import_pentacam : Open-Source OCR Recovery of Corneal Tomography Measurements From Pentacam DICOM, PDF, and Image Archives

Purpose: Pentacam corneal tomography data accumulate in clinical Digital Imaging and Communications in Medicine (DICOM) archives as embedded portable document format (PDF) printouts and proprietary binary readouts rather than structured records; the device's comma-separated values (CSV) export is impractical for retrospective multisite use. We describe an open-source pipeline that recovers structured Pentacam measurements from archives. Methods: import_pentacam is an open-source Rust tool that extracts up to 66 numerical fields and embedded corneal-map images per examination from DICOM, PDF, or image inputs, with single-file, file-list, and recursive picture archiving and communication system (PACS) directory modes supporting continuous incremental updates. Cross-firmware layout variation is normalized by affine transforms onto printout templates. The pipeline was developed on 300 examinations across three printout types and evaluated on a 200-examination holdout; Belin/Ambrósio Ectasia was added as a new printout type without retraining and tested on 333 examinations. Ground truth was derived from automated annotators with manual review of disagreements. Results: Field-level accuracy was 99.46% on training, 98.70% on the holdout, and 99.03% on the Belin/Ambrósio corpus. Agreement with paired DICOM Structured Reports was 100% on 518 fields. Institutional deployment recovered 126,184 eye visits from 29,550 patients across an 18-year archive. Conclusions: Automated recovery of structured Pentacam data from clinical DICOM archives is feasible at large multisite institutional scale. The software supports continuous incremental updates and is deployable at other Pentacam-equipped institutions for longitudinal ectasia research. Translational Relevance: Routinely collected institutional Pentacam examinations are a substantial resource for longitudinal corneal tomography research. This pipeline converts that resource into structured data without disrupting clinical workflows, enabling continuously updated retrospective cohorts and federated extraction across institutions.

Authors

Institutions

Publication Details

Journal
Translational Vision Science & Technology
Published
2026-10-27
DOI
https://doi.org/10.1167/tvst.15.10.46
Primary Topic
Electronic Health Records Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

import_pentacam : Open-Source OCR Recovery of Corneal Tomography Measurements From Pentacam DICOM, PDF, and Image Archives

Tobias Elze, Katerina Kiroshka
Translational Vision Science & Technology
Electronic Health Records Systems
article

import_pentacam : Open-Source OCR Recovery of Corneal Tomography Measurements From Pentacam DICOM, PDF, and Image Archives

Tobias Elze, Katerina Kiroshka
article en

Abstract

Purpose: Pentacam corneal tomography data accumulate in clinical Digital Imaging and Communications in Medicine (DICOM) archives as embedded portable document format (PDF) printouts and proprietary binary readouts rather than structured records; the device's comma-separated values (CSV) export is impractical for retrospective multisite use. We describe an open-source pipeline that recovers structured Pentacam measurements from archives. Methods: import_pentacam is an open-source Rust tool that extracts up to 66 numerical fields and embedded corneal-map images per examination from DICOM, PDF, or image inputs, with single-file, file-list, and recursive picture archiving and communication system (PACS) directory modes supporting continuous incremental updates. Cross-firmware layout variation is normalized by affine transforms onto printout templates. The pipeline was developed on 300 examinations across three printout types and evaluated on a 200-examination holdout; Belin/Ambrósio Ectasia was added as a new printout type without retraining and tested on 333 examinations. Ground truth was derived from automated annotators with manual review of disagreements. Results: Field-level accuracy was 99.46% on training, 98.70% on the holdout, and 99.03% on the Belin/Ambrósio corpus. Agreement with paired DICOM Structured Reports was 100% on 518 fields. Institutional deployment recovered 126,184 eye visits from 29,550 patients across an 18-year archive. Conclusions: Automated recovery of structured Pentacam data from clinical DICOM archives is feasible at large multisite institutional scale. The software supports continuous incremental updates and is deployable at other Pentacam-equipped institutions for longitudinal ectasia research. Translational Relevance: Routinely collected institutional Pentacam examinations are a substantial resource for longitudinal corneal tomography research. This pipeline converts that resource into structured data without disrupting clinical workflows, enabling continuously updated retrospective cohorts and federated extraction across institutions.

Translational Vision Science & TechnologyVol. 15(10)
Massachusetts Eye and Ear Infirmary (US), Harvard University (US), Barzilai Medical Center (IL)
Openalex Percentile: Top 8%
Electronic Health Records Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon