Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues

Journal of Imaging, Journal Year: 2025, Volume and Issue: 11(2), P. 59 - 59

Published: Feb. 15, 2025

Artificial intelligence (AI) transforms image data analysis across many biomedical fields, such as cell biology, radiology, pathology, cancer and immunology, with object detection, feature extraction, classification, segmentation applications. Advancements in deep learning (DL) research have been a critical factor advancing computer techniques for mining. A significant improvement the accuracy of detection algorithms has achieved result emergence open-source software innovative neural network architectures. Automated now enables extraction quantifiable cellular spatial features from microscope images cells tissues, providing insights into organization various diseases. This review aims to examine latest AI DL mining microscopy images, aid biologists who less background knowledge machine (ML), incorporate ML models focus images.

Language: Английский

Comparative Evaluation of Commercial, Freely Available, and Open-Source Tools for Single-Cell Analysis Within Freehand-Defined Histological Brightfield Image Regions of Interest

Technologies, Journal Year: 2025, Volume and Issue: 13(3), P. 110 - 110

Published: March 7, 2025

In the field of histological analysis, one typical issues is analysis single cells contained in regions interest (i.e., ROIs). Today, several commercial, freely available, and open-source software options are accessible for this task. However, literature lacks recent extensive reviews that summarise functionalities opportunities currently available provide guidance on selecting most suitable option analysing specific cases, instance, irregular freehand-defined ROIs brightfield images. work, we reviewed compared 14 tools tailored single-cell within a 2D image ROI. Precisely, six CellProfiler, Cytomine, Digital Slide Archive, Icy, ImageJ/Fiji, QuPath), four Aperio ImageScope, NIS Elements Viewer, Sedeen, SlideViewer), commercial Amira, Arivis, HALO, Imaris) were considered. We focused three key aspects: (a) capacity to handle large file formats such as SVS, DICOM, TIFF, ensuring compatibility with diverse datasets; (b) flexibility defining ROIs, whether through automated extraction or manual delineation, encompassing square, circular, polygonal, freehand shapes accommodate varied research needs; (c) capability classify selected images, ranging from fully semi-automated approaches, requiring different levels user involvement. Thanks deeper understanding strengths limitations platforms emerges, facilitating informed decision making researchers looking tool analyse

Language: Английский

A novel ex vivo protocol that mimics length and excitation changes of human muscles during walking induces force losses in EDL but not in soleus of mdx mice

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0320901 - e0320901

Published: April 7, 2025

Although eccentric contraction protocols are widely used to study the pathophysiology and potential treatments for Duchenne muscular dystrophy (DMD), they do not reflect stresses, strains, strain rates, excitation profiles that DMD muscles experience during human daily functional tasks, like walking. This limitation of contractions may impede our understanding disease progression in proper assessment treatment efficacy. The goals this were examine extent force loss induced by a gait cycling protocol we developed, compare from typical soleus extensor digitorum longus (EDL) mdx mice. To achieve goal, EDL subjected at three levels (10%, 20% 30% optimal length L o ) up 200 cycles mimicked changes patterns corresponding walking gait. Our results showed but had significant losses isometric tetanic forces after protocols. Compared protocol, decrements contractile performance similar those 10% EDL. Together, these indicated is valuable experimental approach better understand screen evaluate efficacy novel therapeutics DMD.

Language: Английский