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Apoptosis detection for adherent cell populations in time-lapse phase-contrast microscopy images

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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.

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Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features

TL;DR: A phase contrast microscope image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis are proposed.
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Mining textural knowledge in biological images: Applications, methods and trends

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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

TL;DR: Experimental results performed on three types of cell populations validate that the interactive cell segmentation algorithm quickly reaches high quality results with minimal human interventions and is significantly more efficient than alternative methods, since the most informative samples are selected for human annotation/verification early.
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Phytol shows anti-angiogenic activity and induces apoptosis in A549 cells by depolarizing the mitochondrial membrane potential

TL;DR: The results of mitochondrial membrane potential analysis, cell cycle analysis, FT-IR and Western blotting analysis clearly demonstrate the mode of action by which phytol induces cell death in A549 lung adenocarcinoma cells.
References
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Multiresolution gray-scale and rotation invariant texture classification with local binary patterns

TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
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Programmed Cell Death in Animal Development and Disease

TL;DR: A growing body of work about the connections between apoptosis, stem cells, and cancer is explored, focusing on how apoptotic cells release a variety of signals to communicate with their cellular environment, including factors that promote cell division, tissue regeneration, and wound healing.
Journal ArticleDOI

Hidden Conditional Random Fields

TL;DR: A discriminative latent variable model for classification problems in structured domains where inputs can be represented by a graph of local observations and a hidden-state conditional random field framework learns a set of latent variables conditioned on local features.
Journal ArticleDOI

Understanding the phase contrast optics to restore artifact-free microscopy images for segmentation

TL;DR: A regularized quadratic cost function is formulated to restore artifact-free phase contrast images that directly correspond to the specimen's optical path length, and it is demonstrated that accurate restoration lays the foundation for high performance in cell detection and tracking.
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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