Graduate Student Seminar Series
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Location: HS610 – 155 College St, Room 610
Presentation Title: ReSCU-Nets: Recurrent U-Nets for segmentation of timelapse microscopy data
Abstract: Segmenting multi-dimensional microscopy data requires high accuracy across many images (e.g. timepoints or Z slices) and is thus a labour-intensive part of biological image processing pipelines. We present ReSCU-Nets, recurrent convolutional neural networks that use the segmentation results from the previous frame as a prompt to segment the current frame. We demonstrate that ReSCU-Nets outperform state-of-the-art image segmentation models in different segmentation tasks on time-lapse microscopy sequences.
Supervisor Name: Rodrigo Fernandez-Gonzalez
Year of Study: 3
Program of Study: MASc
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