Denoisereg: Unsupervised Joint Denoising and Registration of Time-Lapse Live Cell Microscopy Images Using Deep Learning

Image registration is important for analysing time-lapse live cell microscopy images. However, this is challenging due to significant image noise and complex cell movement. We propose a novel end-to-end trainable deep neural network for joint denoising and affine registration of temporal live cell m...

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Bibliographic Details
Main Authors: Celikay, Kerem, Chagin, Vadim O., Cristina Cardoso, M., Rohr, Karl
Format: Conference Proceeding
Language:English
Subjects:
Biomedical Imaging
Deep learning
Denoising
Fluorescence Microscopy Images
Image registration
Microscopy
Neural networks
Noise reduction
Task analysis
Three-dimensional displays
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Summary:Image registration is important for analysing time-lapse live cell microscopy images. However, this is challenging due to significant image noise and complex cell movement. We propose a novel end-to-end trainable deep neural network for joint denoising and affine registration of temporal live cell microscopy images. Our network is trained unsupervised, and only a single network is required for both tasks which reduces overfitting. Our experiments show that the proposed network performs better than deep affine registration without denoising, and better than sequential deep denoising and affine registration. In combination with deep non-rigid registration, we outperform state-of-the-art non-rigid registration methods.
ISSN:1945-8452
DOI:10.1109/ISBI52829.2022.9761507