Paper
10 December 2021 Automatic evaluation of human oocyte developmental potential from microscopy images
Denis Baručić, Jan Kybic, Olga Teplá, Zinovij Topurko, Irena Kratochvílová
Author Affiliations +
Proceedings Volume 12088, 17th International Symposium on Medical Information Processing and Analysis; 120881A (2021) https://doi.org/10.1117/12.2604010
Event: Seventeenth International Symposium on Medical Information Processing and Analysis, 2021, Campinas, Brazil
Abstract
Infertility is becoming an issue for an increasing number of couples. The most common solution, in vitro fertilization, requires embryologists to carefully examine light microscopy images of human oocytes to determine their developmental potential. We propose an automatic system to improve the speed, repeatability, and accuracy of this process. We first localize individual oocytes and identify their principal components using CNN (U-Net) segmentation. Next, we calculate several descriptors based on geometry and texture. The final step is an SVM classifier. Both the segmentation and classification training is based on expert annotations. The presented approach leads to a classification accuracy of 70%.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Denis Baručić, Jan Kybic, Olga Teplá, Zinovij Topurko, and Irena Kratochvílová "Automatic evaluation of human oocyte developmental potential from microscopy images", Proc. SPIE 12088, 17th International Symposium on Medical Information Processing and Analysis, 120881A (10 December 2021); https://doi.org/10.1117/12.2604010
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KEYWORDS
Image segmentation

Feature extraction

Microscopy

Binary data

Wavelet transforms

Convolutional neural networks

Image classification

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