Rafeek Yanni - Academia.edu (original) (raw)
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Papers by Rafeek Yanni
International Journal of Online and Biomedical Engineering (iJOE), 2021
Image segmentation of the medical image and its conversion into anatomical models is an important... more Image segmentation of the medical image and its conversion into anatomical models is an important technique and main point in computer vision (CV) and image processing (IP), training tools that are used routinely in the fields of medicine and surgery. Segmenting images and converting them into a model that depends on its work on the different algorithms and the extent of technological advancement and method of application. The advancement of segmentation algorithms has led to the possibility of creating three-dimensional models for the patient to study without endangering his life. This paper describes a combination of two fields of solving segmentation problem to convert through the workflow of a hybrid algorithm structure Convolutional neural network (CNN, Active Contour & Deep Multi-Planar) and seg3d2 to switch DICOM medical rays “Digital Imaging and Communications in Medicine” into a 3Dimintional model, using data from active contour to be the input of deep learning. This resear...
Int. J. Online Biomed. Eng., 2020
The development of the internet of things makes all objects interconnected, making it the next te... more The development of the internet of things makes all objects interconnected, making it the next technical revolution. It has been applied extensively in various sectors, including agriculture, smart parking, and industrial places, and most importantly, in the health monitoring process.[1] To monitor or its application in surgery procedure is one of its uses in healthcare. This project proposes a system aimed to solve sudden occurrences and emergencies during the operation process. The system's objective is to minimize deaths and other possible effects of the phenomena by connecting the surgeon with an online specialist all over the world. The proposed system architecture is based on medical sensors measuring the patient's physical parameters utilizing wireless sensor networks. The sensors send the parameters to the Raspberry Pi, which converts them to digital data. The digital data is transferred over the wireless network to the server, which is then sent to the cloud environ...
International Journal of Online and Biomedical Engineering (iJOE), 2021
Image segmentation of the medical image and its conversion into anatomical models is an important... more Image segmentation of the medical image and its conversion into anatomical models is an important technique and main point in computer vision (CV) and image processing (IP), training tools that are used routinely in the fields of medicine and surgery. Segmenting images and converting them into a model that depends on its work on the different algorithms and the extent of technological advancement and method of application. The advancement of segmentation algorithms has led to the possibility of creating three-dimensional models for the patient to study without endangering his life. This paper describes a combination of two fields of solving segmentation problem to convert through the workflow of a hybrid algorithm structure Convolutional neural network (CNN, Active Contour & Deep Multi-Planar) and seg3d2 to switch DICOM medical rays “Digital Imaging and Communications in Medicine” into a 3Dimintional model, using data from active contour to be the input of deep learning. This resear...
Int. J. Online Biomed. Eng., 2020
The development of the internet of things makes all objects interconnected, making it the next te... more The development of the internet of things makes all objects interconnected, making it the next technical revolution. It has been applied extensively in various sectors, including agriculture, smart parking, and industrial places, and most importantly, in the health monitoring process.[1] To monitor or its application in surgery procedure is one of its uses in healthcare. This project proposes a system aimed to solve sudden occurrences and emergencies during the operation process. The system's objective is to minimize deaths and other possible effects of the phenomena by connecting the surgeon with an online specialist all over the world. The proposed system architecture is based on medical sensors measuring the patient's physical parameters utilizing wireless sensor networks. The sensors send the parameters to the Raspberry Pi, which converts them to digital data. The digital data is transferred over the wireless network to the server, which is then sent to the cloud environ...