報告人：王森 博士 斯坦福大學醫學院放射學系
主持人：陳陽
報告時間：2024年12月25日（周三）下午16:00
報告地點：bet356手机版唯一官网九龍湖校區計算機樓513報告廳
報告摘要：Photon Counting Detectors (PCDs) for X-ray Computed Tomography provide a semiconductor-based energy-differentiating counting mechanism that better captures realistic physics processes. The direct impacts include significant image resolution improvements and dose reduction compared to conventional energy integrating detectors (EIDs), which has been widely evaluated and recognized. Apart from that, in this presentation, we aim to discuss how the accurate physics information from PCDs potentially offers more extensive benefits for X-ray imaging. We have found that the physics information acquired by PCDs strongly synergizes with current machine learning approaches. By incorporating this physics information, we were able to enable a self-supervised denoising method (Noise2Noise) and an end-to-end differentiable Photon Counting CT (PCCT) imaging chain. These preliminary trials can be generally applied to other imaging methods or applications that involve count measurements and optimizations (in inverse problems).
報告人簡介：王森，2014年本科畢業于清華大學工程物理系獲學士學位，并于2019年在清華大學工程物理系獲博士學位（導師：張麗研究員）。博士畢業同年獲清華大學“紫荊學者”計劃資助，于2020年赴斯坦福放射學系（Department of Radiology）從事博士後研究，合作導師為：Adam Wang教授和Norbert Pelc教授，并于2023年轉為研究科學家（Research Scientist）。他的研究方向主要為先進X射線能譜成像在醫學診斷和介入手術中的應用，代表性工作包括先進光子計數CT探測器物理分析、準單能光子計數CT成像、物理信息約束自監督AI低劑量CT成像等，近期研究方向: 1）低劑量CT成像與AI掃描控制，2）數據驅動的高質量定量X射線成像及其全流程物理信息微分分析。
