首页|Patent Issued for Patient anatomy and task specific automatic exposure control i n computed tomography (USPTO 12002204)
Patent Issued for Patient anatomy and task specific automatic exposure control i n computed tomography (USPTO 12002204)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Ge Precision Healthcare LLC (Waukesha, Wisconsin, United States) has been issued patent number 12002204, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors. The patent's inventors are Imran, Abdullah-Al-Zubaer (Sunnyvale, CA, US), Pal, D ebashish (Sunnyvale, CA, US), Patel, Bhavik Natvar (Paradise Valley, AZ, US), Wa ng, Adam S. (Palo Alto, CA, US), Wang, Sen (Menlo Park, CA, US), Zucker, Evan (P alo Alto, CA, US). This patent was filed on September 10, 2021 and was published online on June 4, 2024. From the background information supplied by the inventors, news correspondents o btained the following quote: "Computed tomography (CT) has been one of the most successful imaging modalities and has facilitated countless image-based medical procedures since its invention decades ago. CT accounts for a large amount of io nizing radiation exposure, especially with the rapid growth in CT examinations. Therefore, it is desirable to reduce the CT radiation dose. However, the reducti on in dose also incurs additional noise and with the degraded image quality, dia gnostic performance can be compromised. "In this regard, radiation dose and image quality have traditionally been compet ing objectives in CT imaging. To balance the two, modern CT systems use automati c exposure control (AEC), particularly tube current modulation (TCM) based on sc out images. However, the goal of conventional AEC algorithms is to provide a uni form noise level across the entire imaged volume. While this is generally succes sful in avoiding excessive radiation dose and maintaining image quality, it is l argely based solely on the general shape and size of the patient. In addition, c onventional AEC algorithms use a metric for dose which reflects the tube output rather than actual dose to the patient. Conventional AEC techniques remain unawa re of patient-specific anatomy that impacts organ dose, do not account for image quality based on the task, and are prone to issues such as patient centering."
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