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![The tracking module uses a U-Net based supervised architecture [37] to segment the mitochondria and a Kalman filter based tracker to estimate their motion.](profile/Arif-Ahmed-Sekh/publication/363631888/figure/fig3/AS:11431281114506801@1674536439070/The-tracking-module-uses-a-U-Net-based-supervised-architecture-37-to-segment-the.png){kind=tracking}
The tracking module uses a U-Net based supervised architecture [37] to segment the mitochondria and a Kalman filter based tracker to estimate their motion.
Source publication
Mitochondria play a crucial role in cellular metabolism. This paper presents a novel method to visualize mitochondria in living cells without the use of fluorescent markers. We propose a physics-guided deep learning approach for obtaining virtually labeled micrographs of mitochondria from bright-field images. We integrate a microscope’s point sprea...
Context in source publication
Context 1
... is performed by the process of tracing individual mitochondria over time by preserving the identity. The process involves detection, identity assignment, and linking identity over time (see Fig. 3). The first step of detection is based on the segmentation of mitochondria. While the brightfield images are not suitable for segmentation directly, their virtually labeled versions emulate fluorescence images and are therefore amenable to segmentation. First, the U-Net network [37] is trained on a set of manually segmented images of ...
