Depth of Field: Understanding Image Clarity (Part 2)

Image clarity is how well an imaging system can accurately reproduce the details and features of its scene. Clarity represents the overall quality and sharpness of an image. Surgeons rely on exceptional image clarity to visualize minute biological features in tissues and organs, which inherently possess depth, curvature, and varying surface topography.

In our previous article, "Resolution: Understanding Image Clarity (Part 1)," we explored the foundations of image resolution. Now in Part 2, we examine depth of field (DoF) - the range of distances over which features remain in clear focus. This characteristic is particularly crucial in surgical imaging because biological surfaces are rarely flat, and maintaining clarity across varying tissue depths can dramatically impact surgical precision.

The Challenge of Depth of Field

Imagine staring at something so closely that you miss the big picture. That is akin to having a shallow depth of field. Achieving optimal image quality requires careful balancing of multiple factors. While high resolution might seem like the ultimate goal, imaging system design involves fundamental trade-offs that affect overall performance. When we adjust one parameter to improve resolution, we often impact other crucial aspects of image quality, such as signal-to-noise and depth of field.

For instance, opening the camera's aperture allows more light to reach the sensor, which can help capture dimly lit features. However, this same adjustment reduces depth of field, meaning fewer objects remain in sharp focus. Conversely, closing the aperture extends depth of field but reduces the amount of light collected, potentially making the image too dark to be useful.

Magnification presents similar challenges. Higher magnification can reveal finer details, but it typically results in a shorter depth of field and requires more light to maintain image brightness. These relationships stem from fundamental properties of light and optics, making them unavoidable constraints that engineers must work within.

The key to successful imaging system design lies in understanding these trade-offs and optimizing them for specific applications. Rather than pursuing maximum resolution at all costs, designers must carefully consider the intended use case and balance these competing factors accordingly.

Also important to note is that many fluorescence imaging systems contain two cameras - one to detect visible light and one to detect near infrared light. There may be trade-offs in system performance between these two cameras, such as decreased fluorescence sensitivity to increase visible optical resolution.

Characterizing Your System’s Depth of Field 

By analyzing the fluorescence signal at different heights, one can determine the range over which the system maintains adequate focus, which gives the DoF. To measure the depth of field, follow the steps for Characterizing Your System’s Resolution while systematically changing the working distance, this is the distances between the imaging system and the reference target. 

1. Position the resolution target at the imaging system's fixed focus height.
2. Focus the imaging system on the target.
3. Perform “Characterizing Your System’s Resolution” (previous article) at this height. You can use the QUEL-QAL Python library to help automate the process.
4. Position the target at incremental heights above and below the initial focus plane to create different 'offsets'. Repeat Steps 2-4.
5. At a given position, the contrast can be determined for a range of image resolutions (line pairs per mm), as shown in the left graph, below.
6. To characterize your Depth of Field, choose a specific Group and Element appropriate for your application. For this one element, plot the contrast vs offset.
7. Determine the height range over which the system maintains adequate focus for your desired level of sharpness; this is the DoF, as shown in the right graph, below.

Check out the Use Guide: Fluorescence Resolution Targets for tips.

Best Practices for Development

Understanding and correctly measuring depth of field is crucial for developing effective imaging systems. While the underlying physics can be complex, focusing on practical measurements and real-world performance will help ensure your system meets clinical needs:

• What anatomical structures need to be simultaneously in focus? Consider whether you need to visualize structures at different depths concurrently or if sequential focusing is acceptable.
• Do you need real-time adjustment of focus during the procedure? Consider whether surgeons need to dynamically change focus depths during the operation.
• How will patient motion affect your imaging requirements? Breathing, pulse, and other physiological movements may require greater depth of field to maintain structures in focus.
• What are your aperture and illumination trade-offs? Smaller apertures increase depth of field but require more light, creating a delicate balance—stronger illumination allows for smaller apertures (greater depth of field) but risks photobleaching or tissue damage, while larger apertures collect more light but reduce depth of field.

Test your system using the same settings (camera exposure time, camera gain, working distance, ambient lighting conditions, etc.) that will be used in clinical practice. If your system has different operating modes, characterize each one separately. By understanding these principles and following proper testing procedures, you'll be better equipped to develop and validate your fluorescence imaging system's depth of field.

For more detailed guidance on system characterization and standardization, refer to the AAPM TG311 guidelines. Implementation tools and reference targets are available to help you meet these standards effectively.

Interested in characterizing your imaging system or developing a customized fluorescence reference target? Contact QUEL Imaging!