EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

none5siembargoed_20190801Penza, Veronica; Ciullo, Andrea S.; Moccia, Sara; Mattos, Leonardo S.; De Momi, ElenaPenza, Veronica; Ciullo, Andrea S.; Moccia, Sara; Mattos, Leonardo S.; De Momi, Elen

EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

Background: 3D reconstruction algorithms are of fundamental importance for augmented reality applications in computer-assisted surgery. However, few datasets of endoscopic stereo images with associated 3D surface references are currently openly available, preventing the proper validation of such algorithms. This work presents a new and rich dataset of endoscopic stereo images (EndoAbS dataset). Methods: The dataset includes (i) endoscopic stereo images of phantom abdominal organs, (ii) a 3D organ surface reference (RF) generated with a laser scanner and (iii) camera calibration parameters. A detailed description of the generation of the phantom and the camera–laser calibration method is also provided. Results: An estimation of the overall error in creation of the dataset is reported (camera–laser calibration error 0.43 mm) and the performance of a 3D reconstruction algorithm is evaluated using EndoAbS, resulting in an accuracy error in accordance with state-of-the-art results (<2 mm). Conclusions: The EndoAbS dataset contributes to an increase the number and variety of openly available datasets of surgical stereo images, including a highly accurate RF and different surgical conditions

Automatic workflow for narrow-band laryngeal video stitching

In narrow band (NB) laryngeal endoscopy, the clinician usually positions the endoscope near the tissue for a correct inspection of possible vascular pattern alterations, indicative of laryngeal malignancies. The video is usually reviewed many times to refine the diagnosis, resulting in loss of time since the salient frames of the video are mixed with blurred, noisy, and redundant frames caused by the endoscope movements. The aim of this work is to provide to the clinician a unique larynx panorama, obtained through an automatic frame selection strategy to discard non-informative frames. Anisotropic diffusion filtering was exploited to lower the noise level while encouraging the selection of meaningful image features, and a feature-based stitching approach was carried out to generate the panorama. The frame selection strategy, tested on on six pathological NB endoscopic videos, was compared with standard strategies, as uniform and random sampling, showing higher performance of the subsequent stitching procedure, both visually, in terms of vascular structure preservation, and numerically, through a blur estimation metric

Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery

Purpose: Single-incision laparoscopic surgery decreases postoperative infections, but introduces limitations in the surgeon’s maneuverability and in the surgical field of view. This work aims at enhancing intra-operative surgical visualization by exploiting the 3D information about the surgical site. An interactive guidance system is proposed wherein the pose of preoperative tissue models is updated online. A critical process involves the intra-operative acquisition of tissue surfaces. It can be achieved using stereoscopic imaging and 3D reconstruction techniques. This work contributes to this process by proposing new methods for improved dense 3D reconstruction of soft tissues, which allows a more accurate deformation identification and facilitates the registration process. Methods: Two methods for soft tissue 3D reconstruction are proposed: Method 1 follows the traditional approach of the block matching algorithm. Method 2 performs a nonparametric modified census transform to be more robust to illumination variation. The simple linear iterative clustering (SLIC) super-pixel algorithm is exploited for disparity refinement by filling holes in the disparity images. Results: The methods were validated using two video datasets from the Hamlyn Centre, achieving an accuracy of 2.95 and 1.66 mm, respectively. A comparison with ground-truth data demonstrated the disparity refinement procedure: (1) increases the number of reconstructed points by up to 43% and (2) does not affect the accuracy of the 3D reconstructions significantly. Conclusion: Both methods give results that compare favorably with the state-of-the-art methods. The computational time constraints their applicability in real time, but can be greatly improved by using a GPU implementation

Label-based Optimization of Dense Disparity Estimation for Robotic Single Incision Abdominal Surgery

