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Automated brain morphometry for sub-millimeter 7T MRI using transfer learning

Author:Gian Franco Piredda  Punith Venkategowda  Piotr Radojewski  Tom Hilbert  Arun Joseph  Gabriele Bonanno  Roland Wiest  Karl Egger  Shan Yang  Jean-Philippe Thiran  Ricardo Corredor-Jerez  Bénédicte Maréchal  Tobias Kober  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2155  

Room Session:Exhibition Hall:S8 & S9  

Institution:Inselspital, Bern University  Lausanne University Hospital and University of Lausanne  Siemens Healthcare AG  Siemens Healthcare Pvt. Ltd.  University of Freiburg  E´cole Polytechnique Fe´de´rale de Lausanne (EPFL)  sitem-insel AG  University of Bern  

Automatic segmentation of whole-body MRI using UnnU-Net: Feasibility of whole-skeleton ADC evaluation in plasma cell disorders

Author:Renyang Gu  Michela Antonelli  Pritesh Mehta  Ashik Amlani  Adrian Green  Radhouene Neji  Sebastien Ourselin  Isabel Dregely  Vicky Goh  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2162  

Room Session:Exhibition Hall:S8 & S9  

Institution:Guy’s & St Thomas’ NHS Foundation Trust  King's College London  Siemens Healthcare Limited  University College London  

A deep-learning non-contrast MRI lesion segmentation model for liver cancer patients that may have had previous surgery

Author:Nora Vogt  Zobair Arya  Luis Núñez  John Connell  Paul Aljabar  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2164  

Room Session:Exhibition Hall:S8 & S9  

Institution:Perspectum  

Efficient, streamline-free white matter tract segmentation for intraoperative diffusion MRI.

Author:Fiona Young  Patrick Hales  Laura Mancini  Sotirios Bisdas  Caroline Micallef  Tarek Yousry  Christopher Clark  Kristian Aquilina  Jonathan Clayden  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2158  

Room Session:Exhibition Hall:S8 & S9  

Institution:Great Ormond Street Hospital for Children  The National Hospital for Neurology & Neurosurgery, University College London Hospitals NHS Foundation Trust  University College London  UCL Queen Square Institute of Neurology  

Generalisability of Automated CNN-based Renal Segmentation for Multi-Vendor Studies

Author:Alexander Daniel  Charlotte Buchanan  David Morris  Hao Li  Rebecca Noble  João Sousa  Steven Sourbron  David Thomas  Andrew Priest  Susan Francis  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2160  

Room Session:Exhibition Hall:S8 & S9  

Institution:University College London  University of Cambridge  University of Edinburgh  University of Nottingham  University of Sheffield  Addenbrooke’s Hospital  

High temporal-resolution MRI during mild-cold exposure enables the assessment of brown adipose tissue with a low inter-image variability

Author:Aashley Sardjoe Mishre  Maaike Straat  Borja Martinez-Tellez  Mariëtte Boon  Oleh Dzyubachyk  Andrew Webb  Patrick Rensen  Hermien Kan  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2161  

Room Session:Exhibition Hall:S8 & S9  

Institution:Leiden University Medical Center  

Incorporating Histological Grading for Brain Tumor Segmentation

Author:Lipei Zhang  Yiran We  Chao Li  Stephen Price  Carola Schönlieb  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2154  

Room Session:Exhibition Hall:S8 & S9  

Institution:Univerisity of Cambridge  University of Cambridge  

Infant Brain Segmentation based on Multi-dMRI contrast Attention (BISMA)

Author:Tianjia Zhu  Minhui Ouyang  Lei Feng  Kay Sindabizera  Jessica Hyland  Hao Huang  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2159  

Room Session:Exhibition Hall:S8 & S9  

Institution:Children's Hospital of Philadelphia  Shandong University Cheeloo College of Medicine  University of Pennsylvania  

A privacy-preserving federated learning infrastructure for prostate segmentation on T2-Weighted MRI

Author:Fadila Zerka  Mohammed Sunoqrot  Bendik Abrahamsen  Alexandros Patsanis  Tone Frost Bathen  Mattijs Elschot  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2156  

Room Session:Exhibition Hall:S8 & S9  

Institution:NTNU  St. Olavs Hospital  

Protocol adaptive Stacked transfer learning (STL) U-NET with small dataset training for soft tissue segmentation in dynamic speech MRI

Author:Subin Erattakulangara  Karthika Kelat  Sajan Lingala  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2163  

Room Session:Exhibition Hall:S8 & S9  

Institution:University of Iowa  

Reducing the impact of texture on deep-learning brain tissue segmentation networks trained with simulated MR images

Author:Yasmina Al Khalil  Aymen Ayaz  Cristian Lorenz  Jürgen Weese  Josien Pluim  Marcel Breeuwer  

Session Type:Digital Poster  

Session Date:Wednesday, 11 May 2022  

Topic:Module 22: Processing & Analysis  

Session Name:Processing & Analysis: Segmentation I  

Program Number:2157  

Room Session:Exhibition Hall:S8 & S9  

Institution:Eindhoven University of Technology  Philips Research Laboratories  Philips Healthcare, MR R&D - Clinical Science