Eye Tracker Accuracy: Quantitative Evaluation of the Invisible Eye Center Location

Purpose. We present a new method to evaluate the accuracy of an eye tracker based eye localization system. Measuring the accuracy of an eye tracker's primary intention, the estimated point of gaze, is usually done with volunteers and a set of fixation points used as ground truth. However, verifying the accuracy of the location estimate of a volunteer's eye center in 3D space is not easily possible. This is because the eye center is an intangible point hidden by the iris. Methods. We evaluate the eye location accuracy by using an eye phantom instead of eyes of volunteers. For this, we developed a testing stage with a realistic artificial eye and a corresponding kinematic model, which we trained with {\mu}CT data. This enables us to precisely evaluate the eye location estimate of an eye tracker. Results. We show that the proposed testing stage with the corresponding kinematic model is suitable for such a validation. Further, we evaluate a particular eye tracker based navigation system and show that this system is able to successfully determine the eye center with sub-millimeter accuracy. Conclusions. We show the suitability of the evaluated eye tracker for eye interventions, using the proposed testing stage and the corresponding kinematic model. The results further enable specific enhancement of the navigation system to potentially get even better results

All fiber-based LIBS feedback system for endoscopic laser surgery

There has been a particular interest to use laser-induced breakdown spectroscopy (LIBS) as a feedback mechanism for laser surgeries in the past decade 1-6. However, none of the mentioned setups 1-6 is suitable for endoscopic applications due to their bulky free-space configurations. In minimally nvasive surgeries, the major challenge is to integrate ablating laser waveguides and also all sensors inside the narrow channel of the endoscope. In this paper, we present a LIBS setup, which uses a multimode silica fiber for both delivering the inducing laser pulse and collecting the plasma emission light through the endoscope. The fiber-based LIBS setup consists of a frequency-doubled Q-switched Nd:YAG laser (Q-smart 450, Quantel, 532 nm, 5 ns, 60 mJ, 1 Hz), a cleaved large-core silica fiber (1.5 m-long, 1500 um-core, 0.39-NA, 70 mm-bending radius), and an in-house Echelle spectrometer (See Fig. 1). A 75 cm plano-convex laser line lens (Thorlabs, LA1978-YAG) was used to couple the laser beam into a multimode step-index silica fiber. Such a long focal length convex lens was used to avoid breakdown process in air. Moreover, the input face of the fiber was placed at 1 cm behind the focal point to maintain the laser power density below the damage threshold of the fiber. Two tight focusing lenses were placed in front of the fiber end face to collimate the highly divergent laser beam and refocus it onto the sample surface. The light emitted from the microplasma generated at the surface of the sample (bone and its surrounding soft tissues) was collected by the same optics and directed to the spectrometer for characterization. The performance of the developed fiber-based LIBS setup for classification of different tissues has been investigated and compared with the free-space LIBS. The feedback provided by this fiber-based LIBS setup can be used in minimally invasive laserosteotomies in order to stop the laser before causing any collateral damage to surrounding tissues. References [1] F. Yueh, H. Zheng, J.P. Singh, S. Burgess, Preliminary evaluation of laser-induced breakdown spectroscopy for tissue classification, Spectrochim. Acta B 64 (2009) 1059-1067. [2] R. Kanawade, F. Mehari, C. Knipfer, M. Rohde, K. Tangermann-Gerk, et al., Pilot study of laser induced breakdown spectroscopy for tissue differentiation by monitoring the plume created during laser surgery-An approach on a feedback Laser control mechanism, Spectrochim. Acta B 87 (2013) 175-181. [3] K. Henn, G.G. Gubaidullin, J. Bongartz, J. Wahrburg, H. Roth, et al., A spectroscopic approach to monitor the cut processing in pulsed laser osteotomy, Lasers Med. Sci. 28 (2013) 87-92. [4] H. Huang, L.-M. Yang, S. Bai, J. Liu, Smart surgical tool, J. Biomed. Opt. 20 (2015) 028001. [5] R.K. Gill, Z.J. Smith, C. Lee, S. Wachsmann-Hogiu, The effects of laser repetition rate on femtosecond laser ablation of dry bone: a thermal and LIBS study, J. Biophotonics 9 (2016) 171-180. [6] H. Abbasi, G. Rauter, R. Guzman, P.C. Cattin, A. Zam, Laser-induced breakdown spectroscopy as a potential tool for auto carbonization detection in laserosteotomy, J. Biomed. Opt. 23 (2018) 071206

Toward finding the best machine learning classifier for LIBS-based tissue differentiation

