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Machine learning-based controllers are promising to help master this task. However, human-generated training data are scarce and resource-intensive to generate. We investigate if a neural network-based controller trained without human-generated data can learn human-like behaviors.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We trained and evaluated a neural network-based controller via deep reinforcement learning in a finite element simulation to navigate the venous system of a porcine liver without human-generated data. The behavior is compared to manual expert navigation, and real-world transferability is evaluated.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The controller achieves a success rate of 100% in simulation. The controller applies a wiggling behavior, where the guidewire tip is continuously rotated alternately clockwise and counterclockwise like the human expert applies. In the ex vivo porcine liver, the success rate drops to 30%, because either the wrong branch is probed, or the guidewire becomes entangled.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>In this work, we prove that a learning-based controller is capable of learning human-like guidewire navigation behavior without human-generated data, therefore, mitigating the requirement to produce resource-intensive human-generated training data. Limitations are the restriction to one vessel geometry, the neglected safeness of navigation, and the reduced transferability to the real world.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11548-022-02646-8","type":"journal-article","created":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T13:04:34Z","timestamp":1653311074000},"page":"2033-2040","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Learning-based autonomous vascular guidewire navigation without human demonstration in the venous system of a porcine liver"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2162-3680","authenticated-orcid":false,"given":"Lennart","family":"Karstensen","sequence":"first","affiliation":[]},{"given":"Jacqueline","family":"Ritter","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3152-7791","authenticated-orcid":false,"given":"Johannes","family":"Hatzl","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1071-1220","authenticated-orcid":false,"given":"Torben","family":"P\u00e4tz","sequence":"additional","affiliation":[]},{"given":"Jens","family":"Langej\u00fcrgen","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Uhl","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5239-5305","authenticated-orcid":false,"given":"Franziska","family":"Mathis-Ullrich","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,23]]},"reference":[{"key":"2646_CR1","doi-asserted-by":"publisher","unstructured":"GBD 2015 Risk Factors Collaborators (2016) Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990\u20132015: a systematic analysis for the Global Burden of Disease Study 2015. 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Specimen from porcine offal, for which ethics approval was not required, was used for this study.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"This article does not contain patient data.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}