Cone-beam computed tomography, or CBCT, has become a cornerstone of modern dental and maxillofacial imaging. It offers high-resolution 3D views of anatomical structures, enabling precise diagnostics and treatment planning. But behind every crisp image lies a complex journey of data transformation. To truly appreciate CBCT’s power, it helps to understand the different types of data involved—raw data, raw DICOM data, and processed DICOM data.
What is raw data in CBCT
Raw data refers to the original measurements collected by the CBCT detector during the scan. These are not images yet. Instead, they are numerical values that represent how much X-ray radiation was absorbed by the tissues at various angles. This data is often called projection data or sinogram data.
Imagine shining a flashlight through a sculpture from different directions and recording how much light comes out the other side. Each measurement gives you a clue about the internal structure. Raw CBCT data is essentially a collection of these clues. It needs to be reconstructed using mathematical algorithms like filtered back projection or iterative reconstruction to become a usable image.
Raw data is typically stored in proprietary formats and is not viewable in standard imaging software. It is used by engineers and physicists to develop or refine reconstruction algorithms. In clinical practice, raw data is rarely accessed directly, but it is the foundation of every CBCT image.
What is raw DICOM data
Once the raw projection data is reconstructed into image slices, it is often saved in the DICOM format. DICOM stands for Digital Imaging and Communications in Medicine. It is a standardized format that includes both the image data and metadata such as patient information, scan parameters, and equipment details.
Raw DICOM data refers to the reconstructed image slices that have not undergone any additional post-processing. These images are typically high-resolution and retain the full detail captured during the scan. They are ideal for advanced analysis, segmentation, and 3D modeling.
Raw DICOM images typically retain the original bit depth from the scanner, often 12-bit or 16-bit grayscale. This means each pixel can represent thousands of shades of gray, allowing for subtle differences in tissue density to be visualized. In CBCT, this is especially important for identifying fine anatomical structures, evaluating bone quality, or segmenting soft tissues like the TMJ disc.
In software like 3D Slicer, raw DICOM data is preferred because it allows for accurate visualization and manipulation of anatomical structures. It is the closest representation of the original anatomy, reconstructed from raw measurements but not yet altered or enhanced.
What is processed DICOM data
Processed DICOM data refers to image slices that have undergone additional modifications after reconstruction. These modifications can include metal artifact reduction, noise suppression, contrast enhancement, or resampling to lower resolution.
Processed DICOM images, on the other hand, are often resampled or compressed for easier viewing or sharing. This can reduce the bit depth to 8-bit grayscale, which limits each pixel to just 256 shades of gray. While this is sufficient for general viewing, it can obscure fine details and reduce diagnostic accuracy. Metal artifact reduction, smoothing filters, or contrast enhancement may also alter pixel values, further distancing the image from its original fidelity.
Processed dicom data might not refere to reduced data size or reduction in pixel depth. It can be even mild alteration in the raw data for a specific need without effecting the other parameters.
Metal artifact reduction is a common form of post-processing in dental CBCT. When metallic objects like implants or fillings are present, they can cause streaks or distortions in the image. Specialized algorithms are used to reduce these artifacts and improve image clarity. The resulting images are easier to interpret but may lose some of the original detail.
Other forms of processing include smoothing filters to reduce graininess, sharpening filters to enhance edges, and resampling to make the data more manageable for viewing on standard monitors. While processed DICOM data is useful for quick review and presentation, it may not be suitable for precise measurements or advanced analysis.
Why the distinction matters?
Understanding the difference between raw data, raw DICOM data, and processed DICOM data is essential for clinicians, researchers, and engineers. Raw data is the starting point for reconstruction. Raw DICOM data is the unaltered output of that reconstruction. Processed DICOM data is optimized for readability but may sacrifice accuracy.
For clinical decisions, raw DICOM data offers the most faithful representation of the anatomy. For presentations or patient communication, processed DICOM data may be more visually appealing.
For algorithm development or research, raw projection data provides the deepest insight into the imaging process.
How many types of post processing are there in cbct?
The types of post-processing applied to CBCT data can vary depending on the clinical goal, the software used, and the anatomical region being studied. Here’s a comprehensive overview of the major categories:
- Metal artifact reduction
This is one of the most critical post-processing steps in dental CBCT. It reduces streaks and distortions caused by metallic restorations, implants, or orthodontic appliances. Algorithms like blooming artifact reduction or iterative MAR techniques help restore image clarity around metal. - Noise reduction and smoothing
These filters reduce graininess in the image, especially in low-dose scans. While they improve visual aesthetics, they can sometimes blur fine anatomical details, so they must be used judiciously. - Contrast enhancement
This improves the visibility of soft tissues or bone structures by adjusting the grayscale mapping. It’s useful for highlighting specific regions but may alter the original pixel values. - Multiplanar reconstruction (MPR)
This allows the raw volumetric data to be reformatted into axial, coronal, sagittal, or oblique slices. It’s foundational for diagnostic review and surgical planning. - Panoramic and curved planar reformation
Used to generate panoramic views of the dental arch or follow curved anatomical paths like the mandibular canal. These are especially useful in implantology and orthodontics. - 3D volume rendering
This creates a 3D visual model from the CBCT data, often used for patient education, surgical simulation, or export to 3D printing workflows. - Segmentation and annotation
Post-processing may include semi-automated or manual segmentation of anatomical structures like the TMJ disc, sinus cavities, or nerve canals. These are essential for research, planning, and quantitative analysis. - Registration and fusion
CBCT data can be aligned with other imaging modalities like MRI or intraoral scans. This fusion enables comprehensive diagnostics and treatment planning. - Resampling and compression
To reduce file size or adapt to display limitations, CBCT volumes may be resampled to lower resolution or compressed. This is common in processed DICOM exports but can affect diagnostic fidelity. - Texture enhancement and sharpening
Advanced algorithms may enhance edges or textures to improve visibility of fine structures. These are often used in software tailored for endodontics or bone density analysis.
Conclusion
In a world where imaging guides diagnosis, surgery, and treatment planning, knowing what kind of data you are working with is not just technical—it is foundational to quality care.
Raw DICOM preserves original reconstructed detail and full dynamic range, typically used for advanced planning or 3D processing. Processed DICOM is optimized for convenience, reduced file size, or specific diagnostic tasks, but may lose some detail due to resampling, filtering, or reduced dynamic range.
With over a decade of experience in dentistry, I specialize in diagnosing a wide range of oral diseases and have developed a deep passion for dental imaging. My interest in CBCT reporting and digital implantology led me to become a pioneer in the concept of diagnostic 3D modelling. Throughout my career, I have supported and educated numerous dentists in mastering CBCT interpretation, virtual implant planning, and the latest advancements in 3D printing for dental applications. Read more about me on the “about me” page.
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