Lasers have become generally accepted devices in surgical applications, especially as a cutting tool, for cutting both soft and hard tissues including bone (laserosteotomy). It has been shown that applying lasers in osteotomy have important advantages over mechanical tools, including faster healing, more precise cut and functional cutting geometries as well as less trauma [1, 2]. However, the ability of detecting the type of tissue that being cut during surgery can extend the application and safety of laserosteotomes in practice. As a result, the laser could be stopped automatically in case of cutting a tissue that should be preserved. Authors have previously demonstrated that laser-induced breakdown spectroscopy (LIBS) is a potential candidate to differentiate surrounding soft tissue from the bone in ex vivo condition [3]. In the current study, different machine learning classifiers were examined to find the best possible method to differentiate bone from soft tissues based on LIBS data. These methods include decision tree, K Nearest Neighbor (KNN), linear and quadratic Support Vector Machine (SVM) as well as linear and quadratic discriminant analysis. All classifiers were applied on LIBS data obtained from bone, muscle, and fat tissues using an Nd:YAG laser and an Echelle spectrometer. Confusion matrix and Receiver Operating Characteristic (ROC) curve were obtained for each classifier afterwards. Moreover, in order to estimate the model's performance on new data and also to protect the model against overfitting, cross-validation was applied. All mentioned examinations were performed with MATLAB (R2017b)

Diffusion Models for Memory-efficient Processing of 3D Medical Images

Denoising diffusion models have recently achieved state-of-the-art performance in many image-generation tasks. They do, however, require a large amount of computational resources. This limits their application to medical tasks, where we often deal with large 3D volumes, like high-resolution three-dimensional data. In this work, we present a number of different ways to reduce the resource consumption for 3D diffusion models and apply them to a dataset of 3D images. The main contribution of this paper is the memory-efficient patch-based diffusion model \textit{PatchDDM}, which can be applied to the total volume during inference while the training is performed only on patches. While the proposed diffusion model can be applied to any image generation tasks, we evaluate the method on the tumor segmentation task of the BraTS2020 dataset and demonstrate that we can generate meaningful three-dimensional segmentations.Comment: Accepted at MIDL 202

Design and implementation of a compact high-throughput echelle spectrometer using off-the-shelf off-axis parabolic mirrors for analysis of biological samples by LIBS (Conference Presentation)

This work presents the development of an Echelle spectrometer that is optimized for the characterization of laser-driven plasma emission of biological samples for application in smart laser surgery systems. Despite the compact (portable) and cost-efficient design of the developed spectrometer, it allows analyzing the spectrum of a plasma emitted from bone, and its surrounding soft tissues (bone marrow, muscle, and fat) in nearly the same way as a full-sized Echelle spectrometer as used in commercial laser-induced breakdown spectroscopy (LIBS) systems. Most of the commercially available Echelle spectrometers on the market use a long focal length on-axis mirror to have a reasonable F number (which defines the optical throughput of the system) and low aberration. While a long focal length requires less tilting of the mirror than a shorter focal length (the higher the tilt angle, the higher the aberration), a long focal length increases the system size and decreases sensitivity (i.e., less optical throughput). In this work, a parabolic 90o off-axis mirror with a focal length of 152.4 mm and a diameter of 50.8 mm, which leads to an F-number of 3, has been used. This low F-number provides a high optical throughput compared to other similar commercial Echelle spectrometers with F-numbers of 10 or more [1-5]. Since most of the important peaks in biological tissue are in the interval of 240 to 840 nm [6], the design was done by using off-the-shelf aluminum mirrors with a UV-enhanced coating for both collimating and focusing purposes to cover this range with sub-Angstrom resolution. Both collimating and focusing mirrors were chosen with the same radius of curvature and declination angle (opposite direction) to cancel the coma. In this antiparallel configuration, the second parabolic mirror largely eliminates the aberrations from the first one. Moreover, we positioned the Echelle grating under the condition of quasi-Littrow design to have high diffraction efficiency with an off-axis angle in the horizontal plane. A ruled reflection grating with dispersion perpendicular to that of the Echelle grating was utilized as a cross dispenser (order separator) after the Echelle grating to distinguish the overlapping diffraction harmonics. The spectrometer has been connected to a gated ICCD to measure time-resolved spectra. The developed spectrometer was installed on a 3-tier utility cart, the inducing laser (Q-switched Nd:YAG) for LIBS was placed on the middle tier, and the last tier was dedicated for calibration instruments (a NIST traceable balanced Deuterium-Halogen light source for intensity calibration, and some gas/vapor spectral lamps including Mercury-Argon, Argon, Neon, and Krypton for wavelength calibration). The portability feature of this LIBS setup provides a remarkable value for testing and characterizing different biological samples on-site. This is a great capability especially if the target sample has the potential of being contagious. This setup is meant to be used for so-called smart laser osteotomies, i.e., the osteotome will be able to identify the type of the tissue being cut through the feedback provided by LIBS [6-8]