2017/06/22 by Geoffrey Jones, Jones, Geoffrey, Neil T. Clancy +11
Engineering · Medicine · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Non-Invasive Vital Sign Monitoring #Optical Imaging and Spectroscopy Techniques #Photoacoustic and Ultrasonic Imaging #Ultrasound Imaging and Elastography
paper · pdf · doi:10.48550/arxiv.1706.07263
openalex publication_date 2017/06/22 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28
Tissue oxygenation and perfusion can be an indicator for organ viability\nduring minimally invasive surgery, for example allowing real-time assessment of\ntissue perfusion and oxygen saturation. Multispectral imaging is an optical\nmodality that can inspect tissue perfusion in wide field images without\ncontact. In this paper, we present a novel, fast method for using RGB images\nfor MSI, which while limiting the spectral resolution of the modality allows\nnormal laparoscopic systems to be used. We exploit the discrete Haar\ndecomposition to separate individual video frames into low pass and directional\ncoefficients and we utilise a different multispectral estimation technique on\neach. The increase in speed is achieved by using fast Tikhonov regularisation\non the directional coefficients and more accurate Bayesian estimation on the\nlow pass component. The pipeline is implemented using a graphics processing\nunit (GPU) architecture and achieves a frame rate of approximately 15Hz. We\nvalidate the method on animal models and on human data captured using a da\nVinci stereo laparoscope.\n