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Targeted Magnetic Drug Delivery (TMDD) is a promising approach that is relevant to multimodal cancer therapy. Therefore, it is important to develop mathematical models of TMDD to serve as a second opinion for medical practitioners. A majority of TMDD models represent a mixture of blood and nanoparticles as a one-phase solution. Therefore, the magnetic nanoparticles (MN) and the blood follow the same streamlines. The existing two-phase models are usually one-way coupled, i.e., the blood flow has a strong impact on the MN flow. However, the inverse impact of the MN on the dynamics of the blood is not included in the models. To eliminate these drawbacks, the MN in a blood vessel is simulated by a two-phase (solid-liquid) flow in a 2D rectangular channel. The problem is governed by two-way coupled momentum and temperature equations for the blood flow and the MN. The numerical procedure invokes the stream function–vorticity formulation and an efficient numerical method on a finite-difference grid. The general formulation for the effect of the magnetic field is that of Biomagnetic fluid Dynamics (BFD) which incorporates both principles of MagnetoHydroDynamics (MHD) and FerroHydroDynamics (FHD). The model, validated by experimental results, has been applied to analyze the formation of and the zones of TMDD, where the velocity of the blood flow is low and the velocity of the MN flow is high towards the magnet. Additionally, we analyze the formation of vortices relative to the magnetic force (MFs), the drag force (DF). The model is capable of simulating the (reverse) impact of the MN on the blood flow and evaluates the corresponding changes in the vorticity. The result shows that the MHD effect causes disturbance in blood flow. It reduces blood flow and minimizes the large vortices created by FHD. Moreover, the concentration of medical drugs is another essential result. These medications have the potential to harm healthy cells. Therefore, the effects of medical drugs have b

Background: The ultrasound test for cancer screening is low-cost and non-invasive. A major drawback is that multiplicative speckle noise can jeopardize the efficiency of the test. This research proposes a new algorithm to reduce noise and segment breast ultrasound. Methods: The method is in two stages. Stage one is based on a combination of the multiscale approach, the Wiener filter, and a new combination of wavelet-transform denoising and the anisotropic Perona-Malik-type filter. In the second stage, pre-processed image is transformed into multiscale images, and then, a boundary efficient superpixel decomposition of the multiscale images is created. Finally, the tumor region is generated by the boundary graph cut segmentation method. Results: The algorithm has been tested on 50 synthetic images degraded by speckle noise with varying intensity and 250 breast ultrasound (BUS) images from two datasets. The results are compared with selected state-of-the-art filters. The proposed approach shows better performance in terms of standard evaluation measures. The results are compared with ground truth by the DICE coefficient, the Jaccard coefficient, and the Hausdorff distance. The proposed filter also achieves high accuracy in terms of these segmentation measures. Conclusions: The proposed two-stage algorithm achieves better accuracy, compared to selected state-of-the-art methods applied to BUS images.

In cutting field, especially for five axis milling machine, managing scallop height and kinematic error is an important factor because it mainly affects to the produced part’s quality. Most of the researcher tried to improve only one factor and assume the remaining factor is in the ideal condition, however in reality both those two factors scallop height and kinematic error mutually affect to each other, result in the quality of the machined part. In this research, a novel constant scallop toolpath generation for ball end mill considering non-linear KE trajectory of five axis milling machine is developed. Within the toolpath generation process, a new proposed scallop evaluation method is suggested with the improvement of the accuracy up to 12% in term of average scallop height compared with the conventional methods. Through the produced solid part model in simulation program Vericut 8.2, we can see that the proposed toolpath generation method works on the parametric as well as the free form STL surfaces, the part quality looks good by the uniform distribution of the scallop height as well as the tool trace.

Toolpath generation for five-axis machining of triangulated surfaces using a vector field of preferred direction (VFPD) is an important problem in toolpath optimization. Although various methods have been proposed to construct such alignment toolpaths, the resulting toolpaths still contain large number of turning points, produce large kinematic errors, and include redundant machining. Many CNC programs are so large that they could not be loaded into the machine operating memory and still their machining efficiency is low and the machining time is long. In this dissertation, new VFPD-based techniques are proposed to generate toolpaths on triangulated surfaces. The methods include pattern-based toolpath generation, statistically significant vector field flow method, and transfinite interpolation. The proposed algorithms have been verified by virtual and real machining, and compared with recent state-of-the-art methods. The experiments show a significant improvement in terms of the machining time and the surface quality.