Evaluating surgical skills from kinematic data using convolutional neural networks

The need for automatic surgical skills assessment is increasing, especially because manual feedback from senior surgeons observing junior surgeons is prone to subjectivity and time consuming. Thus, automating surgical skills evaluation is a very important step towards improving surgical practice. In this paper, we designed a Convolutional Neural Network (CNN) to evaluate surgeon skills by extracting patterns in the surgeon motions performed in robotic surgery. The proposed method is validated on the JIGSAWS dataset and achieved very competitive results with 100% accuracy on the suturing and needle passing tasks. While we leveraged from the CNNs efficiency, we also managed to mitigate its black-box effect using class activation map. This feature allows our method to automatically highlight which parts of the surgical task influenced the skill prediction and can be used to explain the classification and to provide personalized feedback to the trainee.Comment: Accepted at MICCAI 201

Comparison of pattern of self-medication among urban and rural population of Telangana state, India

Background: Self-medication is one of the components of self-care, which may treat the disease or result in worsening of the condition due to irrational use of drug.1 In developing countries like India, self-medication is a common practice as it provides a low-cost alternative for people who cannot afford the high cost of clinical service, and is time efficient.Methods: A total of 110 participants completed the study. A printed questionnaire was given to those who were willing to participate in the study and came to buy medicines without consulting a doctor to various pharmacy outlets.Results: Among the group of drugs used antibiotics were the common drugs used in rural area (74%) and cough suppressants (50%) in urban area. Symptoms for opting self-medication were fever and common cold in both the groups. Individuals in both areas took self-medication based on their previous prescriptions (rural 42% vs urban41.6%) and advertisements. Rural individuals preferred self-medication with the opinion of saving time and urban people felt that it was less expensive.Conclusions: There is a difference in the pattern self-medication among rural and urban individuals. It is also to be noted that use of antibiotics may result in problems related to drug resistance. So, it would be advisable to restrict the sale of antibiotics as over the counter drugs

Statistics of pressure and of pressure-velocity correlations in isotropic turbulence

Some pressure and pressure-velocity correlation in a direct numerical simulations of a three-dimensional turbulent flow at moderate Reynolds numbers have been analyzed. We have identified a set of pressure-velocity correlations which posseses a good scaling behaviour. Such a class of pressure-velocity correlations are determined by looking at the energy-balance across any sub-volume of the flow. According to our analysis, pressure scaling is determined by the dimensional assumption that pressure behaves as a ``velocity squared'', unless finite-Reynolds effects are overwhelming. The SO(3) decompositions of pressure structure functions has also been applied in order to investigate anisotropic effects on the pressure scaling.Comment: 21 pages, 8 figur

A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics

In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and efficient technique is to use an electrical circuit analogy, known as a lumped parameter network or zero-dimensional (0D) fluid model, to represent blood flow throughout the cardiovascular system. Due to the strong physical interaction between the heart and the blood circulation, developing accurate and efficient numerical coupling methods remains an active area of research. In this work, we present a modular framework for implicitly coupling three-dimensional (3D) finite element simulations of cardiac mechanics to 0D models of blood circulation. The framework is modular in that the circulation model can be modified independently of the 3D finite element solver, and vice versa. The numerical scheme builds upon a previous work that combines 3D blood flow models with 0D circulation models (3D fluid - 0D fluid). Here, we extend it to couple 3D cardiac tissue mechanics models with 0D circulation models (3D structure - 0D fluid), showing that both mathematical problems can be solved within a unified coupling scheme. The effectiveness, temporal convergence, and computational cost of the algorithm are assessed through multiple examples relevant to the cardiovascular modeling community. Importantly, in an idealized left ventricle example, we show that the coupled model yields physiological pressure-volume loops and naturally recapitulates the isovolumic contraction and relaxation phases of the cardiac cycle without any additional numerical techniques. Furthermore, we provide a new derivation of the scheme inspired by the Approximate Newton Method of Chan (1985), explaining how the proposed numerical scheme combines the stability of monolithic approaches with the modularity and flexibility of partitioned approaches

Acceleration and vortex filaments in turbulence

We report recent results from a high resolution numerical study of fluid particles transported by a fully developed turbulent flow. Single particle trajectories were followed for a time range spanning more than three decades, from less than a tenth of the Kolmogorov time-scale up to one large-eddy turnover time. We present some results concerning acceleration statistics and the statistics of trapping by vortex filaments.Comment: 10 pages, 5 figure

A microfluidic renal proximal tubule with active reabsorptive function

In the kidney, the renal proximal tubule (PT) reabsorbs solutes into the peritubular capillaries through active transport. Here, we replicate this reabsorptive function in vitro by engineering a microfluidic PT. The microfluidic PT architecture comprises a porous membrane with user-defined submicron surface topography separating two microchannels representing a PT filtrate lumen and a peritubular capillary lumen. Human PT epithelial cells and microvascular endothelial cells in respective microchannels created a PT-like reabsorptive barrier. Co-culturing epithelial and endothelial cells in the microfluidic architecture enhanced viability, metabolic activity, and compactness of the epithelial layer. The resulting tissue expressed tight junctions, kidney-specific morphology, and polarized expression of kidney markers. The microfluidic PT actively performed sodium-coupled glucose transport, which could be modulated by administration of a sodium-transport inhibiting drug. The microfluidic PT reproduces human physiology at the cellular and tissue levels, and measurable tissue function which can quantify kidney pharmaceutical efficacy and toxicity

A Quantitative Evaluation of Dense 3D Reconstruction of Sinus Anatomy from Monocular Endoscopic Video

Generating accurate 3D reconstructions from endoscopic video is a promising avenue for longitudinal radiation-free analysis of sinus anatomy and surgical outcomes. Several methods for monocular reconstruction have been proposed, yielding visually pleasant 3D anatomical structures by retrieving relative camera poses with structure-from-motion-type algorithms and fusion of monocular depth estimates. However, due to the complex properties of the underlying algorithms and endoscopic scenes, the reconstruction pipeline may perform poorly or fail unexpectedly. Further, acquiring medical data conveys additional challenges, presenting difficulties in quantitatively benchmarking these models, understanding failure cases, and identifying critical components that contribute to their precision. In this work, we perform a quantitative analysis of a self-supervised approach for sinus reconstruction using endoscopic sequences paired with optical tracking and high-resolution computed tomography acquired from nine ex-vivo specimens. Our results show that the generated reconstructions are in high agreement with the anatomy, yielding an average point-to-mesh error of 0.91 mm between reconstructions and CT segmentations. However, in a point-to-point matching scenario, relevant for endoscope tracking and navigation, we found average target registration errors of 6.58 mm. We identified that pose and depth estimation inaccuracies contribute equally to this error and that locally consistent sequences with shorter trajectories generate more accurate reconstructions. These results suggest that achieving global consistency between relative camera poses and estimated depths with the anatomy is essential. In doing so, we can ensure proper synergy between all components of the pipeline for improved reconstructions that will facilitate clinical application of this innovative technology

Particle tracking velocimetry and accelerometry (PTVA) measurements applied to quasi-two-dimensional multi-scale flows

Accepted versio

Experimental study and analysis of lubricants dispersed with nano Cu and TiO2 in a four-stroke two wheeler

The present investigation summarizes detailed experimental studies with standard lubricants of commercial quality known as Racer-4 of Hindustan Petroleum Corporation (India) dispersed with different mass concentrations of nanoparticles of Cu and TiO2. The test bench is fabricated with a four-stroke Hero-Honda motorbike hydraulically loaded at the rear wheel with proper instrumentation to record the fuel consumption, the load on the rear wheel, and the linear velocity. The whole range of data obtained on a stationery bike is subjected to regression analysis to arrive at various relationships between fuel consumption as a function of brake power, linear velocity, and percentage mass concentration of nanoparticles in the lubricant. The empirical relation correlates with the observed data with reasonable accuracy. Further, extension of the analysis by developing a mathematical model has revealed a definite improvement in brake thermal efficiency which ultimately affects the fuel economy by diminishing frictional power in the system with the introduction of nanoparticles into the lubricant. The performance of the engine seems to be better with nano Cu-Racer-4 combination than the one with nano TiO2