Leveraging expert knowledge for medical image segmentation
Public support
Provider
Czech Science Foundation
Programme
Standard projects
Call for proposals
SGA0202600001
Main participants
České vysoké učení technické v Praze / Fakulta elektrotechnická
Contest type
VS - Public tender
Contract ID
26-23522S
Alternative language
Project name in Czech
Leveraging expert knowledge for medical image segmentation
Annotation in Czech
Despite recent advances, deep learning methods for medical image segmentation can be hampered by limited availability of expertly labeled data. This project proposes a novel approach to enhance segmentation quality by incorporating constraints on invariance, topology, dimensions, position, count, shape, and other segmentation properties. The method will also handle weak annotations like scribbles and global properties such as fairness. Our key objective is to develop efficient algorithms that integrate deep learning with constraint optimization techniques. We will investigate penalty, barrier, and projection methods, the moving target method and feasibility-guaranteeing reparameterization. These techniques will be coupled with transformation-invariant network operators. The resulting methods will be made publicly available in a user-friendly software library. The methods will be experimentally evaluated on publicly available medical segmentation datasets for an easy comparison with existing approaches.
Scientific branches
R&D category
ZV - Basic research
OECD FORD - main branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
OECD FORD - secondary branch
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OECD FORD - another secondary branch
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CEP - equivalent branches <br>(according to the <a href="http://www.vyzkum.cz/storage/att/E6EF7938F0E854BAE520AC119FB22E8D/Prevodnik_oboru_Frascati.pdf">converter</a>)
AF - Documentation, librarianship, work with information<br>BC - Theory and management systems<br>BD - Information theory<br>IN - Informatics
Solution timeline
Realization period - beginning
Jan 1, 2026
Realization period - end
Dec 31, 2028
Project status
Z - Beginning multi-year project
Latest support payment
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Data delivery to CEP
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data delivery code
CEP26-GA0-GA-R
Data delivery date
May 6, 2026
Finance
Total approved costs
6,402 thou. CZK
Public financial support
6,402 thou. CZK
Other public sources
0 thou. CZK
Non public and foreign sources
0 thou. CZK