Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions

Purpose: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to perform delicate procedures on a beating heart, avoiding the complications of cardiac arrest. This advantage comes with the price of having to deal with a dynamic target which presents technical challenges for the surgical system. In this work, we propose a solution for cardiac motion estimation. Methods: Our estimation approach uses a variational framework that guarantees preservation of the complex anatomy of the heart. An advantage of our approach is that it takes into account different disturbances, such as specular reflections and occlusion events. This is achieved by performing a preprocessing step that eliminates the specular highlights and a predicting step, based on a conditional restricted Boltzmann machine, that recovers missing information caused by partial occlusions. Results: We carried out exhaustive experimentations on two datasets, one from a phantom and the other from an in vivo procedure. The results show that our visual approach reaches an average minima in the order of magnitude of 10-7 while preserving the heart’s anatomical structure and providing stable values for the Jacobian determinant ranging from 0.917 to 1.015. We also show that our specular elimination approach reaches an accuracy of 99% compared to a ground truth. In terms of prediction, our approach compared favorably against two well-known predictors, NARX and EKF, giving the lowest average RMSE of 0.071. Conclusion: Our approach avoids the risks of using mechanical stabilizers and can also be effective for acquiring the motion of organs other than the heart, such as the lung or other deformable objects.Peer ReviewedPostprint (published version

DESIGN, OPTIMIZATION AND IN VITRO EVALUATION OF ANTIFUNGAL ACTIVITY OF NANOSTRUCTURED LIPID CARRIERS OF TOLNAFTATE

Objective: The main purpose of this work was to prepare tolnaftate (TOL) loaded nanostructured lipid carriers (NLCs), Evaluate its characteristics and in vitro release study. Methods: Tolnaftate loaded Nanostructured lipid carriers were prepared by the high shear homogenization method using different liquid lipids types (DERMAROL DCO® and DERMAROL CCT®) and concentrations, different concentration ratios of tween80® to span20® and different homogenization speeds. All the formulated nanoparticles were subjected to particle size (PS), zeta potential (ZP), polydispersity index (PI), drug entrapment efficiency (EE), Differential Scanning Calorimetry (DSC), Transmission Electron microscopy (TEM), release kinetics and in vitro release study was determined. Results: The results revealed that NLC dispersions had spherical shapes with an average size between 154.966±1.85 nm and 1078.4±103.02 nm. High entrapment efficiency was obtained with negatively charged zeta potential with PDI value ranging from 0.291±0.02 to 0.985±0.02. The release profiles of all formulations were characterized by a sustained release behavior over 24 h and the release rates increased as the amount of surfactant decreased. The release rate of TOL is expressed following the theoretical model by Higuchi. Conclusion: From this study, It can be concluded that NLCs are a good carrier for tolnaftate deliver

V-ANFIS for Dealing with Visual Uncertainty for Force Estimation in Robotic Surgery

Accurate and robust estimation of applied forces in Robotic-Assisted Minimally Invasive Surgery is a very challenging task. Many vision-based solutions attempt to estimate the force by measuring the surface deformation after contacting the surgical tool. However, visual uncertainty, due to tool occlusion, is a major concern and can highly affect the results' precision. In this paper, a novel design of an adaptive neuro-fuzzy inference strategy with a voting step (V-ANFIS) is used to accommodate with this loss of information. Experimental results show a significant accuracy improvement from 50% to 77% with respect to other proposals.Peer ReviewedPostprint (published version

Waste management and material recycle as a potential of sustainable building envelope for low income housing

Energy crisis and pollution are two main challenges that hinder sustainable development in Egypt. Electricity represents the major part of Egypt energy; however, the Egyptian electricity consumption is increasing much faster than capacity expansions which causes electrical blackout. Egypt’s electricity prices began to rise starting July 2015 as part of a plan to reduce the government subsistence on electricity and force people to rationalize the consumption. Residential buildings are representing 40% of the total energy consumption, in Egypt. This is mainly due to a poor design of buildings, with no concern to neither materials used nor building tightness. This results in high cold bridges that increase the heat transfer from the outside to the inside of building spaces leading to high internal discomfort. Concomitantly, impacting the increase of energy consumption in cooling and heating today in most Egyptian buildings. This paper is part of a multiphase experimental research work that represents an empirical comparative study of different thermal walls’ created from recyclable materials. The results would be analyzed in details, developed, and evaluated in terms of; technical, economic and environmental aspects and conditions. As a result of this study; the walls of such economical homes will be able to resist heat transfer with lowest possible cost and consume less energy