| Autor: |
Bao R; University of Missouri-Columbia, MO 65211, USA., Al-Shakarji NM; University of Missouri-Columbia, MO 65211, USA., Bunyak F; University of Missouri-Columbia, MO 65211, USA., Palaniappan K; University of Missouri-Columbia, MO 65211, USA. |
| Jazyk: |
angličtina |
| Zdroj: |
... IEEE International Conference on Computer Vision workshops. IEEE International Conference on Computer Vision [IEEE Int Conf Comput Vis Workshops] 2021 Oct; Vol. 2021, pp. 3354-3363. Date of Electronic Publication: 2021 Nov 24. |
| DOI: |
10.1109/iccvw54120.2021.00375 |
| Abstrakt: |
Accurate segmentation and tracking of cells in microscopy image sequences is extremely beneficial in clinical diagnostic applications and biomedical research. A continuing challenge is the segmentation of dense touching cells and deforming cells with indistinct boundaries, in low signal-to-noise-ratio images. In this paper, we present a dual-stream marker-guided network (DMNet) for segmentation of touching cells in microscopy videos of many cell types. DMNet uses an explicit cell marker-detection stream, with a separate mask-prediction stream using a distance map penalty function, which enables supervised training to focus attention on touching and nearby cells. For multi-object cell tracking we use M2Track tracking-by-detection approach with multi-step data association. Our M2Track with mask overlap includes short term track-to-cell association followed by track-to-track association to re-link tracklets with missing segmentation masks over a short sequence of frames. Our combined detection, segmentation and tracking algorithm has proven its potential on the IEEE ISBI 2021 6th Cell Tracking Challenge (CTC-6) where we achieved multiple top three rankings for diverse cell types. Our team name is MU-Ba-US, and the implementation of DMNet is available at, http://celltrackingchallenge.net/participants/MU-Ba-US/. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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