ArticleInternational journal of computer assisted radiology and surgery2021
Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern.
Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05110677 (Pilot Study of Topographic Imaging of the Gastrocnemius Muscle in Patients With PAD Using Non-invasive Multispectral Optoacoustic Tomography), which is not on this map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Pilot Study of Topographic Imaging of the Gastrocnemius Muscle in Patients With PAD Using Non-invasive Multispectral Optoacoustic Tomography (MSOT) as a 3D Reconstruction Based on Longitudinal 2D Measurements
Who cites it
5 citing papers in PubMed.
- Motion score for spectral quality control of optoacoustic-ultrasound data.Scientific reports · 2026Article
- Review of Three-Dimensional Handheld Photoacoustic and Ultrasound Imaging Systems and Their Applications.Sensors (Basel, Switzerland) · 2023Review
- Visual inertial odometry enabled 3D ultrasound and photoacoustic imaging.Biomedical optics express · 2023Article
- LED-based photoacoustic imaging for preoperative visualization of lymphatic vessels in patients with secondary limb lymphedema.Photoacoustics · 2023Article
- Semantic segmentation of multispectral photoacoustic images using deep learning.Photoacoustics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposePhotoacoustic tomography (PAT) is a novel imaging technique that can spatially resolve both morphological and functional tissue properties, such as vessel topology and tissue oxygenation. While this capacity makes PAT a promising modality for the diagnosis, treatment, and follow-up of various diseases, a current drawback is the limited field of view provided by the conventionally applied 2D probes.
methodsIn this paper, we present a novel approach to 3D reconstruction of PAT data (Tattoo tomography) that does not require an external tracking system and can smoothly be integrated into clinical workflows. It is based on an optical pattern placed on the region of interest prior to image acquisition. This pattern is designed in a way that a single tomographic image of it enables the recovery of the probe pose relative to the coordinate system of the pattern, which serves as a global coordinate system for image compounding.
resultsTo investigate the feasibility of Tattoo tomography, we assessed the quality of 3D image reconstruction with experimental phantom data and in vivo forearm data. The results obtained with our prototype indicate that the Tattoo method enables the accurate and precise 3D reconstruction of PAT data and may be better suited for this task than the baseline method using optical tracking.
conclusionsIn contrast to previous approaches to 3D ultrasound (US) or PAT reconstruction, the Tattoo approach neither requires complex external hardware nor training data acquired for a specific application. It could thus become a valuable tool for clinical freehand PAT.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.