Title Soft optical sensor for embryo quality evaluation based on multi-focal image fusion and RAG-enhanced vision transformers
Authors Jonaitis, Domas ; Raudonis, Vidas ; Drejeriene, Egle ; Kozlovskaja - Gumbriene, Agne ; Salumets, Andres
DOI 10.3390/s26051441
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Is Part of Sensors.. Basel : MDPI. 2026, vol. 26, iss. 5, art. no. 1441, p. 1-25.. ISSN 1424-8220
Keywords [eng] soft sensor ; embryo grading ; data fusion ; Vision Transformer ; RAG ; explainable AI ; deep learning
Abstract [eng] Assessing human embryo quality is a critical step in in vitro fertilization (IVF), yet traditional manual grading remains subjective and physically limited by the shallow depth-of-field in conventional microscopy. This study develops a novel “soft optical sensor” architecture that transforms standard optical microscopy into an automated, high-precision instrument for embryo quality assessment. The proposed system integrates two key computational innovations: (1) a multi-focal image fusion module that reconstructs lost morphological details from Z-stack focal planes, effectively creating a 3D-aware representation from 2D inputs; and (2) a retrieval-augmented generation (RAG) framework coupled with a Swin Transformer to provide both high-accuracy classification and explainable clinical rationales. Validated on a large-scale clinical dataset of 102,308 images (prior to augmentation), the system achieves a diagnostic accuracy of 94.11%. This performance surpasses standard single-plane analysis methods by 9.43%, demonstrating the critical importance of fusing multi-focal data. Furthermore, the RAG module successfully grounds model predictions in standard ESHRE consensus guidelines, generating natural language explanations. The results demonstrate that this soft sensor approach significantly reduces inter-observer variability and offers a robust tool for standardized morphological assessment, though prospective validation against live birth outcomes remains essential for clinical adoption.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2026
CC license CC license description