Within image-guided surgery, `hybrid' guidance technologies have been used to integrate the complementary features of radioactive guidance and fluorescence guidance. Here, we explore how the generation of a novel freehand fluorescence (fhFluo) imaging approach complements freehand SPECT (fhSPECT) in a hybrid setup. Near-infrared optical tracking was used to register the position and the orientation of a hybrid opto-nuclear detection probe while recording its readings. Dedicated look-up table models were used for 3D reconstruction. In phantom and excised tissue settings (i.e., flat-surface human skin explants), fhSPECT and fhFluo were investigated for image resolution and in-tissue signal penetration. Finally, the combined potential of these freehand technologies was evaluated on prostate and lymph node specimens of prostate cancer patients receiving prostatectomy and sentinel lymph node dissection (tracers: indocyanine green (ICG) +99mTc-nanocolloid or ICG-99mTc-nanocolloid). After hardware and software integration, the hybrid setup created 3D nuclear and fluorescence tomography scans. The imaging resolution of fhFluo (1 mm) was superior to that of fhSPECT (6 mm). Fluorescence modalities were confined to a maximum depth of 0.5 cm, while nuclear modalities were usable at all evaluated depths (<; 2 cm). Both fhSPECT and fhFluo enabled augmented- and virtual-reality navigation toward segmented image hotspots, including relative hotspot quantification with an accuracy of 3.9% and 4.1%. Imaging in surgical specimens confirmed these trends (fhSPECT: in-depth detectability, low resolution, and fhFluo: superior resolution, superficial detectability). Overall, when radioactive and fluorescent tracer signatures are used, fhFluo has complementary value to fhSPECT. Combined the freehand technologies render a unique hybrid imaging and navigation modality.

Reliable measurements of Sun Induced Fluorescence (SIF) require a good instrument characterization as well as a complex processing chain. In this paper, we summarize the state of the art SIF retrieval methods and measurements platforms for field phenotyping. Furthermore, we use HyScreen, hyperspectral-imaging system for top of canopy measurements of SIF, as an example of the instrument requirements, data process, and data validation needed to obtain reliable measurements of SIF.

In this paper we present the usage of a drop-in gamma probe for intra-operative Single-Photon Emission Computed Tomography (SPECT) imaging in the scope of minimally invasive robot-assisted interventions. The probe is designed to be inserted and reside inside the abdominal cavity during the intervention. It is grasped during the procedure using a robotic laparoscopic gripper enabling full six degrees of freedom handling by the surgeon. We demonstrate the first deployment of the tracked probe for intra-operative in-patient robotic SPECT enabling augmented-reality image guidance. The hybrid mechanical- and image-based in-patient probe tracking is shown to have an accuracy of 0.2 mm. The overall system performance is evaluated and tested with a phantom for gynecological sentinel lymph node interventions and compared to ground-truth data yielding a mean reconstruction accuracy of 0.67 mm.

Image-guided medical interventions more frequently rely on Augmented Reality (AR) visualization to enable surgical navigation. Current systems use 2-D monitors to present the view from external cameras, which does not provide an ideal perception of the 3-D position of the region of interest. Despite this problem, most research targets the direct overlay of diagnostic imaging data, and only few studies attempt to improve the perception of occluded structures in external camera views. The focus of this paper lies on improving the 3-D perception of an augmented external camera view by combining both auditory and visual stimuli in a dynamic multi-sensory AR environment for medical applications. Our approach is based on Temporal Distance Coding (TDC) and an active surgical tool to interact with occluded virtual objects of interest in the scene in order to gain an improved perception of their 3-D location. Users performed a simulated needle biopsy by targeting virtual lesions rendered inside a patient phantom. Experimental results demonstrate that our TDC-based visualization technique significantly improves the localization accuracy, while the addition of auditory feedback results in increased intuitiveness and faster completion of the task.

This paper presents a signal processing tool for analyzing and manipulating digitized acoustic wave fields, based on a spatio-temporal extension of the time-frequency representation space. The emphasis is on wave fields acquired with a 1-D linear array of equidistant microphones (representing the spatial samples), but the basic formulation is valid for the three dimensions of space. We start by defining a spatio-temporal extension of the short time Fourier transform, in both continuous and discrete space and time, and then focus on applications of the proposed representation. In particular, we show that acoustic scenes with multiple sources can benefit from the use of space-frequency analysis in applications such as source separation (spatial filtering) and spatial audio coding (wave field coding). The experiments suggest that there is a spatial window size for which the performance of filtering and coding is optimal.

We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatio-temporal spectral representation of the acoustic wave field. With the proposed method, the wave field is expressed as a separable combination of the signal and spatial components that characterize the various sources in the acoustic scene. This allows beamforming operations such as beam steering and sidelobe canceling to be translated into a two-dimensional (2D) sampling problem, where the sampling kernels are derived according to a parametric model representing the 2D spectral pattern generated in the presence of a source. Conversely, the spectral pattern can be estimated from an arbitrary input through the use of parametric spectral estimation techniques, providing a novel solution to the near-field source localization problem.

Abstract There is a vast number of applications that require distance field computation over triangular meshes. State‐of‐the‐art algorithms have quadratic or sub‐quadratic worst‐case complexity, making them impractical for interactive applications. While most of the research on this subject has been focused on reducing the computation complexity of the algorithms, in this work we propose an approximate algorithm that achieves similar results working in lower resolutions of the input meshes. The creation of lower resolution meshes is the essence of our proposal. The idea is to identify regions on the input mesh that can be unfolded into planar regions with minimal area distortion (i.e. quasi‐developable charts). Once charts are computed, their interior is re‐triangulated to reduce the number of triangles, which results in a collection of simplified charts that we call a base mesh. Due to the properties of quasi‐developable regions, we are able to compute distance fields over the base mesh instead of over the input mesh. This reduces the memory footprint and data processed for distance computations, which is the bottleneck of these algorithms. We present results that are one order of magnitude faster than current exact solutions, with low approximation errors.

We present a new method for compressing spatio-temporal audio data for reproduction through wave field synthesis. The data is obtained by sampling the sound field in space at equally-spaced points on a straight line, and transformed into the frequency domain using a spatio-temporal lapped transform. The two-dimensional spectrum is quantized using a psychoacoustic model derived for spatio-temporal frequencies, which estimates the maximum quantization noise power that each frequency can support in order to preserve transparency in the decoded signal. On the decoder side, the inverse lapped transform recovers the spatio-temporal data. In our experimental results, we verified that the bitrate-efficiency can be improved by increasing either the spatial sampling frequency or the spatial resolution of the lapped transform.