CapsuleMotion：一种用于胶囊内窥镜的轻量级实时视觉运动预测器
CapsuleMotion: A Lightweight Real-Time Visual Motion Predictor for Capsule Endoscopy
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中文总结 AI 辅助
针对胶囊内窥镜电池受限问题，提出CapsuleMotion动态帧率预测器，通过图像压缩指标预测运动并调整帧率，降低能耗达20.66%，并提升小肠入口检测准确性。
中文摘要 AI 辅助
视频胶囊内窥镜（VCE）是一种非侵入性医学检查方法，能够观察小肠，而小肠通常难以直接触及。一个基本挑战仍然存在，即胶囊尺寸必须足够小以便吞咽。然而，由此导致的电池容量受限与图像采集和传输的高功耗特性相矛盾。因此，我们提出了CapsuleMotion，一种患者特定的动态胶囊行为，它以目标导向的方式利用可用能量，以提高胃肠道完整筛查的可能性。通过研究并结合设备端图像压缩中的指标，CapsuleMotion预测两帧连续图像之间的运动。相机的帧率将根据预测的运动幅度进行调整。此外，在进入小肠之前，胶囊以显著降低帧率的低功耗模式运行。在此模式下，若预测到运动，则使用LocalizationNet来确定当前器官。所提出的框架在罗德岛VCE数据集上进行了评估，并部署在带有集成硬件加速器的超低功耗单核RISC-V演示器上。与缺乏动态帧率的传统胶囊相比，CapsuleMotion展示了将电能消耗降低高达20.66%的能力。此外，检测小肠入口点的准确性也得到了提高。
英文摘要
Video Capsule Endoscopy (VCE) is a non-invasive medical examination that allows for the observation of the small intestine, which is otherwise difficult to access. A fundamental challenge persists in the form of their limited size in order to still be swallowable. The resulting restricted battery capacity, however, contradicts with the power-intensive nature of image capture and transmission. Therefore, we propose CapsuleMotion, a patient-specific dynamic capsule behavior that utilizes the available energy in a goal-oriented manner to increase the likelihood of a complete screening of the gastrointestinal tract. By investigating and combining metrics from the on-device image compression, CapsuleMotion predicts the motion between two successive frames. The camera's frame rate will be modified in accordance with the predicted magnitude of motion. Furthermore, prior to entering the small intestine, the capsule operates in a low power mode with a significantly reduced frame rate. In this mode, the LocalizationNet is employed to determine the current organ, provided that motion was predicted. The proposed framework is evaluated on the Rhode Island VCE dataset and deployed on an ultra-low power single-core RISC-V demonstrator with an integrated hardware accelerator. CapsuleMotion demonstrated the capability to reduce electric energy consumption by up to 20.66% in comparison with conventional capsules that lack a dynamic frame rate. Additionally, the accuracy of detecting the entry point of the small intestine has been improved.
发表机构
- University of Tübingen（图宾根大学）
机构由 AI 辅助整理，请以论文原文为准。
