The technique at the heart of the story is X-ray computed tomography, or XCT, the same fundamental technology used in hospitals to image the human body. When a drill core arrives on the Chikyu’s core processing deck, it is loaded into an onboard medical-grade scanner, a Revolution Frontier VT1700 built by GE HealthCare. The machine rotates an X-ray source around the section and reconstructs a three-dimensional map of how strongly the material attenuates X-rays. Because attenuation depends on both density and elemental composition, the resulting images reveal features that are completely invisible from the outside: burrows left by seafloor organisms, the sharp bases of turbidite deposits, subtle faults and deformation bands, and even the ghostly outlines of gas-filled voids.

Physically, the scanner reconstructs the distribution of the linear attenuation coefficient, conventionally expressed as CT numbers in Hounsfield units, a scale on which water registers zero and air registers minus one thousand. Dense minerals or materials rich in heavy elements produce high values, so discontinuities defined by density contrasts pop out of the images. The Chikyu scanner produces two-dimensional slices of 512 by 512 pixels across a 90-millimetre field of view, giving a resolution of about 0.176 millimetres within each slice, with slices spaced 0.625 millimetres apart. A full-length core section of roughly 1.4 metres therefore consists of some 2,200 to 2,300 individual slices, each saved as a DICOM file — the standard format of medical imaging. The scanner is calibrated every 24 hours using mock-ups of air, water, and aluminium to keep the numbers honest.

Here lies the paradox that motivated the new study, led by Hanaya Okuda of the Japan Agency for Marine-Earth Science and Technology together with colleagues in Austria and France. Although XCT scanning is one of the very first measurements performed on every core, and although it captures the most complete and continuous record of the material before anything is cut away, the data were largely going to waste. The DICOM files are enormous — typically more than a gigabyte per section — the viewing software is unfamiliar to most geologists, and only a handful of dedicated computers on the vessel could even open them. As a result, the scans were consulted almost exclusively by designated watchdog scientists whose job was to flag intervals for time-sensitive whole-round sampling, such as interstitial water squeezing or microbiology work, before the core warmed and its chemistry drifted.

Okuda and her team, including Charlotte Pizer and Michael Strasser of the University of Innsbruck and Mai-Linh Doan of Université Grenoble Alpes, set out to democratize that data. They built a Python-based visualization workflow that runs on the ship’s existing computers and converts the raw DICOM stacks into a family of accessible images that any shipboard scientist can consult within minutes. From each three-dimensional section volume, the workflow generates four image types: slices along the split surfaces of both the archive half and the working half, a slice perpendicular to the split surface that reveals structures hiding beneath it, and an unwrapped image produced by sampling the volume along a circular path of about 22.5 millimetres diameter centred on the core axis — effectively flattening the curved outer surface of the core into a single panoramic strip, a scheme adapted from methodology developed during IODP Expedition 405.

Alongside the images, the workflow computes a depth profile of CT numbers by averaging pixel values within a 40-millimetre-diameter circular area, counting only voxels above 1,200 Hounsfield units to exclude liner material and air. These parameters can be tuned manually for different lithologies, and the profiles are exported both as images and as CSV files for quantitative analysis. The individual products are then assembled into three nested summaries. A section summary lines up all five products for one core section, ideal for pinpointing undisturbed, representative spots for sampling. A core summary aligns one image type across every section of a core, directly mirroring what scientists see on the core description tables. Finally, a hole summary stacks every core in the borehole into a continuous downhole image, generated for both of the programme’s depth scales, CSF-A and CSF-B, and vertically compressed to one-third length for the downhole views.

The practical payoff is immediate and concrete. A physical properties specialist hunting for a crack-free cube of sediment for P-wave velocity measurements can scan the perpendicular slice to dodge fractures that would sabotage the measurement. Sedimentologists describing the archive half can compare their observations against the split-surface images to spot burrows and event deposits that a knife might smear. Structural geologists can trace faults through the working half before sampling destroys the context. And because the summaries are saved on a local computer accessible to everyone, scientists on any shift, in any science team, can generate them independently rather than queuing for the few machines equipped with DICOM viewers.

Getting the software to run smoothly on a research vessel posed its own engineering challenges. The team chose a Mac mini running the open-source Horos DICOM viewer as the processing host, because Horos offers prompt access to the shipboard XCT server and can export data easily, unlike the locked-down Advanced Workstation used for watchdog duties. They also decompress the DICOM files into the standard uncompressed Explicit VR Little Endian format, ensuring the archives remain usable in post-cruise research with tools such as ImageJ. To sidestep the notorious difficulty of configuring Python environments on shipboard machines, the entire workflow is packaged in a Docker container — a self-contained digital ecosystem that can be deployed on any computer running the free Docker software. The code reads each section’s 18-digit J-CORES identification number, builds a look-up table automatically, and processes more than 2,000 DICOM files per section in parallel across all processor cores, finishing in a few minutes; the downhole summaries take about one minute each.

The workflow was implemented and tested during IODP³ Expeditions 502 and 503, and while the summaries cannot yet be produced before time-sensitive whole-round sampling — not all sections have been scanned by that point — they are ready well before non-time-sensitive sampling, section splitting, and visual core description begin. The authors are candid about the method’s limits: slicing a three-dimensional volume along fixed planes inevitably misses some structures, so an irregular, subvertical feature such as an injection structure near the core’s outer edge could escape detection. They therefore recommend complementing the summaries with examination in a full three-dimensional DICOM viewer. Looking ahead, they envision direct comparison of the unwrapped images with borehole logging data, and the integration of machine-learning techniques to automatically detect key features, potentially fusing XCT data with continuous core scan images and other track measurements for an unprecedented real-time picture of what the drill has recovered.

What makes this development resonate beyond one ship is its philosophy. The Chikyu’s scanner was already producing world-class data on every expedition; the bottleneck was not instrumentation but accessibility. By wrapping a robust visualization pipeline in a portable container and publishing both the Docker image and the Python scripts openly, the team has shown how a modest investment in software can multiply the scientific return of expensive, hard-won samples drilled from the seafloor. The same strategy, the authors note, can be transferred to any laboratory working with drill cores, promising rapid and consistent visualization of large tomographic datasets wherever scientists interrogate the Earth’s buried archives.

Subject of Research: Non-destructive X-ray computed tomography visualization of drill cores and its integration into the shipboard core workflow on the drilling vessel Chikyu

Article Title: Non-destructive core visualization using X-ray computed tomography scan and its implementation into the core workflow on D/V Chikyu

Article References: Okuda, H., Pizer, C., Doan, M.-L., & Strasser, M. (2026). Non-destructive core visualization using X-ray computed tomography scan and its implementation into the core workflow on D/V Chikyu. Scientific Drilling, 35(1), 119-125. https://doi.org/10.5194/sd-35-119-2026

Image Credits: AI Generated

DOI: 10.5194/sd-35-119-2026

Keywords: X-ray computed tomography, drill cores, D/V Chikyu, IODP, scientific drilling, DICOM, core visualization, Python workflow, Docker, marine geology, shipboard science, JAMSTEC