MOTIVATION: Reliable label-free methods are needed for detecting and profiling apoptotic events in time-lapse cell-cell interaction assays. Prior studies relied on fluorescent markers of apoptosis, e.g. Annexin-V, that provide an inconsistent and lat...
STUDY QUESTION: Can artificial intelligence (AI) algorithms developed to assist embryologists in evaluating embryo morphokinetics be enriched with multi-centric clinical data to better predict clinical pregnancy outcome?
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
We use deep learning methods to predict human induced pluripotent stem cell (hiPSC) formation using time-lapse brightfield microscopy images taken from a cell identified as the beginning of entered into the reprogramming process. A U-net is used to s...
We present a compact 3D diffractive microscope that can be inserted directly in a cell incubator for long-term observation of developing organisms. Our setup is particularly simple and robust, since it does not include any moving parts and is compati...
MOTIVATION: Live cell segmentation is a crucial step in biological image analysis and is also a challenging task because time-lapse microscopy cell sequences usually exhibit complex spatial structures and complicated temporal behaviors. In recent yea...
DNA-bound proteins are essential elements for the maintenance, regulation, and use of the genome. The time they spend bound to DNA provides useful information on their stability within protein complexes and insight into the understanding of biologica...
OBJECTIVE: To evaluate the consistency and objectivity of deep neural networks in embryo scoring and making disposition decisions for biopsy and cryopreservation in comparison to grading by highly trained embryologists.