title: Semiautomated analysis of embryoscope images: Using localized variance of image intensity to detect embryo developmental stages.
abstract: Embryo selection in in vitro fertilization (IVF) treatment has traditionally been done manually using microscopy at intermittent time points during embryo development. Novel technique has made it possible to monitor embryos using time lapse for long periods of time and together with the reduced cost of data storage, this has opened the door to long-term time-lapse monitoring, and large amounts of image material is now routinely gathered. However, the analysis is still to a large extent performed manually, and images are mostly used as qualitative reference. To make full use of the increased amount of microscopic image material, (semi)automated computer-aided tools are needed. An additional benefit of automation is the establishment of standardization tools for embryo selection and transfer, making decisions more transparent and less subjective. Another is the possibility to gather and analyze data in a high-throughput manner, gathering data from multiple clinics and increasing our knowledge of early human embryo development. In this study, the extraction of data to automatically select and track spatio-temporal events and features from sets of embryo images has been achieved using localized variance based on the distribution of image grey scale levels. A retrospective cohort study was performed using time-lapse imaging data derived from 39 human embryos from seven couples, covering the time from fertilization up to 6.3 days. The profile of localized variance has been used to characterize syngamy, mitotic division and stages of cleavage, compaction, and blastocoel formation. Prior to analysis, focal plane and embryo location were automatically detected, limiting precomputational user interaction to a calibration step and usable for automatic detection of region of interest (ROI) regardless of the method of analysis. The results were validated against the opinion of clinical experts. © 2015 International Society for Advancement of Cytometry.
authors.affiliation: School of Computing, Mathematics and Digital Technology, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK.
authors.forename: Anna
authors.initials: A
authors.lastname: Mölder
authors.forename: Sarah
authors.initials: S
authors.lastname: Drury
authors.forename: Nicholas
authors.initials: N
authors.lastname: Costen
authors.forename: Geraldine M
authors.initials: GM
authors.lastname: Hartshorne
authors.forename: Silvester
authors.initials: S
authors.lastname: Czanner
mesh_terms: D001755:Blastocyst / Q000166:cytology*; D015331:Cohort Studies; D003936:Diagnosis, Computer-Assisted; D046149:Embryo Culture Techniques / Q000379:methods*; D047108:Embryonic Development; D005307:Fertilization in Vitro / Q000379:methods*; D020669:Fetoscopes; D005332:Fetoscopy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D012189:Retrospective Studies; D059008:Time-Lapse Imaging
keywords: automated annotation; automated image analysis; computer-aided diagnosis; embryology; embryoscope; image-based embryo classification; time-lapse microscopy