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

被引：7

作者：

Ali, Muhammad ^{[1
,2
]}

Benfante, Viviana ^{[2
,3
,4
]}

Basirinia, Ghazal ^{[1
,2
]}

Alongi, Pierpaolo ^{[3
,5
]}

Sperandeo, Alessandro ^{[4
]}

Quattrocchi, Alberto ^{[6
]}

Giannone, Antonino Giulio ^{[6
]}

Cabibi, Daniela ^{[6
]}

Yezzi, Anthony ^{[7
]}

Di Raimondo, Domenico ^{[2
]}

Tuttolomondo, Antonino ^{[2
]}

Comelli, Albert ^{[1
]}

机构：

[1] Ri MED Fdn, Via Bandiera 11, I-90133 Palermo, Italy

[2] Univ Palermo, Dept Hlth Promot Mother & Child Care, Internal Med & Med Specialties, I-90127 Palermo, Italy

[3] ARNAS Civ Cristina & Benfratelli Hosp, Dept Radiol Sci, Adv Diagnost Imaging INNOVA Project, Pzza N Leotta 4, I-90127 Palermo, Italy

[4] La Maddalena SPA, Pharmaceut Factory, Via San Lorenzo Colli,312-d, I-90146 Palermo, Italy

[5] Univ Palermo, Dept Biomed Neurosci & Adv Diagnost BIND, I-90127 Palermo, Italy

[6] Univ Palermo, Dept Hlth Promot Mother & Child Care Internal Med, Pathol Anat Unit, I-90127 Palermo, Italy

[7] Georgia Inst Technol, Dept Elect & Comp Engn, Atlanta, GA 30332 USA

来源：

JOURNAL OF IMAGING | 2025年 / 11卷 / 02期

关键词：

artificial intelligence; deep learning; machine learning; microscopic images; cell; detection; segmentation; contouring; biomedical fields; PROCESS ANALYTICAL TECHNOLOGY; CNN; SEGMENTATION; ENHANCEMENT;

D O I：

10.3390/jimaging11020059

中图分类号：

TB8 [摄影技术];

学科分类号：

0804 ;

摘要：

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

引用

页数：42

共 196 条

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