title: Spatial-frequency-compression scheme for diffuse optical tomography with dense sampling dataset.
abstract: Dense sampling of illumination and detection offers an effective way of improving the image-reconstruction performance of near-infrared diffuse optical tomography (DOT) at a cost of lengthy computation times. In this paper, we describe a fast DOT scheme for reconstructing the absorption coefficient image of a slab medium from dense sampling of both illumination and detection in the noncontact DOT. The proposed method is carried out with spatial-frequency encoding in both the source and detection spaces, and involves a spatial-frequency-compression (SFC) strategy for selecting the useful spatial frequency based on the tissue transfer function. The method is expected to considerably reduce the calculation time for reconstruction while improving the quality of the reconstructed images. Results from the simulated data show that the speed for absorption reconstruction with the proposed SFC method is more than 400 times faster than that with the conventional one. A noncontact DOT system for dense sampling of both illumination and detection is developed by using laser raster scanning and CCD-based data acquisition. Experimental measurements on several solid phantoms demonstrate that a high quantitativeness ratio can be obtained from the proposed method thanks to reduction of the ill-posedness of the inverse calculation. It takes less than 20 s for the proposed method to experimentally reconstruct one absorption image from a 256×256-sized dataset, which would take a few hours with the conventional method.
authors.affiliation: College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, China.
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Zhou
authors.forename: Ying
authors.initials: Y
authors.lastname: Fan
authors.forename: Qiang
authors.initials: Q
authors.lastname: Hou
authors.forename: Huijuan
authors.initials: H
authors.lastname: Zhao
authors.forename: Feng
authors.initials: F
authors.lastname: Gao
mesh_terms: D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D041622:Tomography, Optical / Q000295:instrumentation / Q000379:methods*