In minimally invasive surgery, the white-light thoracoscope as a standard imaging tool is facing challenges of the low contrast between important anatomical or pathological regions and surrounding tissues. Recently, the near-infrared (NIR) fluorescence imaging shows superior advantages over the conventional white-light observation, which inspires researchers to develop imaging systems to improve overall outcomes of endoscopic imaging. We developed an NIR and white-light dual-channel thoracoscope system, which achieved high-fluorescent signal acquisition efficiency and the simultaneously optimal visualization of the NIR and color dual-channel signals. The system was designed to have fast and accurate image registration and high signal-to-background ratio by optimizing both software algorithms and optical hardware components for better performance in the NIR spectrum band. The system evaluation demonstrated that the minimally detectable concentration of indocyanine green (ICG) was 0.01 μM, and the spatial resolution was 35 μm. The in vivo feasibility of our system was verified by the preclinical experiments using six porcine models with the intravenous injection of ICG. Furthermore, the system was successfully applied for guiding the minimally invasive segmentectomy in three lung cancer patients, which revealed that our system held great promise for the clinical translation in lung cancer surgeries.
Fluorescence molecular tomography (FMT) is developing rapidly in the field of molecular imaging. FMT has been
used in surgical navigation for tumor resection and has many potential applications at the physiological, metabolic, and
molecular levels in tissues. Due to the ill-posed nature of the problem, many regularized methods are generally adopted.
In this paper, we propose a region reconstruction method for FMT in which the trace norm regularization. The trace
norm penalty was defined as the sum of the singular values of the matrix. The proposed method adopts a priori
information which is the structured sparsity of the fluorescent regions for FMT reconstruction. In order to improve the
solution efficiency, the accelerated proximal gradient algorithms was used to accelerate the computation. The
numerical phantom experiment was conducted to evaluate the performance of the proposed trace norm regularization
method. The simulation study shows that the proposed method achieves accurate and is able to reconstruct image
effectively.
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