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Toward automatic phenotyping of developing embryos from videos
| Content Provider | Hyper Articles en Ligne (HAL) |
|---|---|
| Author | Ning, F. Delhomme, D. Lecun, Y. Piano, F. Bottou, L. Barbano, P.E. |
| Abstract | We describe a trainable system for analyzing videos of developing C. elegans embryos. The system automatically detects, segments, and locates cells and nuclei in microscopic images. The system was designed as the central component of a fully automated phenotyping system. The system contains three modules 1) a convolutional network trained to classify each pixel into five categories. cell wall, cytoplasm, nucleus membrane, nucleus, outside medium; 2) an energy-based model, which cleans up the output of the convolutional network by learning local consistency constraints that must be satisfied by label images; 3) a set of elastic models of the embryo at various stages of development that are matched to the label images. |
| Related Links | https://hal.science/hal-00114920/file/IEEE.pdf |
| ISSN | 10577149 |
| Volume Number | 14 (9) |
| Journal | IEEE Transactions on Image Processing |
| Language | English |
| Publisher | HAL CCSD Institute of Electrical and Electronics Engineers |
| Publisher Date | 2005-09-07 |
| Access Restriction | Open |
| Subject Keyword | RNAI RECOGNITION nonlinear filter convolutional network energy-based model CAENORHABDITIS-ELEGANS image segmentation C-ELEGANS INTERFERENCE |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Software |
