4 papers
InVitroVision: a Multi-Modal AI Model for Automated Description of Embryo Development using Natural Language
Nicklas Neu, Thomas Ebner, Jasmin Primus +4
The application of artificial intelligence (AI) in IVF has shown promise in improving consistency and standardization of decisions, but often relies on annotated data and does not…
Expert-Annotated Embryo Image Dataset with Natural Language Descriptions for Evidence-Based Patient Communication in IVF
Nicklas Neu, Thomas Ebner, Jasmin Primus +4
Embryo selection is one of multiple crucial steps in in-vitro fertilization, commonly based on morphological assessment by clinical embryologists. Although artificial intelligence…
Predicting Blastocyst Formation in IVF: Integrating DINOv2 and Attention-Based LSTM on Time-Lapse Embryo Images
Zahra Asghari Varzaneh, Niclas Wölner-Hanssen, Reza Khoshkangini +2
The selection of the optimal embryo for transfer is a critical yet challenging step in in vitro fertilization (IVF), primarily due to its reliance on the manual inspection of exten…
Multitasking Embedding for Embryo Blastocyst Grading Prediction (MEmEBG)
Nahid Khoshk Angabini, Mohsen Tajgardan, Mahesh Madhavan +3
Reliable evaluation of blastocyst quality is critical for the success of in vitro fertilization (IVF) treatments. Current embryo grading practices primarily rely on visual assessme…