Fachbereich 4
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- Colonoscopy (1)
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- Polypendetektion (1)
- polyp detection (1)
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This work addresses the challenge of calibrating multiple solid-state LIDAR systems. The study focuses on three different solid-state LIDAR sensors that implement different hardware designs, leading to distinct scanning patterns for each system. Consequently, detecting corresponding points between the point clouds generated by these LIDAR systems—as required for calibration—is a complex task. To overcome this challenge, this paper proposes a method that involves several steps. First, the measurement data are preprocessed to enhance its quality. Next, features are extracted from the acquired point clouds using the Fast Point Feature Histogram method, which categorizes important characteristics of the data. Finally, the extrinsic parameters are computed using the Fast Global Registration technique. The best set of parameters for the pipeline and the calibration success are evaluated using the normalized root mean square error. In a static real-world indoor scenario, a minimum root mean square error of 7 cm was achieved. Importantly, the paper demonstrates that the presented approach is suitable for online use, indicating its potential for real-time applications. By effectively calibrating the solid-state LIDAR systems and establishing point correspondences, this research contributes to the advancement of multi-LIDAR fusion and facilitates accurate perception and mapping in various fields such as autonomous driving, robotics, and environmental monitoring.
Colonoscopy is one of the best methods for screening colon cancer. As the automatic detection of polyps in endoscopic images is a challenging task for image processing, a variety of research groups have proposed methods that try to fulfill this task to develop a system which supports the doctors during examination. However, the problem is still "at least partially" not solved. This paper gives a summary of 16 different polyp detection methods published in the last ten years. We found out that the major draw-back of many approaches is the lack of representative video data, which hinders comparison and evaluation of the published methods.