Recent advances in microscopy imaging and image analysis motivate more and more institutes worldwide to establish dedicated core-facilities for bioimage analysis. To maximise the benefits research groups at these institutes gain from their core-facilities, they should be established to fit well into their respective environment. In this article, we introduce common collaborator requests and corresponding potential services core-facilities can offer. We also discuss potential competing interests between the targeted missions and implementations of services to guide decision makers and core-facility founders to circumvent common pitfalls.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/jmi.13192 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlines.
Data Brief
February 2025
Cell Death, Lysosomes and Artificial Intelligence Group, Department of Experimental Medical Science, Faculty of Medicine, Lund University, BMC D10, 22184 Lund, Sweden.
Many forms of bioimage analysis involve the detection of objects and their outlines. In the context of microscopy-based high-throughput drug and genomic screening and even in smaller scale microscopy experiments, the objects that most often need to be detected are cells. In order to develop and benchmark algorithms and neural networks that can perform this task, high-quality datasets with annotated cell outlines are needed.
View Article and Find Full Text PDFUtilization of the QuPath open-source software platform for analysis of mammalian spermatogenesis.
Biol Reprod
January 2025
Department of Anatomy and Cell Biology, Brody School of Medicine, East Carolina University, Greenville, NC USA.
The adult mammalian testis is filled with seminiferous tubules, which contain somatic Sertoli cells along with germ cells undergoing all phases of spermatogenesis. During spermatogenesis in postnatal mice, male germ cells undergo at least 17 different nomenclature changes as they proceed through mitosis as spermatogonia (=8), meiosis as spermatocytes (=6), and spermiogenesis as spermatids (=3) [1-6]. Adding to this complexity, combinations of germ cells at each of these stages of development are clumped together along the length of the seminiferous tubules.
View Article and Find Full Text PDFGNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning.
Comput Struct Biotechnol J
December 2024
VISILAB Group, Universidad de Castilla-La Mancha, Av. Camilo José Cela, Ciudad Real, 13071, Ciudad Real, Spain.
The digitalization of traditional glass slide microscopy into whole slide images has opened up new opportunities for pathology, such as the application of artificial intelligence techniques. Specialized software is necessary to visualize and analyze these images. One of these applications is QuPath, a popular bioimage analysis tool.
View Article and Find Full Text PDFBridging the gap: Integrating cutting-edge techniques into biological imaging with deepImageJ.
Biol Imaging
November 2024
Bioengineering Department[CMT1], Universidad Carlos III de Madrid, Leganes, Spain.
This manuscript showcases the latest advancements in deepImageJ, a pivotal Fiji/ImageJ plugin for bioimage analysis in life sciences. The plugin, known for its user-friendly interface, facilitates the application of diverse pre-trained convolutional neural networks to custom data. The manuscript demonstrates several deepImageJ capabilities, particularly in deploying complex pipelines, three-dimensional (3D) image analysis, and processing large images.
View Article and Find Full Text PDFWhat are the important risk factors for excessive daytime sleepiness in a population-based cohort?
J Sleep Res
January 2025
Centre for Sleep and Vigilance Disorders, Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Excessive daytime sleepiness (EDS) is a common complaint in the general population and is associated with cardiovascular disease and increased mortality. We aimed to investigate whether sleep duration is related to excessive daytime sleepiness in the general population, both in itself and in combination with other factors. We performed a cross-sectional analysis in the population-based Swedish CArdioPulmonary bioImage Study (SCAPIS) cohort (n = 27,976; 14,436 females; aged 50-64 years) to assess how sleep-related factors along with anthropometric, lifestyle, socioeconomic factors as well as somatic disease and psychological distress, were related with EDS assessed by the Epworth sleepiness scale (ESS).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!