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ESTRO 2022
Programme
Imaging acquisition and processing
06 May 2022 - 10 May 2022
Copenhagen, Denmark
Onsite/Online
ESTRO 2022
Session
Imaging acquisition and processing
Session Type:
Poster (digital)
Track:
Physics
Journey:
Add to
My Programme
A simple proton-radiography system for accurate RSP measurements in proton therapy
Francesco Olivari
,
The Netherlands
Presentation Number:
PO-1591
A novel system and approach for proton radiography using a monolithic scintillator detector
Daniel Robertson
,
USA
Presentation Number:
PO-1592
Automatic segmentation of individual lymph nodes in head and neck cancer patients using 3D CNNs
Floris Reinders
,
The Netherlands
Presentation Number:
PO-1593
The use of LEGO to assess CT-MRI fusion accuracy for stereotactic radiosurgery
Geoff Heyes
,
United Kingdom
Presentation Number:
PO-1594
Automated stability study on mpMRI prostate radiomics features to variations in segmentation
Sithin Thulasi Seetha
,
Italy
Presentation Number:
PO-1595
Evaluation of synthetic CTs generated from T2-weighted MRIs of prostate cancer patients
Sebastian Andersson
,
Sweden
Presentation Number:
PO-1597
Deep learning based 4D synthetic CTs for daily proton dose calculations in lung cancer patients
Adrian Thummerer
,
Germany
Presentation Number:
PO-1598
Comparison of Deep Learning synthetic CT methods for CBCT-guided adaptive prostate radiotherapy
Paul van Haaren
,
The Netherlands
Presentation Number:
PO-1599
Development of simplified auto-segmentable functional cardiac atlas
Pierre Loap
,
France
Presentation Number:
PO-1600
GPU accelerated Monte Carlo activation calculations for PET range verification in proton therapy
Keegan McNamara
,
Switzerland
Presentation Number:
PO-1601
Image reconstruction using the PETITION PET scanner aimed at biologically guided proton therapy
Shubhangi Makkar
,
Switzerland
Presentation Number:
PO-1602
Evaluating the geometric accuracy of the constructed Mid-P CT using mathematically deformed phantoms
Firass Ghareeb
,
Portugal
Presentation Number:
PO-1603
Weekly dosimetric evaluation of CBCT-based synthetic CTs for proton therapy of head & neck patients
Rutger de Koster
,
The Netherlands
Presentation Number:
PO-1604
Low dose cone beam CT protocols for image-guided breast and pediatric treatments
Marianne Falk
,
Sweden
Presentation Number:
PO-1605
Slice-by-slice deep learning aided oropharyngeal cancer segmentation on PET and CT images
Alessia De Biase
,
The Netherlands
Presentation Number:
PO-1606
Low-dose CT allows for accurate proton dose calculation in esophageal cancer
Masoud Elhamiasl
,
Belgium
Presentation Number:
PO-1607
Application of BioXmark® liquid fiducial markers for CyberKnife® stereotactic body radiotherapy
Sandra Ledina
,
Latvia
Presentation Number:
PO-1608
Generating synthetic hypoxia images from FDG-PET using Generative Adversarial Networks (GANs)
Alberto Traverso
,
Italy
Presentation Number:
PO-1609
Evaluation of Compressed Sensing acceleration for 3D radiotherapy MRI
Frederik Crop
,
France
Presentation Number:
PO-1610
Evaluation of synthetic-CT generated from prostate MRI (0.35T) with a 2D+ Pix2Pix method
Jean-Claude Nunes
,
France
Presentation Number:
PO-1611
CNN-based multi-task learning for tumor segmentation and T-Stage classification in NPC MRI
Jiyou Peng
,
China
Presentation Number:
PO-1612
AI-driven combined deformable registration and image synthesis between radiology and histopathology
Amaury Leroy
,
France
Presentation Number:
PO-1613
Quantification of MRI signal artifacts from titanium intracavitary brachytherapy applicator
souha aouadi
,
Qatar
Presentation Number:
PO-1614
Evaluation of prostate synthetic CTs from 0.35T MR images using different deep training cohort sizes
Jean-Claude Nunes
,
France
Presentation Number:
PO-1615
Evaluation of deep learning-based OAR segmentation in paediatric radiotherapy settings
Adam Szmul
,
United Kingdom
Presentation Number:
PO-1616
Mapping of the human wrist to develop a non-invasive radiation detector for Dynamic PET application
Youstina Daoud
,
Canada
Presentation Number:
PO-1617
Standardising Nomenclatures in Breast Radiotherapy Imaging Data using Machine Learning Algorithms
Phillip Chlap
,
Australia
Presentation Number:
PO-1618
Clinical evaluation of novel DWI sequence on rectal cancer patients in a low tesla MR-Linac system
Matteo Nardini
,
Italy
Presentation Number:
PO-1619
Can auto-delineated lung lobe motion be a surrogate for tumour motion for Mid-V determination?
Evelien Bogaert
,
Belgium
Presentation Number:
PO-1620
An efficient training approach for brain paediatrics synthetic CT generation for protontherapy
Francois de Kermenguy
,
France
Presentation Number:
PO-1621
Target definition for cardiac radioablation of ventricular tachycardia: A multimodal workflow
Louis Rigal
,
France
Presentation Number:
PO-1622
Characterisation of synthetic CTs clinical quality: which gamma indices to evaluate in practice?
Emilie Alvarez-Andres
,
Germany
Presentation Number:
PO-1623
An empirical approach for metal implant classification using 2D dual energy radiography
Jens Edmund
,
Denmark
Presentation Number:
PO-1624
Modeled clinical target volume in soft tissue using diffusion weighted MRI data
Nadya Shusharina
,
USA
Presentation Number:
PO-1625
Automatic brain structure segmentation in children with brain tumours
Abigail Bryce-Atkinson
,
United Kingdom
Presentation Number:
PO-1626
Peripheral dose sparing of volume-of-interest CBCT using a novel 2.5 MV low-Z beam
Jennifer Borsavage
,
Canada
Presentation Number:
PO-1627
Evaluation of material properties retrieved with a radiotherapy specific CT scanner
Erik Pettersson
,
Sweden
Presentation Number:
PO-1628
Ion CT image reconstruction with the TIGRE toolbox
Stefanie Kaser
,
Austria
Presentation Number:
PO-1629
An analytic method for inhomogeneity correction of Gafchromic EBT3 films
Marco Parisotto
,
Italy
Presentation Number:
PO-1630
Feasibility of low-dose 4DCBCT for patient setup and motion measurement
Josh Lindsay
,
United Kingdom
Presentation Number:
PO-1631
DL-based OAR delineation for Head and Neck Radiotherapy: accuracy versus computational resources
Lucia Cubero
,
Spain
Presentation Number:
PO-1632
Radiomics predicts the location of local recurrence after reirradiation for head and neck carcinoma
Arnaud Beddok
,
France
Presentation Number:
PO-1633
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