AIMC Topic: Organoids

Clear Filters Showing 21 to 30 of 51 articles

Deep-Orga: An improved deep learning-based lightweight model for intestinal organoid detection.

Computers in biology and medicine
PROBLEM: Organoids are 3D cultures that are commonly used for biological and medical research in vitro due to their functional and structural similarity to source organs. The development of organoids can be assessed by morphological tests. However, m...

Development of a deep learning based image processing tool for enhanced organoid analysis.

Scientific reports
Contrary to 2D cells, 3D organoid structures are composed of diverse cell types and exhibit morphologies of various sizes. Although researchers frequently monitor morphological changes, analyzing every structure with the naked eye is difficult. Given...

Deep Learning Model for Predicting Airway Organoid Differentiation.

Tissue engineering and regenerative medicine
BACKGROUND: Organoids are self-organized three-dimensional culture systems and have the advantages of both in vitro and in vivo experiments. However, each organoid has a different degree of self-organization, and methods such as immunofluorescence st...

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

PLoS computational biology
Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses. However, these metrics are diffi...

D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images.

Lab on a chip
Stem cell-derived organoids are a promising tool to model native human tissues as they resemble human organs functionally and structurally compared to traditional monolayer cell-based assays. For instance, colon organoids can spontaneously develop cr...

Deep-learning analysis of micropattern-based organoids enables high-throughput drug screening of Huntington's disease models.

Cell reports methods
Organoids are carrying the promise of modeling complex disease phenotypes and serving as a powerful basis for unbiased drug screens, potentially offering a more efficient drug-discovery route. However, unsolved technical bottlenecks of reproducibilit...

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...

A deep learning model for detection and tracking in high-throughput images of organoid.

Computers in biology and medicine
Organoid, an in vitro 3D culture, has extremely high similarity with its source organ or tissue, which creates a model in vitro that simulates the in vivo environment. Organoids have been extensively studied in cell biology, precision medicine, drug ...

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...