Asynchronous in Parallel Detection and Tracking (AIPDT): Real-Time Robust Polyp Detection

7Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Automatic polyp detection during colonoscopy screening test is desired to reduce polyp miss rate and thus lower patients’ risk of developing colorectal cancer. Previous works mainly focus on detection accuracy, however, real-time and robust polyp detection is as important to be adopted in clinical workflow. To maintain accuracy, speed and robustness for polyp detection at the same time, we propose a framework featuring two novel concepts: (1) decompose the task into detection and tracking steps to take advantage of both high resolution static images for accurate detection and the temporal information between frames for fast tracking and robustness. (2) run detector and tracker in two parallel threads asynchronously so that a heavy but accurate detector and a light tracker can efficiently work together. We also propose a robustness metric to evaluate performance in realistic clinical setting. Experiments demonstrated that our method outperformed the state-of-the-art results in terms of accuracy, robustness and speed.

Cite

CITATION STYLE

APA

Zhang, Z., Shang, H., Zheng, H., Wang, X., Wang, J., Sun, Z., … Yao, J. (2020). Asynchronous in Parallel Detection and Tracking (AIPDT): Real-Time Robust Polyp Detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12263 LNCS, pp. 722–731). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59716-0_69

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free