Editorial Feature

Optical Imaging: An Overview

Optical imaging uses light to capture images of objects, tissues, or materials for analysis across various applications, including medical diagnostics, materials science, and telecommunications.

Optical Imaging: An Overview

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Fundamentals of Optical Imaging

Optical imaging relies on fundamental light-matter interactions—absorption, reflection, and transmission—to generate images. When light interacts with an object, it can be absorbed and converted into thermal energy or re-emitted as light at a different wavelength.

To harness these interactions for image generation, optical systems incorporate three key components: a light source (e.g., LED or laser) for illumination, specialized filters to selectively transmit specific wavelengths, and a detector to capture and record the resulting light interactions.

However, the choice of components varies by application, such as using infrared light in medical imaging to penetrate tissue or ultraviolet light in microscopy to visualize small cellular structures.1,2

Key Techniques and Technologies in Optical Imaging

Cameras

Cameras are the most common optical imaging technology, capturing and converting light into electronic signals to create images.

Advanced digital cameras employ various sensor technologies, such as complementary metal-oxide-semiconductor (CMOS) and charge-coupled device (CCD), to enhance image quality, sensitivity, and processing speed. These advancements enable high-resolution imaging across diverse applications, from photography to medical diagnostics.

Spectroscopic Imaging

Spectroscopic imaging techniques capture the spectral information of materials for chemical analysis.

For example, Raman spectroscopy utilizes laser light interactions with molecular vibrations to reveal chemical properties. It is crucial for identifying compounds and analyzing materials, including monitoring anesthetic gas mixtures in surgical settings.

Medical Imaging Techniques

Optical medical imaging techniques use non-ionizing radiation, reducing patient exposure to harmful radiation and enabling safe, repeated monitoring of disease progression and treatment outcomes.

For instance, optical coherence tomography (OCT) has revolutionized ophthalmology by offering detailed, non-invasive sub-surface imaging of tissues. This technique emits light into the tissue and measures the reflected light to produce high-resolution cross-sectional images, facilitating precise visualization of internal structures.

Photoacoustic imaging combines optical and acoustic methods, delivering laser pulses to tissues that induce localized heating and expansion, generating detectable acoustic waves for imaging. This technique is particularly useful for assessing tumor blood vessel growth, detecting skin melanomas, and monitoring tissue oxygenation levels.

Diffuse optical tomography (DOT) and imaging (DOI) are non-invasive methods that utilize near-infrared light to assess tissue properties, such as total hemoglobin concentration and blood oxygen saturation. These techniques excel in imaging soft tissues, with applications in breast cancer detection, brain function evaluation, stroke diagnosis, and monitoring therapies like photodynamic and radiation therapy.2

Microscopic Imaging Techniques

Various optical microscopic imaging techniques provide high-resolution imaging at the sub-micron level, enabling detailed visualization of cellular structures and processes.

Fluorescence microscopy utilizes a single objective for illumination and detection, filtering and reflecting excitation light onto the sample. This method allows fluorescent structures in the focal plane to appear with high contrast, although out-of-focus signals may compromise image quality.

Confocal microscopy overcomes this limitation by enabling three-dimensional scanning of specimens while restricting detection to a defined focal plane. This is accomplished using pinhole apertures that exclude out-of-focus light, resulting in higher-resolution images.1,3

Applications of Optical Imaging

Industrial Applications

Optical imaging has become integral to quality control and process optimization in the manufacturing sector. These technologies provide non-contact remote sensing capabilities in challenging environments, offering high-speed responses and exceptional spatial resolution.

Modern manufacturing systems employ optical probes for in-line process control and spectroscopic analysis, while optical metrology techniques ensure precise control over critical dimensions and layouts.4

Medical Applications

Optical imaging has transformed medical diagnostics by providing non-invasive techniques to visualize internal structures and monitor diseases. It helps track disease progression and treatment efficacy in conditions such as cancer, neurological disorders, and cardiovascular diseases.

Recent technological advancements have enabled in vivo imaging of protein stability regulated by the ubiquitin-proteasome system, offering insights into cellular processes and potential therapeutic targets for cancer.5

Agricultural Applications

The agricultural sector has embraced optical imaging as a powerful tool for crop management and disease detection. Recent studies have demonstrated remarkable success in identifying rot diseases in mangoes with up to 98 % accuracy, while multispectral imaging has proven effective in predicting botrytis bunch rot in grapevines.

Combined with unmanned aerial vehicles (UAVs), these imaging techniques facilitate scalable crop monitoring, reducing reliance on manual labor and enabling more precise and timely interventions in crop management.6

Recent Research and Developments

Recent advancements have improved optical imaging capabilities, enhancing resolution, speed, and digital integration.

