| Title |
Algavision: object recognition tool for phytoplankton cells in microscopy images |
| Authors |
Jasiūnas, Simas ; Ghedini, Giulia ; Treigys, Povilas |
| DOI |
10.15388/LMITT.2026.10 |
| Full Text |
|
| Is Part of |
Lietuvos magistrantų informatikos ir IT tyrimai: konferencijos darbai, 2026 m. gegužės 6 d. Vilnius.. Vilnius : Vilniaus universiteto leidykla. 2026, p. 89-97.. eISSN 2783-784X |
| Keywords [eng] |
cell segmentation ; deep learning ; microscopy ; phytoplankton |
| Abstract [eng] |
Phytoplankton are microbes driving half of global primary production and are widely used model organisms in various studies. Despite advancements in high-throughput methods for acquisition of cell size and abundance data, microscopy remains widely preferred in multi-strain experiments. In this study, an instance segmentation model was trained on a dataset containing 11 strains and integrated into an image processing pipeline. The final version of the pipeline showed superiority over an established thresholding method (Avg. F1 Score 86% vs. 34%). This approach also highlights the potential of clustering unseen strains by prompting a general-purpose segmenter with low-confidence predictions. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2026 |
| CC license |
|
