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Moulay Akhloufi: Can AI Boost Success Rates in In Vitro Fertilization?
Moulay Akhloufi/cbc.ca
Oct 4, 2025, 02:46

Moulay Akhloufi: Can AI Boost Success Rates in In Vitro Fertilization?

Moulay Akhloufi, Head of the Perception, Robotics, and Intelligent Machines Laboratory, shared a post on LinkedIn:

“Can AI help improve In Vitro Fertilization (IVF) success rates?

Advancing IVF with Deep Learning: Semantic Segmentation of Human Blastocyst Images

In vitro fertilization (IVF) has brought hope to millions of families worldwide, yet success rates remain lower than expected. One key challenge lies in the accurate assessment of embryo quality, a task traditionally performed through subjective visual evaluation by embryologists.

Our latest research explores how deep learning can revolutionize this process by segmenting key blastocyst components: Inner Cell Mass (ICM), Trophectoderm (TE) and Zona Pellucida (ZP). These structures are critical indicators of embryo viability and implantation potential.

Our models demonstrated strong performance on the available blastocyst data, paving the way for automated, objective, and scalable embryoquality assessment. This work has the potential to enhance IVF success rates, reduce human error in embryo selection, and support embryologists with AI-powered decision tools.

Read the full paper here.”

Title: Semantic segmentation of human blastocyst images using deep CNNs and vision transformers

Authors: Wided S. Miled, Rafik Ghali, Sana Chtourou, Moulay A. Akhloufi

Moulay Akhloufi

AI deeplearning embryo embryoquality Fertility Fertility News in vitro fertilization Inner Cell Mass IVF Moulay A. Akhloufi Rafik Ghali Sana Chtourou SemanticSegmentation Trophectoderm Wided S. Miled Zona Pellucida
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