AIMC Topic: Organoids
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Visualization of incrementally learned projection trajectories for longitudinal data.
Scientific reports
Jun 12, 2024
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualiz...
SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.
Cell genomics
May 31, 2024
Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-effi...
Image-based profiling and deep learning reveal morphological heterogeneity of colorectal cancer organoids.
Computers in biology and medicine
Mar 26, 2024
Patient-derived organoids have proven to be a highly relevant model for evaluating of disease mechanisms and drug efficacies, as they closely recapitulate in vivo physiology. Colorectal cancer organoids, specifically, exhibit a diverse range of morph...
OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion.
Communications biology
Mar 13, 2024
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be measured th...
Revealing the clinical potential of high-resolution organoids.
Advanced drug delivery reviews
Feb 8, 2024
The symbiotic interplay of organoid technology and advanced imaging strategies yields innovative breakthroughs in research and clinical applications. Organoids, intricate three-dimensional cell cultures derived from pluripotent or adult stem/progenit...
Deep-Orga: An improved deep learning-based lightweight model for intestinal organoid detection.
Computers in biology and medicine
Dec 19, 2023
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
Nov 13, 2023
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
Aug 18, 2023
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
Nov 9, 2022
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
Oct 25, 2022
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...
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