using Bayesian Convolutional Autoencoders
Nick Pawlowski, Matthew C.H. Lee, Martin Rajchl, Steven McDonagh, Enzo Ferrante, Konstantinos Kamnitsas, Sam Cooke, Susan Stevenson, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F.J. Newcombe, Ben Glocker
https://openreview.net/forum?id=S1hpzoisz
Deep Pose Estimation for Image-Based Registration
Benjamin Hou, Nina Miolane, Bishesh Khanal, Matthew Lee, Amir Alansary, Steven McDonagh, Joseph Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
https://openreview.net/forum?id=SyweajisG
Standard Plane Localisation in 3D Fetal Ultrasound Using Network with Geometric and Image Loss
Yuanwei Li, Juan J. Cerrolaza, Matthew Sinclair, Benjamin Hou, Amir Alansary, Bishesh Khanal, Jacqueline Matthew, Bernhard Kainz, Daniel Rueckert
https://openreview.net/forum?id=BykcN8siz
Image-Based Registration in Canonical Atlas Space
Benjamin Hou, Bishesh Khanal, Amir Alansary, Steven McDonagh, Alice Davidson, Mary Rutherford, Jo V. Hajnal, Daniel Rueckert, Ben Glocker, Bernhard Kainz
https://openreview.net/forum?id=Syxv3ijjf
Automatic Shadow Detection in 2D Ultrasound
Qingjie Meng, Christian Baumgartner, Matthew Sinclair, James Housden, Martin Rajchl, Alberto Gomez, Benjamin Hou, Nicolas Toussaint, Jeremy Tan, Jacqueline Matthew, Daniel Rueckert, Julia Schnabel, Bernhard Kainz
https://openreview.net/forum?id=SkU16Ec5f
Subject-level Prediction of Segmentation Failure using Real-Time Convolutional Neural Nets
Robert Robinson, Ozan Oktay, Wenjia Bai, Vanya V. Valindria, Mihir M. Sanghvi, Nay Aung, José Miguel Paiva, Filip Zemrak, Kenneth Fung, Elena Lukaschuk, Aaron M. Lee, Valentina Carapella, Young Jin Kimm, Bernhard Kainz, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Chris Page, Daniel Rueckert, Ben Glocker
https://openreview.net/forum?id=SJJfBr9oM
Deep Learning Methods for Estimating “Brain Age” from Structural MRI Scans
Sebastian G. Popescu, James H. Cole, David J. Sharp, Ben Glocker
https://openreview.net/forum?id=HJuBWTjjz