AIMC Topic: Cell Shape
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Importance of dataset design in developing robust U-Net models for label-free cell morphology evaluation.
Journal of bioscience and bioengineering
Feb 10, 2025
Advances in regenerative medicine highlighted the need for label-free cell image analysis to replace conventional microscopic observation for non-invasive cell quality evaluation. Image-based evaluation provides an efficient, quantitative, and automa...
Optimizing gelation time for cell shape control through active learning.
Soft matter
Jan 29, 2025
Hydrogels are popular platforms for cell encapsulation in biomedicine and tissue engineering due to their soft, porous structures, high water content, and excellent tunability. Recent studies highlight that the timing of network formation can be just...
A data-driven approach to establishing cell motility patterns as predictors of macrophage subtypes and their relation to cell morphology.
PloS one
Dec 31, 2024
The motility of macrophages in response to microenvironment stimuli is a hallmark of innate immunity, where macrophages play pro-inflammatory or pro-reparatory roles depending on their activation status during wound healing. Cell size and shape have ...
Deep learning-based automatic image classification of oral cancer cells acquiring chemoresistance in vitro.
PloS one
Nov 1, 2024
Cell shape reflects the spatial configuration resulting from the equilibrium of cellular and environmental signals and is considered a highly relevant indicator of its function and biological properties. For cancer cells, various physiological and en...
Deep learning reveals a damage signalling hierarchy that coordinates different cell behaviours driving wound re-epithelialisation.
Development (Cambridge, England)
Sep 24, 2024
One of the key tissue movements driving closure of a wound is re-epithelialisation. Earlier wound healing studies describe the dynamic cell behaviours that contribute to wound re-epithelialisation, including cell division, cell shape changes and cell...
Small hand-designed convolutional neural networks outperform transfer learning in automated cell shape detection in confluent tissues.
PloS one
Feb 16, 2023
Mechanical cues such as stresses and strains are now recognized as essential regulators in many biological processes like cell division, gene expression or morphogenesis. Studying the interplay between these mechanical cues and biological responses r...
Classification of HEp-2 Staining Pattern Images Using Adapted Multilayer Perceptron Neural Network-Based Intra-Class Variation of Cell Shape.
Sensors (Basel, Switzerland)
Feb 15, 2023
There exists a growing interest from the clinical practice research communities in the development of methods to automate HEp-2 stained cells classification procedure from histopathological images. Challenges faced by these methods include variations...
MIRIAM: A machine and deep learning single-cell segmentation and quantification pipeline for multi-dimensional tissue images.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Feb 7, 2022
Increasingly, highly multiplexed tissue imaging methods are used to profile protein expression at the single-cell level. However, a critical limitation is the lack of robust cell segmentation tools for tissue sections. We present Multiplexed Image Re...
Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning.
Scientific reports
Jan 7, 2022
Signet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor has long been considered to be poorly differentiated and highly invasive because it has a higher rate of metastasis than well-differentiated adenocarcinoma. Bu...
Spatial and temporal dynamics of RhoA activities of single breast tumor cells in a 3D environment revealed by a machine learning-assisted FRET technique.
Experimental cell research
Nov 20, 2021
One of the hallmarks of cancer cells is their exceptional ability to migrate within the extracellular matrix (ECM) for gaining access to the circulatory system, a critical step of cancer metastasis. RhoA, a small GTPase, is known to be a key molecula...
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