Academic Journal
Cell segmentation and representation with shape priors
| العنوان: | Cell segmentation and representation with shape priors |
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| المؤلفون: | Hirling, Dominik, Horvath, Peter |
| المساهمون: | Institute for Molecular Medicine Finland |
| بيانات النشر: | Chalmers University of Technology |
| سنة النشر: | 2024 |
| المجموعة: | Helsingfors Universitet: HELDA – Helsingin yliopiston digitaalinen arkisto |
| مصطلحات موضوعية: | Cell segmentation, Deep learning, Fourier descriptors, Shape representation, Statistical shape models, Biochemistry, cell and molecular biology, Medical biotechnology, 11832 Microbiology and virology |
| الوصف: | Cell segmentation is a fundamental problem of computational biology, for which convolutional neural networks yield the best results nowadays. This field is expanding rapidly, and in the recent years, shape -constrained segmentation models emerged as strong competitors to traditional, pixel-based segmentation methods for instance segmentation. These methods predict the parameters of the underlying shape model, so choosing the right shape representation is critical for the success of the segmentation. In this study, we introduce two new representation-based deep learning segmentation methods after a quantitative com-parison of the most important shape descriptors in the literature. Our networks are based on Fourier coefficients and statistical shape models, both of which have proven to be reliable tools for cell shape modelling. Our results indicate that the methods are competitive alternatives to the most widely used baseline deep learning algorithms, especially when the number of parameters for the underlying shape model are low or the cells to be segmented have irregular morphologies.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/). ; Peer reviewed |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| ردمك: | 978-85-14-59742-1 85-14-59742-6 |
| Relation: | http://hdl.handle.net/10138/571907; 85145974269; 000928288100001 |
| الاتاحة: | http://hdl.handle.net/10138/571907 |
| Rights: | cc_by_nc_nd ; info:eu-repo/semantics/openAccess ; openAccess |
| رقم الانضمام: | edsbas.A10C2947 |
| قاعدة البيانات: | BASE |
| ردمك: | 9788514597421 8514597426 |
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