Selected Contributions (2017)

Oral presentations

  • Joseph Paul Cohen (University of Montreal)
    Count-ception: Counting by Fully Convolutional Redundant Counting
  • Martin Maška (Masaryk University)
    Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests
  • Constantin Pape (University of Heidelberg)
    Solving Large Multicut Problems for Connectomics via Domain Decomposition
  • Mira Valkonen (University of Tampere)
    Dual Structured Convolutional Neural Network with Feature Augmentation for Quantitative Characterization of Tissue Histology

Poster presentations

  • Sajith Sadanandan, Johan Karlsson, Carolina Wählby
    Spheroid Segmentation using Multiscale Deep Adversarial Networks
  • Martin Maška, Pavel Matula
    Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests
  • Denis Fortun, Noemi Debroux, Charles Kervrann
    Spatially-Variant Kernel for Optical Flow under Low Signal-to-Noise Ratios: Application to Microscopy
  • Constantin Pape, Thorsten Beier, Peter Li, Viren Jain, Davi Bock, Anna Kreshuk
    Solving large Multicut problems for connectomics via domain decomposition
  • Heba Sailem, Mar Arias-Garcia, Chris Bakal, Andrew Zisserman, Jens Rittscher
    Discovery of Rare Phenotypes in Cellular Images Using Weakly Supervised Deep Learning
  • Mira Valkonen, Kimmo Kartasalo, Kaisa Liimatainen, Matti Nykter, Leena Latonen, Pekka Ruusuvuori
    Dual structured convolutional neural network with feature augmentation for quantitative characterization of tissue histology
  • Faïçal Selka, Thomas Blein, Jasmine Burguet, Eric Biot, Patrick Laufs, Philippe Andrey
    Towards a spatio-temporal atlas of 3D cellular parameters during leaf morphogenesis
  • Neslihan Bayramoglu, Mika Kaakinen, Lauri Eklund, Janne Heikkila
    Towards Virtual H&E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks
  • Swati Jindal, Gaurav Gupta, Mohit Yadav, Monika Sharma, Lovekesh Vig
    Siamese Networks For Chromosome Classification
  • Håkan Wieslander, Gustav Forslid, Ewert Bengtsson, Carolina Wählby, Jan-Michaél Hirsch, Christina Runow Stark, Sajith Sadanandan
    Deep Convolutional Neural Networks For Detecting Cellular Changes Due To Malignancy
  • Keylor Viquez, Ognjen Arandjelovic, Andrew Blaikie, In Ae Hwang
    Synthesising Wider Field Images from Narrow-Field Retinal Video Acquired Using a Low-Cost Direct Ophthalmoscope (Arclight) Attached to a Smartphone
  • Qiuyu Chen, Ryoma  Bise, Lin Gu, Yinqiang Zheng, Imari Sato, Jenq-Neng Hwang, Nobuaki Imanishi,  Sadakazu  Aiso
    Virtual Blood Vessels in Complex Background using Stereo X-ray Images
  • Jonas Pichat, Eugenio Iglesias, Sotiris Nousias, Tarek Yousry, Sebastien Ourselin, Marc Modat Part-to-Whole
    Registration of Histology and MRI using Shape Elements
  • Courosh Mehanian, Mayoore Jaiswal, Charles Delahunt, Clay Thompson, Matt Horning, Liming Hu, Travis Ostbye, Shawn McGuire, Martha-Marie Mehanian, Cary Champlin, Ben Wilson, Earl Long, Stephane Proux, Dionicia Gamboa, Peter Chiodini, Jane Carter, Mehul Dhorda, David  Isaboke, Bernhards Ogutu, Wellington Oyibo, Elizabeth Villasis, Kyaw Myo Tun, Christine Bachman, David Bell
    Computer-Automated Malaria Diagnosis and Quantitation Using Convolutional Neural Networks
  • Joseph Paul Cohen, Genevieve Boucher, Craig A. Glastonbury, Henry Z Lo, Yoshua Bengio
    Count-ception: Counting by Fully Convolutional Redundant Counting
  • Zihao Tang, Donghao Zhang, Siqi Liu, Yang Song, Hanchuan Peng, Weidong Cai
    Automatic 3D Single Neuron Reconstruction with Exhaustive Tracing
  • Marcelo Cicconet, Daniel Hochbaum, David Richmond, Bernado Sabatini
    Bots for Software-Assisted Analysis of Image-Based Transcriptomics