Ultrasound Localisation and TRacking Algorithms for Super Resolution (ULTRA-SR) Challenge:

About the Challenge

Super-resolution (SR) ultrasound imaging, particularly through localisation and tracking of microbubble contrast agents (also known as ultrasound localisation microscopy or ULM), is a new exciting area of research in biomedical ultrasound with potential impact in a wide range of biomedical applications. In recent years many different SR methodologies and algorithms have been proposed by different groups and their applications to biological systems, pre-clinical models and clinical patients are being explored.

We challenge the participants to produce the best SR images using a set of data consisting of a number of contrast enhanced ultrasound image sequences generated through computer simulation and in-vivo acquisition. Participants are asked to submit:

  1. Their SR imaging results in a pre-defined format;
  2. A paper summarizing details of the methodology. Paper submissions should follow the IEEE IUS 2022 proceedings guidelines.

All accepted participants are required to prepare a poster for presentation during the ULTRA-SR workshop at IEEE IUS 2022 in Venice. Posters will remain visible during this 3-hour challenge summary workshop, as well as during the entire symposium.

The top 4-8 finishers will receive a cash prize of up to $1,000 USD and will have the opportunity to deliver oral presentations about their algorithms during this workshop.

Further details of the ULTRA-SR challenge and a web link will be available soon.


Mengxing Tang
Imperial College London


Vassilis Sboros
Heriot-Watt University


Marcelo Lerendegui
Imperial College London


George Papageorgiou
Heriot-Watt University


Organizing Comittee

Jorgen Jensen (Technical University of Denmark)

Georg Schmitz (Ruhr-University Bochum)

Pengfei Song (UIUC)

Chris Dunsby (Imperial College)

Mingxi Wan (Xian Jiaotong University)

Sevan Harput (LSBU)

Kirsten Christensen-Jefferies (King’s College London)

Massimo Mischi (Eindhoven University of Technology)

Ruud van Sloun (Eindhoven University of Technology)

Mickael Tanter (INSERM)

Olivier Couture (Sorbonne University)

Yonina Eldar (Weizmann Institute)

Jianwen Luo (Tsinghua University)

Paul Dayton (NC State University)

Shigao Chen (Mayo Clinic)

Jean Provost (Polytechnique Montréal)

Kai Riemer (Imperial College)

Jipeng Yan (Imperial College)

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