Registration of medical image sequences using auto-differentiation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU146280" target="_blank" >RIV/00216305:26220/23:PU146280 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-981-16-6775-6_15" target="_blank" >https://link.springer.com/chapter/10.1007/978-981-16-6775-6_15</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-16-6775-6_15" target="_blank" >10.1007/978-981-16-6775-6_15</a>

Result language
angličtina
Original language name
Registration of medical image sequences using auto-differentiation
Original language description
This paper focuses on image registration using the automatic differentiation of deep learning frameworks. Specifically, a method for the registration of image sequences is proposed and tested on retinal video ophthalmoscopic data and brain DCE MR images. PyTorch auto-differentiation has been used as a core of an optimisation tool to find the optimal image transformation parameters. It allows us to easily design a loss function for our registration tasks. The image registration was achieved by simultaneous registration of all images using a global loss function without the need of the reference frame.
Czech name
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Czech description
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Project
<a href="/en/project/GA21-18578S" target="_blank" >GA21-18578S: Dual-wavelength functional retinal imaging and simultaneous biosignals acquisition for ocular blood circulation assessment</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Medical Imaging and Computer-Aided Diagnosis: Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2022)
ISBN
978-981-16-6774-9
ISSN
1876-1100
e-ISSN
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Number of pages
10
Pages from-to
169-178
Publisher name
Springer
Place of publication
neuveden
Event location
University of Leicester, UK
Event date
Nov 20, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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