ISBI 2019 AWARDS

Best Paper Awards

Best machine learning paper award:
Aniket Pramanik and colleagues from the University of Iowa, USA for the paper “Off-The-Grid Model Based Deep Learning (O-MoDL)”

Runners-up for the best paper award
Ruiming Cao and colleagues from the University of California Los Angeles, USA for the paper “Prostate Cancer Detection and Segmentation in Multi-Parametric MRI Via CNN and Conditional Random Field”

Thanh-an Pham and colleagues from the Ecole Polytechnique Fédérale de Lausanne, Switzerland for the paper “Closed-Form Expression of the Fourier Ring-Correlation for Single-Molecule Localization Microscopy”

Winner of the best paper award
Christian Jaques and colleagues from the Idiap Research Institute, Switzerland for the paper “Multi-Spectral Widefield Microscopy of the Beating Heart through Post-Acquisition Synchronization and Unmixing”

The Best Paper Winners were also offered free participation in the IEEE EMBS summer school in 2020: http://ieeess.enst-bretagne.fr


ISBI 2019 will recognize the three best papers from students and early-career researchers that will be presented during the conference either as an oral or poster presentation. In addition, our sponsor NVIDIA will offer a state-of-the-arts GPU card for the best machine learning paper.

Based on ISBI reviews and the recommendations of our editors, the top ten papers have been selected and are listed below. Among those, a committee of senior IEEE researchers will score each presentation during ISBI while also taking into account the reviews from the conference paper selection process. The awards will be announced at the conference Thursday April 11, 2019 at 10 am.

Congratulations to our best paper award finalists who are listed below:

  • Ke Yan and colleagues from the National Institute of Health, USA for the paper “Fine-Grained Lesion Annotation in CT Images with Knowledge Mined from Radiology Reports”
  • Uddeshya Upadhyay and colleagues from the Indian Institute of Technology, India for the paper “Robust Super-Resolution Gan, with Manifold-Based and Perception Loss”
  • Christian Jaques and colleagues from the Idiap Research Institute, Switzerland for the paper “Multi-Spectral Widefield Microscopy of the Beating Heart through Post-Acquisition Synchronization and Unmixing”
  • Kai Zhang and colleagues from University of Florida, USA for the paper “A Convolutional Framework for Forward and Back-Projection in Fan-Beam Geometry”
  • Thanh-an Pham and colleagues from the Ecole Polytechnique Fédérale de Lausanne, Switzerland for the paper “Closed-Form Expression of the Fourier Ring-Correlation for Single-Molecule Localization Microscopy”
  • Raphael Philippe Titouan Couronne and colleagues from INRIA, France for the paper “Learning Disease Progression Models with Longitudinal Data and Missing Values”
  • Mohammad Hossein Jafari and colleagues from the University of British Columbia, Canada for the paper “Semi-Supervised Learning for Cardiac Left Ventricle Segmentation Using Conditional Deep Generative Models As Prior”
  • Ruiming Cao and colleagues from the University of California, USA for the paper “Prostate Cancer Detection and Segmentation in Multi-Parametric MRI Via CNN and Conditional Random Field”
  • Aniket Pramanik and colleagues from the University of Iowa, USA for the paper “Off-The-Grid Model Based Deep Learning (O-MoDL)”
  • Fanglin Huang and colleagues from Shenzhen University, China for the paper “Sparse Low-Rank Constrained Adaptive Structure Learning Using Multi-Template for Autism Spectrum Disorder Diagnosis”

Travel awards

ISBI 2019 is pleased to offer ten travel grants, each of $1,000 funded by the NIH National Institute of Biomedical Imaging and Bioengineering for students and early career researchers based in the USA who present their work at the conference.

Congratulations to the winners of the ISBI travel awards who are listed below. We thank the support of NIH/NHBI.

  • Arko Barman from the University of Texas Health Science Center at Houston who will present the paper “Determining Ischemic Stroke from CT-Angiography Imaging Using Symmetry-Sensitive Convolutional Networks”
  • Ruiming Cao from the University of California, Los Angeles who will present the paper “Prostate Cancer Detection and Segmentation in Multi-Parametric MRI Via CNN and Conditional Random Field”
  • Emily Dennis from Brigham & Women’s Hospital, Harvard Medical School who will present the paper “Associations between Maternal Depression and Infant Fronto-Limbic Connectivity”
  • Sarah Gerard from The University of Iowa who will present the paper “Pulmonary Lobe Segmentation Using a Sequence of Convolutional Neural Networks for Marginal Learning”
  • James Gornet from Columbia University   who will present the paper “Reconstructing neuronal anatomy from whole-brain images”
  • Peixian Liang from the University of Notre Dame who will present the paper “Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation”
  • Aniket Pramanik from the University of Iowa who will present the paper “Off-The-Grid Model Based Deep Learning (O-MoDL)”
  • Wiem Safta from the University of Louisville who will present the paper “Multiple Instance Learning for Malignant vs. Benign Classification of Lung Nodules in Thoracic Screening CT Data”
  • Yuxing Tang from the National Institutes of Health who will present the paper “Abnormal Chest X-Ray Identification with Generative Adversarial One-Class Classifier”
  • Kai Zhang from the University of Florida who will present the paper “A Convolutional Framework for Forward and Back-Projection in Fan-Beam Geometry”
  • Peiye Zhuang from the University of Illinois at Urbana-Champaign who will present the paper “fMRI Data Augmentation Via Synthesis”