AUTOMATIC PLANNING AND GUIDANCE OF LIVER TUMOR THERMAL ABLATION USING AI AGENTS TRAINED WITH DEEP REINFORCEMENT LEARNING
Systems and methods for determining an optimal position of one or more ablation electrodes are provided. A current state of an environment is defined based on a mask of one or more anatomical objects and one or more current positions of one or more ablation electrodes. The one or more anatomical obj...
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Format | Patent |
Language | English |
Published |
11.04.2024
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Abstract | Systems and methods for determining an optimal position of one or more ablation electrodes are provided. A current state of an environment is defined based on a mask of one or more anatomical objects and one or more current positions of one or more ablation electrodes. The one or more anatomical objects comprise one or more tumors. For each particular AI (artificial intelligence) agent of one or more AI agents, one or more actions for updating the one or more current positions of a respective ablation electrode of the one or more ablation electrodes in the environment are determined based on the current state using the particular AI agent. A next state of the environment is defined based on the mask and the one or more updated positions of the respective ablation electrode. The steps of determining the one or more actions and defining the next state are repeated for a plurality of iterations using 1) the next state as the current state and 2) the one or more updated positions as the one or more current positions to determine one or more final positions of the respective ablation electrode for performing a thermal ablation on the one or more tumors. The one or more final positions of each respective ablation electrode are output. |
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AbstractList | Systems and methods for determining an optimal position of one or more ablation electrodes are provided. A current state of an environment is defined based on a mask of one or more anatomical objects and one or more current positions of one or more ablation electrodes. The one or more anatomical objects comprise one or more tumors. For each particular AI (artificial intelligence) agent of one or more AI agents, one or more actions for updating the one or more current positions of a respective ablation electrode of the one or more ablation electrodes in the environment are determined based on the current state using the particular AI agent. A next state of the environment is defined based on the mask and the one or more updated positions of the respective ablation electrode. The steps of determining the one or more actions and defining the next state are repeated for a plurality of iterations using 1) the next state as the current state and 2) the one or more updated positions as the one or more current positions to determine one or more final positions of the respective ablation electrode for performing a thermal ablation on the one or more tumors. The one or more final positions of each respective ablation electrode are output. |
Author | Audigier, Chloé Mansi, Tommaso Ghesu, Florin-Cristian Chaitanya, Krishna Paillard, Joseph Comaniciu, Dorin Balascuta, Laura Elena |
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Snippet | Systems and methods for determining an optimal position of one or more ablation electrodes are provided. A current state of an environment is defined based on... |
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SubjectTerms | DIAGNOSIS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY |
Title | AUTOMATIC PLANNING AND GUIDANCE OF LIVER TUMOR THERMAL ABLATION USING AI AGENTS TRAINED WITH DEEP REINFORCEMENT LEARNING |
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