Hardware Plateforms Benchmark For Real-Time Polyp Detection

Quentin Angermann 1 Aymeric Histace 1, * Maroua Hammami 1 Mehdi Terosiet 1 Lionel Faurlini 1 Olivier Romain 1
* Auteur correspondant
1 ASTRE [Cergy-Pontoise]
ETIS - Equipes Traitement de l'Information et Systèmes
Abstract : In this article, our concern is the early diagnosis of colorectal cancer from a computer-aided detection point of view in order to help physicians in their diagnosis during the gold standard examination: optical videocolonoscopy. Since many years, some methods and materials have been developed to reduce the polyp missrate and to improve detection capabilities. Nevertheless, the real challenge lies in the real-time use of these methods. In this context, more precisely, we focus our attention on the hardware implementation of a previous method we recently introduced in the literature for real-time detection of colorectal polyps, lesions that may degenerate into cancer. This implementation is subject to three performance criteria: real-time processing capabilities, detection rate and necessary computational resources. Six different platforms were tested and compared. If we noticed that only workstation computers are able to perform the detection with a good tradeoff between the three aforementioned criteria, possibilities of architecture optimizations are also identified and discussed in order to achieve real-time performance on platforms with low available computational resources like Raspberry Pi for instance. This latter issue is of major importance for possible integration of the detection algorithm inside small-connected object like videocapsule, a promising alternative to standard colonoscopy
Type de document :
Communication dans un congrès
Euromicro Conference on Digital System Design, Aug 2017, Vienna, Austria. accepted, Proceedings of DSD conference
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https://hal.archives-ouvertes.fr/hal-01567321
Contributeur : Aymeric Histace <>
Soumis le : samedi 22 juillet 2017 - 15:23:04
Dernière modification le : lundi 24 juillet 2017 - 10:52:31

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  • HAL Id : hal-01567321, version 1

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Quentin Angermann, Aymeric Histace, Maroua Hammami, Mehdi Terosiet, Lionel Faurlini, et al.. Hardware Plateforms Benchmark For Real-Time Polyp Detection. Euromicro Conference on Digital System Design, Aug 2017, Vienna, Austria. accepted, Proceedings of DSD conference. <hal-01567321>

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