Minimally invasive surgical techniques have led to novel approaches such as Single Incision Laparoscopic Surgery (SILS), which allows the reduction of post-operative infections and patient recovery time, improving surgical outcomes. However, the new techniques pose also new challenges to surgeons: during SILS, visualization of the surgical field is limited by the endoscope field of view, and the access to the target area is limited by the fact that instruments have to be inserted through a single port. In this context, intra-operative navigation and augmented reality based on pre-operative images have the potential to enhance SILS procedures by providing the information necessary to increase the intervention accuracy and safety. Problems arise when structures of interest change their pose or deform with respect to pre-operative planning, as usually happens in soft tissue abdominal surgery. This requires online estimation of the deformations to correct the pre-operative plan, which can be done, for example, through methods of depth estimation from stereo endoscopic images (3D reconstruction). The denser the reconstruction, the more accurate the deformation identification can be. This work presents an algorithm for 3D reconstruction of soft tissue, focusing on the refinement of the disparity map in order to obtain an accurate and dense point map. This algorithm is part of an assistive system for intra-operative guidance and safety supervision for robotic abdominal SILS . Results show that comparing our method with state-of-the-art CPU implementations, the percentage of valid pixel obtained with our method is 24% higher while providing comparable accuracy. Future research will focus on the development of a real-time implementation of the proposed algorithm, potentially based on a hybrid CPU-GPU processing framework

Total solar irradiance during the last five centuries

The total solar irradiance (TSI) varies on timescales of minutes to centuries. On short timescales it varies due to the superposition of intensity fluctuations produced by turbulent convection and acoustic oscillations. On longer timescales, it changes due to photospheric magnetic activity, mainly because of the facular brightenings and dimmings caused by sunspots. While modern TSI variations have been monitored from space since the 1970s, TSI variations over much longer periods can only be estimated either using historical observations of magnetic features, possibly supported by flux transport models, or from the measurements of the cosmogenic isotope (e.g., 14C or 10Be) concentrations in tree rings and ice cores. The reconstruction of the TSI in the last few centuries, particularly in the 17th/18th centuries during the Maunder minimum, is of primary importance for studying climatic effects. To separate the temporal components of the irradiance variations, specifically the magnetic cycle from secular variability, we decomposed the signals associated with historical observations of magnetic features and the solar modulation potential Φ by applying an empirical mode decomposition algorithm. Thus, the reconstruction is empirical and does not require any feature contrast or field transport model. The assessed difference between the mean value during the Maunder minimum and the present value is ≃2.5 W m−2. Moreover it shows, in the first half of the last century, a growth of ≃1.5 W m−2, which stops around the middle of the century to remain constant for the next 50 years, apart from the modulation due to the solar cycle

Effects of a walking aid in COPD patients receiving oxygen therapy

STUDY OBJECTIVES: To elucidate whether a simple walking aid may improve physical performance in COPD patients with chronic respiratory insufficiency who usually carry their own heavy oxygen canister. DESIGN: Randomized crossover trial. SETTING: Physiopathology laboratory of three rehabilitation centers. PATIENTS AND INTERVENTIONS: We studied 60 stable COPD patients (mean age, 70.6 +/- 7.9 years; FEV(1), 44.8 +/- 14.3% of predicted [+/- SD]) with chronic respiratory insufficiency who randomly performed, on 2 consecutive days, a standardized 6-min walking test using two different modalities: a full-weight oxygen canister transported using a small wheeled cart and pulled by the patient (Aid modality) or full-weight oxygen canister carried on the patient's shoulder (No-Aid modality). MEASUREMENTS AND RESULTS: The distance walked, peak effort dyspnea, and leg fatigue scores as primary outcomes, and other cardiorespiratory parameters as secondary outcomes were recorded during both tests. A significant difference (p < 0.05) between the two tests occurred for all the measured outcomes in favor of the Aid modality. Most importantly, significant changes for distance (+ 43 m, p < 0.001), peak effort dyspnea (- 2.0 points, p < 0.001), leg fatigue (- 1.4 points, p < 0.001), as well as for mean and nadir oxygen saturation and heart rate with the Aid modality (but not with the No-Aid modality) were recorded in the subgroup of patients walking < 300 m at baseline. CONCLUSIONS: This study suggests that a simple walking aid may be helpful in COPD patients receiving long-term oxygen therapy, particularly in those with lower residual exercise capacity

Hypersensitivity to Imatinib: Successful Desensitization in a Skin Test–Positive Patient

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