{"doi":"10.1109/ismr48331.2020.9312944","title":"Pose-aware C-Arm Calibration and Image Distortion Correction for Guidewire Tracking and Image Reconstruction","abstract":"Image intensifiers, also known as C-arms, are important and low-cost tools for surgeons to guide minimally-invasive procedures. However, image intensifiers suffer from several distortions that can impede their ability to provide accurate guidance. These distortions can be misleading during an automated minimally-invasive surgery where the accurate shape-estimation of the robot is essential. Since the distortion strongly depends on the orientation of the C-arm during image acquisition, we propose an approach for distortion correction in combination with a calibration procedure to precisely estimate its orientation. To estimate an accurate distortion correction function, we take images of a calibration grid in 258 different C-arm orientations and apply polynomial regression on these images. The C-arm is calibrated using an external camera along with optical flow and point-correspondence-based matching to allow sufficient pose estimation. Our C-arm tracking algorithm estimates the pose of the C-arm with a mean absolute deviation of 0.2° and 0.3° for 5° and 10° relative motion. The proposed C-arm calibration procedure allows the positioning of the C-arm within an error range of 0.5°. The resulting distortion correction leads to a mean pixel displacement of 0.30 pixel.","journal":null,"year":2020,"id":120597,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9575,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":299941,"name":"Anirudh Choudhary","orcid":null,"position":1,"is_corresponding":false},{"id":311569,"name":"Jaydev P. Desai","orcid":"0000-0001-8298-2439","position":2,"is_corresponding":false},{"id":558591,"name":"Florian Heemeyer","orcid":"0000-0001-6069-4487","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-18T23:14:38.147936Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}