Embryonic Development Analysis System Using Time-Series Image Evaluation
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Solution Overview
Problem
Current technologies face challenges in accurately evaluating fertile ova, as existing methods lack comprehensive and efficient evaluation processes, leading to suboptimal assessment of embryonic development and fertility potential.
Innovation Solution
An embryonic development analysis system that captures time-series images of cells, assigns evaluation values to predetermined items, and evaluates characteristics based on these values using machine learning algorithms, providing a graphical user interface to assist users in inputting and correcting evaluation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive evaluation of fertile ovum is performed using multiple parameters and time-series analysis, then evaluation accuracy is improved, but evaluation time and complexity increase
Solution Approach 1:
The system performs preliminary automated processing of time-series images to extract morphological parameters and generate evaluation data before final assessment. By pre-processing images to extract key features such as cell division timing, morphology changes, and developmental stage markers, the system reduces the time required for comprehensive evaluation while maintaining high accuracy through automated parameter extraction from multiple time points
Solution Approach 2:
The system creates standardized evaluation templates and reference profiles based on known developmental patterns. By comparing actual time-series observations against these pre-established reference models, the system can rapidly assess multiple parameters simultaneously without requiring manual analysis of each individual parameter, thus reducing evaluation time while maintaining comprehensive assessment accuracy
2Measurement precision
If multiple evaluation items are analyzed for each image, then evaluation comprehensiveness is improved, but processing complexity increases
Solution Approach 1:
The evaluation process is divided into distinct modular components: image acquisition module, parameter extraction module, evaluation calculation module, and assessment module. Each module handles specific tasks independently - extracting morphological parameters, timing parameters, and developmental stage parameters separately - which reduces processing complexity while enabling comprehensive multi-parameter evaluation through systematic organization of the analysis workflow
Solution Approach 2:
The system employs a unified evaluation framework that simultaneously processes multiple evaluation items including morphology, cell division timing, and developmental stage using the same time-series image data. This multi-functional approach allows comprehensive assessment across different parameters without requiring separate complex processing systems for each evaluation item, reducing overall processing complexity while maintaining evaluation comprehensiveness
Data Source
AI summary
Methods and apparatus for analyzing embryonic development images. The method comprises obtaining a plurality of embryonic development images captured in a time series, determining, for at least one of the plurality of embryonic development images, a time series of evaluation values for each of a plurality of evaluation items associated with the plurality of embryonic development images, and evaluating a characteristic of cells represented in one or more of the plurality of embryonic development images based, at least in part, on the time series of evaluation values for the plurality of evaluation items.