Literature DB >> 24001925

SAPPHIRE: a toolkit for building efficient stream programs for medical video analysis.

Sean R Stanek1, Wallapak Tavanapong, Johnny Wong, JungHwan Oh, Ruwan D Nawarathna, Jayantha Muthukudage, Piet C de Groen.   

Abstract

This paper describes the design and implementation of SAPPHIRE--a novel middleware and software development kit for stream programing on a heterogeneous system of multi-core multi-CPUs with optional hardware accelerators such as graphics processing unit (GPU). A stream program consists of a set of tasks where the same tasks are repeated over multiple iterations of data (e.g., video frames). Examples of such programs are video analysis applications for computer-aided diagnosis and computer-assisted surgeries. Our design goal is to reduce the implementation efforts and ease collaborative software development of stream programs while supporting efficient execution of the programs on the target hardware. To validate the toolkit, we implemented EM-Automated-RT software with the toolkit and reported our experience. EM-Automated-RT performs real-time video analysis for quality of a colonoscopy procedure and provides visual feedback to assist the endoscopist to achieve optimal inspection of the colon during the procedure. The software has been deployed in a hospital setting to conduct a clinical trial.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords:  Medical video analysis; Multi-core multi CPUs; Software development kit; Stream programs

Mesh:

Year:  2013        PMID: 24001925     DOI: 10.1016/j.cmpb.2013.07.028

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  3 in total

1.  Medical needs related to the endoscopic technology and colonoscopy for colorectal cancer diagnosis.

Authors:  Juan Francisco Ortega-Morán; Águeda Azpeitia; Luisa F Sánchez-Peralta; Luis Bote-Curiel; Blas Pagador; Virginia Cabezón; Cristina L Saratxaga; Francisco M Sánchez-Margallo
Journal:  BMC Cancer       Date:  2021-04-26       Impact factor: 4.430

2.  Artificial intelligence-based assessments of colonoscopic withdrawal technique: a new method for measuring and enhancing the quality of fold examination.

Authors:  Wei Liu; Yu Wu; Xianglei Yuan; Jingyu Zhang; Yao Zhou; Wanhong Zhang; Peipei Zhu; Zhang Tao; Long He; Bing Hu; Zhang Yi
Journal:  Endoscopy       Date:  2022-04-07       Impact factor: 9.776

Review 3.  Artificial intelligence-assisted colonoscopy: A review of current state of practice and research.

Authors:  Mahsa Taghiakbari; Yuichi Mori; Daniel von Renteln
Journal:  World J Gastroenterol       Date:  2021-12-21       Impact factor: 5.742

  3 in total

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