{"doi":"10.1109/tbme.2021.3113841","title":"Pose Estimation and Non-Rigid Registration for Augmented Reality During Neurosurgery","abstract":"OBJECTIVE: A craniotomy is the removal of a part of the skull to allow surgeons to have access to the brain and treat tumors. When accessing the brain, a tissue deformation occurs and can negatively influence the surgical procedure outcome. In this work, we present a novel Augmented Reality neurosurgical system to superimpose pre-operative 3D meshes derived from MRI onto a view of the brain surface acquired during surgery. METHODS: Our method uses cortical vessels as main features to drive a rigid then non-rigid 3D/2D registration. We first use a feature extractor network to produce probability maps that are fed to a pose estimator network to infer the 6-DoF rigid pose. Then, to account for brain deformation, we add a non-rigid refinement step formulated as a Shape-from-Template problem using physics-based constraints that helps propagate the deformation to sub-cortical level and update tumor location. RESULTS: We tested our method retrospectively on 6 clinical datasets and obtained low pose error, and showed using synthetic dataset that considerable brain shift compensation and low TRE can be achieved at cortical and sub-cortical levels. CONCLUSION: The results show that our solution achieved accuracy below the actual clinical errors demonstrating the feasibility of practical use of our system. SIGNIFICANCE: This work shows that we can provide coherent Augmented Reality visualization of 3D cortical vessels observed through the craniotomy using a single camera view and that cortical vessels provide strong features for performing both rigid and non-rigid registration.","journal":"IEEE Transactions on Biomedical Engineering","year":2021,"id":171121,"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":27,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.958,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":284056,"name":"Parikshit Juvekar","orcid":"0000-0001-7496-7394","position":1,"is_corresponding":false},{"id":705691,"name":"Michael Nercessian","orcid":null,"position":2,"is_corresponding":false},{"id":284059,"name":"William M. Wells","orcid":"0000-0002-4279-8634","position":3,"is_corresponding":false},{"id":273471,"name":"Alexandra J. Golby","orcid":"0000-0001-8461-9561","position":4,"is_corresponding":false},{"id":284057,"name":"Sarah Frisken","orcid":"0000-0001-5731-5095","position":5,"is_corresponding":false},{"id":545986,"name":"Nazim Haouchine","orcid":"0000-0002-1752-3479","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-18T23:46:28.747384Z","pmid":"34543188","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":[]}