Program

Time Event
8:00-8:20 Registration, speaker check-in and poster setup
8:20-8:30 Opening remarks
8:30-9:15 Invited Talk 1 (45 min)

Prof. Dinggang Shen: Presentation Slides

9:15–9:45 Oral Presentations (Session 1 – Reconstruction) (each presentation lasts 15 min.)
    Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features
       Khosro Bahrami and Feng Shi and Islem Rekik and Dinggang Shen
   De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks
       Ariel Benou and Ronel Veksler and Alon Friedman and Tammy Riklin Raviv
9:45-10:15 Oral Presentations (Session 2 – Segmentation) (each presentation lasts 15 min.)
    The importance of skip connections in biomedical image segmentation
       Michal Drozdzal and Eugene Vorontsov and Gabriel Chartrand and Samuel Kadoury and Christopher Pal
    Multi-Dimensional Gated Recurrent Units for the Segmentation of Biomedical 3D-Data
       Simon Andermatt and Simon Pezold and Philippe C. Cattin
10:15-10:30 Presentation: Butterfly Network (15 min.)

Butterfly Network: Presentation Slides

10:30-11:00 Coffee Break
11:00-11:30 Oral Presentations (Session 3 – Microscopy image analysis) (each presentation lasts 15 min.)
    Cell Segmentation Proposal Network for Microscopy Image Analysis
       Saad Ullah Akram and Juho Kannala and Lauri Eklund and Janne Heikkila
    HEp-2 cell classification using K-support Spatial Pooling in Deep CNNs (poster paper)
       Xian-Hua Han and Jian Mei Lei and Yen-Wei Chen
11:30-13:00 Poster Presentations
    1. Vessel detection in ultrasound images using deep convolutional neural networks
       Erik Smistad and Lasse Lovstakken
    2. Longitudinal Multiple Sclerosis Lesion Segmentation using Multi-View Convolutional Neural Networks
       Ariel Birenbaum and Hayit Greenspan
    3. Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks
       Daniel E Worrall and Clare Wilson and Gabriel Brostow
    4. Fully Convolutional Network for Liver Segmentation and Lesions Detection
       Avi Ben-Cohenl and Idit Diamant and Eyal Klang and Michal Amitai and Hayit Greenspan
    5. Three-dimensional CT image segmentation by combining 2D fully convolutional network with 3D majority voting
       Xiangrong Zhou and Takaaki Ito and Ryosuke Takayama and Song Wang and Takeshi Hara and Hiroshi Fujita
    6. Medical image description using multi-task loss CNN
       Pavel Kisilev and Eli Sason and Ella Barkan and Sharbell Hashoul
    7. Fully automating Graf’s method for DDH diagnosis using deep convolutional neural networks
       David Golan and Yoni Donner and Chris Mansi and Jacob Jaremko and Manoj Ramachandran
    8. Understanding the Mechanisms of Deep Transfer Learning for Medical Images
       Hariharan Ravishankar and Prasad Sudhakar and Rahul Venkataramani and Sheshadri Thiruvenkadam, Pavan Annangi and Narayanan Babu and Vivek Vaidya
    9. A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography
       Ayelet Akselrod Ballin and Leonid Karlinsky and Sharon Alpert and Sharbell Hasoul and Rami Ben-Ari and Ella Barkan
13:00-14:00 Lunch
14:00-14:30 Oral Presentations (Session 4 – Multimodal data) (each presentation lasts 15 min.)
    Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks
       Dong Nie and Xiaohuan Cao and Yaozong Gao and Li Wang and Dinggang Shen
    Fast Predictive Image Registration
       Xiao Yangi and Roland Kwitt and Marc Niethammer
14:30-15:15 Invited Talk 2 (45 min)

Prof. Nassir Navab

15:15-15:45 Oral Presentations (Session 5 – Localisation) (each presentation lasts 15 min.)
    Automatic Slice Identification in 3D Medical Images with a ConvNet Regressor
       Bob D. de Vos and Max A. Viergever and Pim A. de Jong and Ivana Isgum
    Robust 3D organ localization with dual learning architectures and fusion (poster score)
       Xiaoguang Lu and Daguang Xu and David Liu
15:45-16:00 Presentation: NVIDIA (15 min.)

NVIDIA Presentation Slides

16:00-16:30 Coffee Break
16:30-17:00 Oral Presentations (Session 6 – Inference) (each presentation lasts 15 min.)
   Learning thermal process representations for intraoperative analysis of cortical perfusion during ischemic strokes
       Nico Hoffmann and Edmund Koch and Gerald Steiner and Uwe Petersohn and Matthias Kirsch
   Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis
       Youngjin Yoo and Lisa Tang and Tom Brosch and David K.B. Li and Luanne Metz and Anthony Traboulsee and Roger Tam
17:00-17:10 Presentation of the NVIDIA Best paper award, and final comments