# US 2025/0375175 A1 · Smart frame rate adaptation by tracking bolus agent flow in fluoroscopy > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0375175 A1 - Document ID: US20250375175A1 - Status: Published application - Kind: A1 - Application number: 19/226,215 - Filed: 2025-06-03 - Published: 2025-12-11 - Earliest claimed: 2024-06-05 - Assignees: Siemens Healthineers AG - Applicants: Siemens Healthineers AG - Inventors: Mrutyunjay BISWAL; Murali Tharan GNANAMANI; Tasheer HUSSAIN B; Vivek MISHRA - Web page: https://patentgrep.com/patent/US20250375175A1 ## CPC - A61B 6/032: {Transmission computed tomography [CT]} - A61B 6/481: {involving the use of contrast agents} - A61B 6/485: {involving fluorescence X-ray imaging} - A61B 6/487: {involving fluoroscopy} - A61B 6/545: {involving automatic set-up of acquisition parameters} - G06T 7/0012: {Biomedical image inspection} - G06T 7/0016: {involving temporal comparison} - H04N 19/172: the region being a picture, frame or field - G06T 2207/10121: Fluoroscopy - G06T 2207/30092: Stomach; Gastric - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract Example embodiments relate to a system for smart frame rate adaptation by tracking bolus agent flow in fluoroscopy, a method for using said system, and a computer program product. A system for acquiring a number of medical images of a patient is suggested. The system comprises a medical imaging unit configured to acquire the number of medical images with a particular value of a frame rate; an image analysis unit configured to analyze the acquired number of medical images; an event detection unit configured to detect at least one event based on the analyzed acquired number of medical images; and a frame rate determination unit configured to determine a modified value of the frame rate based on the detected at least one event and the particular value of the frame rate. The system can minimize the radiation exposure of the patient. ## Claims ### Claim 1 A system for acquiring a number of medical images of a patient, the system comprising: a medical imaging unit configured to acquire the number of medical images with a particular value of a frame rate; an image analysis unit configured to analyze the acquired number of medical images; an event detection unit configured to detect at least one event based on the analyzed acquired number of medical images; and a frame rate determination unit configured to determine a modified value of the frame rate based on the detected at least one event and the particular value of the frame rate. ### Claim 2 (depends on 1) The system of claim 1, wherein the at least one event is an entry of a bolus within the acquired number of medical images or an exit of the bolus from the acquired number of medical images. ### Claim 3 (depends on 2) The system of claim 2, wherein at least one of the entry or the exit of the bolus is referred to boundaries of a limited field of interest within the acquired number medical images. ### Claim 4 (depends on 3) The system of claim 3, wherein the field of interest is defined prior to acquiring the number of medical images. ### Claim 5 (depends on 1) The system of claim 1, wherein the image analysis unit is configured to calculate an entropy-based metric of the acquired number of medical images. ### Claim 6 (depends on 5) The system of claim 5, wherein the event detection unit is configured to detect the at least one event based on a variation of the calculated entropy-based metric. ### Claim 7 (depends on 6) The system of claim 6, wherein the event detection unit is configured to detect the at least one event based on a similar variation of the calculated entropy-based metric during subsequent ones of the acquired number of medical images. ### Claim 8 (depends on 5) The system of claim 5, wherein the entropy-based metric is a weighted combination of Forward and Backward Kullback Leibler Divergence. ### Claim 9 (depends on 6) The system of claim 6, wherein the event detection unit is configured to define an action time window between two determined time stamps corresponding to two detected events. ### Claim 10 (depends on 9) The system of claim 9, wherein the frame rate determination unit is configured to increase the value of the frame rate during the defined action time window. ### Claim 11 (depends on 9) The system of claim 9, wherein the frame rate comprises values of a standby frame rate and an action frame rate, the action frame rate is higher than the standby frame rate. ### Claim 12 (depends on 11) The system of claim 11, wherein the frame rate determination unit is configured to switch from the standby frame rate to the action frame rate with a beginning of the defined action time window and to switch from the action frame rate to the standby frame rate with an end of the defined action time window. ### Claim 13 (depends on 1) The system of claim 1, wherein the frame rate is limited by at least one of a minimum value or a maximum value. ### Claim 14 (depends on 1) A method for using the system of claim 1, the method comprising: acquiring the number of medical images with the particular value of the frame rate by the medical imaging unit; analyzing the acquired number of medical images by the image analysis unit; detecting the at least one event based on the analyzing; and determining the modified value of the frame rate based on the detected at least one event and the particular value of the frame rate by the frame rate determination unit. ### Claim 15 (depends on 14) A non-transitory computer program product comprising instructions, when executed by a computer, cause the computer to perform the method of claim 14. ### Claim 16 (depends on 6) The system of claim 6, wherein the event detection unit is configured to determine a time stamp of the detected at least one event. ### Claim 17 (depends on 2) The system of claim 2, wherein the image analysis unit is configured to calculate an entropy-based metric of the acquired number of medical images. ### Claim 18 (depends on 17) The system of claim 17, wherein the event detection unit is configured to detect the at least one event based on a variation of the calculated entropy-based metric. ### Claim 19 (depends on 18) The system of claim 18, wherein the event detection unit is configured to detect the at least one event based on a similar variation of the calculated entropy-based metric during subsequent ones of the acquired number of medical images. ### Claim 20 (depends on 17) The system of claim 17, wherein the entropy-based metric is a weighted combination of Forward and Backward Kullback Leibler Divergence.