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The selection of high-quality sperms is critical to intracytoplasmic sperm injection, which accounts for 70–80% of in vitro fertilization (IVF) treatments. So far, sperm screening is usually performed manually by clinicians. However, the performance of manual screening is limited in its objectivity, consistency, and efficiency. To overcome these limitations, we have developed a fast and noninvasive three-stage method to characterize morphology of freely swimming human sperms in bright-field microscopy images using deep learning models. Specifically, we use an object detection model to identify sperm heads, a classification model to select in-focus images, and a segmentation model to extract geometry of sperm heads and vacuoles. The models achieve an F1-score of 0.951 in sperm head detection, a z-position estimation error within ±1.5 μm in in-focus image selection, and a Dice score of 0.948 in sperm head segmentation, respectively. Customized lightweight architectures are used for the models to achieve real-time analysis of 200 frames per second. Comprehensive morphological parameters are calculated from sperm head geometry extracted by image segmentation. Overall, our method provides a reliable and efficient tool to assist clinicians in selecting high-quality sperms for successful IVF. It also demonstrates the effectiveness of deep learning in real-time analysis of live bright-field microscopy images.
Nearly all metals form a passivation film due to oxidation in air at ambient temperatures, that acts as a diffusion barrier to protect the materials from further corrosion. Aluminum demonstrates excellent passivation behavior due to the formation of a protective amorphous alumina film during exposure to air at ambient temperatures. However, H. Ebinger and J. Yates discovered that the passivation of aluminum can be significantly improved by artificial oxidation. Both electron-beam induced oxidation in water vapor and oxidation in ozone atmospheres3 showed higher impedance in electrochemical impedance spectroscopy measurements to anion diffusion than the thermally grown oxides. To understand the nature of this beneficial passivation, we probed the microstructure of these amorphous oxide films by transmission electron microscopy (TEM).
The oxide films were grown on a polycrystalline Al substrate. The Al substrate was cleaned with a sputter cleaner inside a UHV (ultra-high vacuum) system.
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