Imaging Invisible Objects

Conventional cameras struggle to capture transparent objects due to the absence of phase information. Recent breakthroughs have introduced diffractive imagers that convert phase information into amplitude data, allowing standard cameras to image transparent materials without complex post-processing.

This technology leverages self-interference patterns and machine learning to optimize the imaging process.7

High-Speed 3D Imaging Systems

Topographic optical imaging at the microscale is essential for industrial and scientific applications, including optical inspection in production lines, 3D surface measurement of biomaterials, and metrology of additively manufactured parts. However, generating topography maps from sequential z-stack images can be slow, particularly for large objects or high-resolution needs, limiting effectiveness in dynamic environments.

Recently, researchers at the University of Barcelona developed a high-resolution optical profilometry system that captures 3D images rapidly. The results are published in Nature Communications.

The team employed synchronized pulsed light and a rapid scanning technique to achieve up to 67 measurements per second. The system reduces the required images for accurate analysis from hundreds to eight by simultaneously interrogating multiple planes, enhancing the characterization of dynamic processes like gas sensor behavior.8

AI-Enhanced Optical Imaging Systems

Integrating AI and optical imaging has improved diagnostic precision, enabling faster and more accurate analyses of cellular structures.

A recent study proposed ultrahigh-resolution imaging systems that complete high-precision scans in just 10 seconds, generating detailed cellular images. The researchers employed DeepTree, a deep-learning architecture, to automate tasks such as cell counting and morphology analysis, freeing pathologists from repetitive tasks and enhancing efficiency.

This advancement is crucial for meeting the demands of major hospitals that process up to 5,000 pathology slides daily while addressing disparities in medical resource distribution nationwide.9

Conclusion

As optical imaging technologies advance and become more accessible, their growing impact on research, healthcare, and industrial applications will facilitate discoveries and enhance our ability to visualize and understand the world around us.

More from AZoOptics: Exploring Ultra-Lightweight Space Cameras for Space Missions

References and Further Reading

  1. Lin, L. et al. (2021). Fundamentals of Optical Imaging. Optical Imaging in Human Disease and Biological Research. https://doi.org/10.1007/978-981-15-7627-0_1
  2. NIBIB. (2020). Optical Imaging. [Online] NIBIB. Available at: https://www.nibib.nih.gov/science-education/science-topics/optical-imaging
  3. Elliott AD. (2020). Confocal Microscopy: Principles and Modern Practices. Current protocols in cytometry. https://doi.org/10.1002/cpcy.68
  4. Kuchimaru, T., Suka, T., Hirota, K., Kadonosono, T. (2016). A novel injectable BRET-based in vivo imaging probe for detecting the activity of hypoxia-inducible factor regulated by the ubiquitin-proteasome system. Scientific Reports. https://doi.org/10.1038/srep34311
  5. Archenti, A., Gao, W., Donmez, A., Savio, E., Irino, N. (2023). Integrated metrology for advanced manufacturing. CIRP Annals. https://doi.org/10.1016/j.cirp.2024.05.003
  6. Eh Teet, S., Hashim, N. (2023). Recent advances of application of optical imaging techniques for disease detection in fruits and vegetables: A review. Food Control. https://doi.org/10.1016/j.foodcont.2023.109849
  7. Nape, I., Forbes, A. (2024). Seeing invisible objects with intelligent optics. Light: Science & Applications. https://doi.org/10.1038/s41377-024-01575-2
  8. Vilar, N., Artigas, R., Duocastella, M., Carles, G. (2024). Fast topographic optical imaging using encoded search focal scan. Nature Communications. https://doi.org/10.1038/s41467-024-46267-y
  9. Nature Research Media. (2023). With digital and AI tech, pathology eyes the future. [Online] Nature Research Media. Available at: https://www.nature.com/articles/d42473-024-00056-9

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Owais Ali

Written by

Owais Ali

NEBOSH certified Mechanical Engineer with 3 years of experience as a technical writer and editor. Owais is interested in occupational health and safety, computer hardware, industrial and mobile robotics. During his academic career, Owais worked on several research projects regarding mobile robots, notably the Autonomous Fire Fighting Mobile Robot. The designed mobile robot could navigate, detect and extinguish fire autonomously. Arduino Uno was used as the microcontroller to control the flame sensors' input and output of the flame extinguisher. Apart from his professional life, Owais is an avid book reader and a huge computer technology enthusiast and likes to keep himself updated regarding developments in the computer industry.

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