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Copyright ©2011 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Clin Oncol. Apr 10, 2011; 2(4): 179-186
Published online Apr 10, 2011. doi: 10.5306/wjco.v2.i4.179
Online volume rendering of incrementally accumulated LSCEM images for superficial oral cancer detection
Wei Ming Chiew, Feng Lin, Kemao Qian, Hock Soon Seah
Wei Ming Chiew, Feng Lin, Kemao Qian, Hock Soon Seah, School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore
Author contributions: Chiew WM, Lin F, Qian K and Seah HS performed research; Ming CW and Lin F wrote the paper.
Supported by The grant SBIC RP C-010/2006 from A*Star Biomedical Research Council
Correspondence to: Feng Lin, Associate Professor, School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore. asflin@ntu.edu.sg
Telephone: +65-67906184 Fax: +65-67926559
Received: August 19, 2010
Revised: November 15, 2010
Accepted: November 22, 2010
Published online: April 10, 2011
Abstract

Laser scanning confocal endomicroscope (LSCEM) has emerged as an imaging modality which provides non-invasive, in vivo imaging of biological tissue on a microscopic scale. Scientific visualizations for LSCEM datasets captured by current imaging systems require these datasets to be fully acquired and brought to a separate rendering machine. To extend the features and capabilities of this modality, we propose a system which is capable of performing realtime visualization of LSCEM datasets. Using field-programmable gate arrays, our system performs three tasks in parallel: (1) automated control of dataset acquisition; (2) imaging-rendering system synchronization; and (3) realtime volume rendering of dynamic datasets. Through fusion of LSCEM imaging and volume rendering processes, acquired datasets can be visualized in realtime to provide an immediate perception of the image quality and biological conditions of the subject, further assisting in realtime cancer diagnosis. Subsequently, the imaging procedure can be improved for more accurate diagnosis and reduce the need for repeating the process due to unsatisfactory datasets.

Keywords: Confocal endomicroscope, Field-programmable gate arrays, Incrementally accumulated volume rendering, Realtime, Online cancer detection