Sharif Digital Repository

Local mean-field models (MFMs) describe regional brain activities by some connected differential equations. In an overall view, constituting variables of these differential equations can be divided to very fast, fast and slow variables. In this article we propose a method that can be used to determine role of a slow variable in behavior of MFMs. Very fast variables can be adiabatically removed from the equations. Isoclines of fast and slow variables and their corresponding vector field can provide valuable information about model behavior and role of the slow variable in it. The vector field of our interested MFM that is an enhanced MFM designed specially for general anesthesia, is a 3D... 

Delivering first aid before transferring patients to hospital is among keys to survival. Moreover, calling the emergency center as soon as possible and providing brief information about the patient are helpful for the emergency center to dispatch specialized medical team and equipments proportionate to the conditions of the patient. Mobile phone is a device which many people use and always carry with them. One more thing is that SMS (Short Message Service) stands as a favorite service in mobile network, used to exchange short messages and featuring low cost, non-stop lines of dispatch, possibilities for offline work and so forth. This paper puts forward procedures of calling an emergency... 

Accurate gross tumor volume (GTV) segmentation in esophagus CT images is a critical task in computer aided diagnosis (CAD) systems. However, because of the difficulties raised by the contrast similarity between esophageal GTV and its neighboring tissues in CT scans, this problem has been addressed weakly. In this paper, we present a 3D end-to-end method based on a convolutional neural network (CNN) for this purpose. We leverage design elements from DenseNet in a typical U-shape. The proposed architecture consists of a contractile path and an extending path that includes dense blocks for extracting contextual features and retrieves the lost resolution respectively. Using dense blocks leads to... 

Point Set Registration (PSR) of anatomic parts is used in different fields such as Patient Specific Implant (PSI) design in Computer Assisted Surgery (CAS) procedure. We designed a modified rigid PSR method based on student's-t mixture model. The proposed method is compared with Coherent Point Drift (CPD) registration method. Higher convergence speed and the lower error value are the advantages of the suggested algorithm in compare with CPD. In our method, the number of iterations decreases by about 69%, and the final error improvement was about 7% in comparison with CPD. The robustness of the proposed algorithm makes it beneficial to be used in the procedure of designing PSI in both... 

Chest computed tomography (CT) has played an essential diagnostic role in assessing patients with COVID-19 by showing disease-specific image features such as ground-glass opacity and consolidation. Image segmentation methods have proven to help quantify the disease and even help predict the outcome. The availability of longitudinal CT series may also result in an efficient and effective method to reliably assess the progression of COVID-19, monitor the healing process and the response to different therapeutic strategies. In this paper, we propose a new framework to identify infection at a voxel level (identification of healthy lung, consolidation, and ground-glass opacity) and visualize the... 

Lung cancer is one of the most common diseases for human beings everywhere throughout the world. Early identification of this disease is the main conceivable approach to enhance the possibility of patients’ survival. In this paper, a k-Nearest-Neighbors technique, for which a genetic algorithm is applied for the efficient feature selection to reduce the dataset dimensions and enhance the classifier pace, is employed for diagnosing the stage of patients’ disease. To improve the accuracy of the proposed algorithm, the best value for k is determined using an experimental procedure. The implementation of the proposed approach on a lung cancer database reveals 100% accuracy. This implies that one... 

Labeling vertebral discs from MRI scans is important for the proper diagnosis of spinal related diseases, including multiple sclerosis, amyotrophic lateral sclerosis, degenerative cervical myelopathy and cancer. Automatic labeling of the vertebral discs in MRI data is a difficult task because of the similarity between discs and bone area, the variability in the geometry of the spine and surrounding tissues across individuals, and the variability across scans (manufacturers, pulse sequence, image contrast, resolution and artefacts). In previous studies, vertebral disc labeling is often done after a disc detection step and mostly fails when the localization algorithm misses discs or has false... 

This paper focuses on the biomechanical aspects of the human lower extremity loading condition during backpack load carrying. A biomechanical framework was generated with the aim of employing a block-oriented structure of Simulink integrated with the Virtual Reality Toolbox of MATLAB software to provide a simulation study of the musculoskeletal system in a virtual environment. In this case, a ten-degrees-of-freedom musculoskeletal model actuated with sixteen muscles in each leg was utilized to simulate movement in the sagittal plane. An inverse dynamics based optimization approach was employed to estimate the excitation level of the muscles. In addition, distributions of the mechanical power... 

Schizophrenia is a severe brain disease that influences the behaviour and thought of person. These effects may fail in achieving the expected levels of interpersonal, academic, or occupational functioning. Although the underlying mechanism is not yet clear, the early detection of schizophrenia is an attractive and challenging research area. There are differences in brain connections of patients and healthy people. This study presents a new computer-aided diagnosis (CAD) method to diagnose schizophrenia (SZ) patients from normal control (NC) people by using the rest-state functional magnetic resonance imaging (R-fMRI) data. fMRI data has a huge dimension, and extracting efficient features is... 

Inverse dynamics analysis as well as the generation of an optimal goal oriented human motion both lead to the problem of finding suitable activations of the redundant muscles involved. This paper employs an iterative feedback tuning approach to perform the forward dynamics simulation of the human musculoskeletal system during level walking. A modified form of the proportional-integral-derivative (PID) controller is proposed to stabilize the movement and provide tracking of problems of the desired lower extremity joint profiles. Controller parameters were determined iteratively using an optimization algorithm to minimize tracking errors during forward dynamics simulation. Static optimization...