## 1 Introduction  
In spinal fixation surgery, navigation systems provide accuracy to allow the safe placement of pedicle screws [1; 2]. Compared to free-hand techniques, which rely solely on the expertise of the surgeon, a safer pedicle screw placement is achieved and the risk of damaging neurovascular structures is reduced [3; 4; 5]. The improved accuracy afforded by surgical navigation also facilitates minimally invasive surgery (MIS), which strives to reduce tissue trauma and blood loss, shortening recovery time [6]. After the initial co-registration of patient position and imaging data, accuracy in navigated spinal surgery relies on the continuous tracking of the patient position. Thus, tracking should be sustained without loss throughout the whole procedure and should also be able to compensate for patient movements during breathing and surgical manipulation. The current, commercially available spinal navigation systems utilize markers or dynamic reference frames (DRF) to track the patient's position [7; 8]; however, markers or DRFs can be dislodged or obscured during the surgical procedure, resulting in the loss of navigational feedback and accuracy. In addition, DRFs are reportedly bulky and require adequate anchoring to the spine for best accuracy. We have previously reported on an augmented reality surgical navigation system (ARSN) using adhesive optical markers placed on the skin and detected by live video cameras for tracking [9; 10]. Since patient movements during surgery are typically well controlled and mainly reflect intentional movements of the surgical table, the relations between the skin surface and the deeply located spine structures are maintained. Thus, navigational accuracy can be achieved using surface-based tracking solutions [11]. The ARSN system using adhesive skin markers for patient position tracking has previously been extensively investigated in cadaveric and clinical studies and has demonstrated high accuracy [6; 9; 10; 12; 13; 14; 15]. Although easily detected and unobtrusive, adhesive optical markers still require placement within the surgical field, and a number of such markers need to be visible for tracking to be maintained. In contrast to marker-based solutions with single fixation points, typically occurring skin features such as spots, moles or changes in pigmentation are more uniformly distributed and can potentially provide accurate tracking without the shortcomings of other solutions. To explore the potential of skin feature detection, we have employed hyperspectral imaging (HSI). HSI is an optical imaging technique that captures a wide range of the electromagnetic spectrum, making it suitable for the detection of skin features even beyond the visible spectrum. HSI is non-ionizing and non-invasive and relies on the use of special cameras to acquire two-dimensional images across adjacent narrower spectral bands, reconstructing the reflectance spectrum for every pixel [16]. Compared with a normal RGB (Red Green Blue) camera, the spectral information is enriched by acquiring images over a larger spectral range with a narrower spectral band. This allows HSI to capture features which are not detectable with the visible wavelengths and consequently to capture information below the skin surface. xw The technology is well established in the remote sensing field and has recently received attention in medical imaging. The potential of HSI has been demonstrated in the medical field by [PERSON] et al. [17], who employed HSI as a non-invasive tool for tumor visualization and classification. [PERSON] et al. [18] developed a system that allows the capture of hyperspectral (HS) images of the in-vivo brain surface during neurosurgical operations. Their system acquired two HS data cubes: one in the visible-to-near-infrared (VNIR) range covering 400-1000 nm, and another in the near-infrared (NIR) range covering 900-1700 nm.