Apoptosis detection for adherent cell populations in time-lapse phase-contrast microscopy images
Seungil Huh,Dai Fei Elmer Ker,Hang Su,Takeo Kanade +3 more
- Vol. 15, pp 331-339
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TLDR
An image analysis method to detect apoptosis in time-lapse phase-contrast microscopy, which is nondestructive imaging and achieved around 90% accuracy in terms of average precision and recall.Abstract:
The detection of apoptosis, or programmed cell death, is important to understand the underlying mechanism of cell development. At present, apoptosis detection resorts to fluorescence or colorimetric assays, which may affect cell behavior and thus not allow long-term monitoring of intact cells. In this work, we present an image analysis method to detect apoptosis in time-lapse phase-contrast microscopy, which is non-destructive imaging. The method first detects candidates for apoptotic cells based on the optical principle of phase-contrast microscopy in connection with the properties of apoptotic cells. The temporal behavior of each candidate is then examined in its neighboring frames in order to determine if the candidate is indeed an apoptotic cell. When applied to three C2C12 myoblastic stem cell populations, which contain more than 1000 apoptosis, the method achieved around 90% accuracy in terms of average precision and recall.read more
Citations
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Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network
TL;DR: This paper proposes an efficient variant of capsule networks (CapsNets) as an alternative to CNNs and proposes a recurrent CapsNet constructed by stacking a CapsNet and a bi-directional long short-term recurrent structure to utilize temporal information within microscopy videos.
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Interactive Cell Segmentation Based on Active and Semi-Supervised Learning
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Phytol shows anti-angiogenic activity and induces apoptosis in A549 cells by depolarizing the mitochondrial membrane potential
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Journal ArticleDOI
Automated Mitosis Detection of Stem Cell Populations in Phase-Contrast Microscopy Images
TL;DR: This paper proposes an effective approach for automated mitosis detection using phase-contrast time-lapse microscopy, which is a nondestructive imaging modality, thereby allowing continuous monitoring of cells in culture.
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