{"doi":"10.1109/tmi.2024.3494022","title":"A Learnable Prior Improves Inverse Tumor Growth Modeling","abstract":"Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a substantial challenge, either due to the high computational requirements of model-based approaches or the limited robustness of deep learning (DL) methods. We propose a novel framework that leverages the unique strengths of both approaches in a synergistic manner. Our method incorporates a DL ensemble for initial parameter estimation, facilitating efficient downstream evolutionary sampling initialized with this DL-based prior. We showcase the effectiveness of integrating a rapid deep-learning algorithm with a high-precision evolution strategy in estimating brain tumor cell concentrations from magnetic resonance images. The DL-Prior plays a pivotal role, significantly constraining the effective sampling-parameter space. This reduction results in a fivefold convergence acceleration and a Dice-score of 95%.","journal":"IEEE Transactions on Medical Imaging","year":2024,"id":444297,"datarank":0.31191623125197543,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.0,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9498,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":838818,"name":"Ivan Ezhov","orcid":"0000-0002-0862-6513","position":1,"is_corresponding":false},{"id":1196161,"name":"Michał Balcerak","orcid":"0009-0006-3137-7048","position":2,"is_corresponding":false},{"id":1259408,"name":"Marie‐Christin Metz","orcid":"0000-0002-1459-5741","position":3,"is_corresponding":false},{"id":69403,"name":"Sergey Litvinov","orcid":"0000-0002-5999-149X","position":4,"is_corresponding":false},{"id":1259409,"name":"Sebastian Kaltenbach","orcid":"0000-0002-4261-7282","position":5,"is_corresponding":false},{"id":1170007,"name":"Leonhard Feiner","orcid":"0000-0002-5299-7311","position":6,"is_corresponding":false},{"id":1259410,"name":"Laurin Lux","orcid":"0009-0003-7359-6212","position":7,"is_corresponding":false},{"id":64853,"name":"Florian Kofler","orcid":"0000-0003-0642-7884","position":8,"is_corresponding":false},{"id":705452,"name":"Jana Lipková","orcid":"0000-0001-8101-4794","position":9,"is_corresponding":false},{"id":1259411,"name":"Jonas Latz","orcid":"0000-0002-4600-0247","position":10,"is_corresponding":false},{"id":50812,"name":"Daniel Rueckert","orcid":"0000-0002-5683-5889","position":11,"is_corresponding":false},{"id":51419,"name":"Bjoern Menze","orcid":"0000-0003-4136-5690","position":12,"is_corresponding":false},{"id":456131,"name":"Benedikt Wiestler","orcid":"0000-0002-2963-7772","position":13,"is_corresponding":false},{"id":1259407,"name":"Jonas Weidner","orcid":"0009-0003-6784-9738","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:01:33.526738Z","pmid":"38495563","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":[]}