Wellcome / EPSRC Centre for Interventional and Surgical Sciences



15 October 2021

It’s been another successful year for WEISS at MICCAI!

MICCAI 2021 logo

The annual MICCAI conference attracts world leading biomedical scientists, engineers, and clinicians from a wide range of disciplines associated with medical imaging and computer assisted intervention. As with last year, this year’s conference was hosted virtually, but for the first time the ClinICCAI event was co-hosted - a MICCAI event dedicated to healthcare practitioners researching the translational and clinical aspects of medical image computing, computer-assisted interventions, and medical robotics.

The ASMUS workshop was held for the second year in a row with 22 presentations, 2 keynotes and 5 demos taking place on 4 October. Several WEISS papers were submitted as part of the workshop, with Shaheer Saeed et al. winning the best paper award with their paper: Adaptable image quality assessment using meta-reinforcement learning of task amenability! Well done also to Zach Baum who won the best demo award for his demo: ADAPTS (Artificial intelligence Diagnostic And Prognostic Tools for Sonography) for real-time ultrasound assessment and COVID-19 diagnosis. Congratulations to the all-WEISS delivery team: Yipeng Hu, Su-Lin Lee, Alex Grimwood, Zhe Min and Zach Baum for organizing a great workshop! Find the full ASMUS proceedings here.

Sophia Bano, Francisco Vasconcelos and Danail Stoyanov were all part of the organising committee for the EndoVis-FetReg challenge. This was a sub-challenge of the popular endoscopic vision challenge EndoVis, which has been a regular feature at MICCAI since 2015. The FetReg challenge explored placental vessel segmentation and registration for mosaicking in clinical fetoscopy for the treatment of Twin-to-Twin Transfusion Syndrome (TTTS) – you can now watch a recording of the FetReg challenge on YouTube. The FetReg challenge was also featured in the June edition of Computer Vision News as their Challenge of the Month. Congratulations to Binod Bhattarai and team who won the segmentation award at FetReg.

WEISS also had success at the SimSurgSkill challenge. Also part of the EndoVis challenge, this sub-challenge is aimed at developing automated skills assessment algorithms using virtual reality (VR) based surgical tasks and objective metrics that are provided directly from the virtual environment. Emanuele Colleoni, Dimitris Psychogyios and Yueming Jin recieved the runner-up prize in Category 1: Surgical tool clevis and needle detection; and also managed to scoop first prize in Category 2: Objective skill efficiency metrics predictions. Congratulations!  

Sophia Bano also co-organised the Women in MICCAI Inspirational Leadership Legacy (WiM WILL) initiative. It’s goal is to enhance and spotlight leaders and build a community legacy. This was also a great success – you can watch some of the highlights on the WiM WILL YouTube channel.  


AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes
Sophia Bano, Brian Dromey, Francisco Vasconcelos, Raffaelle Napolitano, Anna L. David, Donald M. Peebles, and Danail Stoyanov

Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures
Fernando Pérez-García, Catherine Scott, Rachel Sparks, Beate Diehl, and Sébastien Ourselin

Cal-Obs, A Prospective Study Investigating The Use Of Dimensionless Square Jerk For The Assessment Of Expertise In Obstetric Ultrasound
Dromey, Brian*; Vasconcelos, Francisco; Neary-Zajiczek, Lydia; David, Anna L.; Stoyanov, Danail; Peebles, Donald

Minimising Subjectivity In Surgery - An Automl Approach For Intraoperative Fluorescence Angiography.
Soares, António S*; Bano, Sophia Dr; Clancy, Neil T; Lovat, Laurence; Stoyanov, Danail; Chand, Manish

Development and Evaluation of Intraoperative Ultrasound Segmentation with Negative Image Frames and Multiple Observer Labels 
Liam F. Chalcroft, Jiongqi Qu, Sophie A. Martin, Iani JMB Gayo, Giulio V. Minore, Imraj RD Singh, Shaheer U. Saeed, Qianye Yang, Zachary M. C. Baum, Andre Altmann, Yipeng Hu

Endoscopic Ultrasound Image Synthesis Using a Cycle-Consistent Adversarial Network
Alexander Grimwood, Joao Ramalhinho, Zachary M. C. Baum, Nina Montaña-Brown, Gavin J. Johnson, Yipeng Hu, Matthew J. Clarkson, Stephen P. Pereira, Dean C. Barratt, Ester Bonmati

Lung Ultrasound Segmentation and Adaptation Between COVID-19 and Community-Acquired Pneumonia
Harry Mason, Lorenzo Cristoni, Andrew Walden, Roberto Lazzari, Thomas Pulimood, Louis Grandjean, Claudia A. M. Gandini Wheeler-Kingshott, Yipeng Hu, Zachary M. C. Baum

Adaptable Image Quality Assessment Using Meta-Reinforcement Learning of Task Amenability
Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides, Zachary M. C. Baum, Qianye Yang, Mirabela Rusu, Richard E. Fan, Geoffrey A. Sonn, J. Alison Noble, Dean C. Barratt, Yipeng Hu