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Full-Text Articles in Architecture
Glaucoma Diagnosis Using Hybrid Neural Encoder Decoder Based Unet Hybrid Inception, Akanksha Bali, Vibhakar Mansotra
Glaucoma Diagnosis Using Hybrid Neural Encoder Decoder Based Unet Hybrid Inception, Akanksha Bali, Vibhakar Mansotra
Mansoura Engineering Journal
The anatomy of the retinal fundus picture, which includes the optic disc, affects how glaucoma characteristics are extracted. One of the main causes of blindness in the globe is glaucoma. Correct glaucoma screening in its early phases is difficult since the condition only becomes apparent when its symptoms are severe. If glaucoma is not treated, the optic nerve head (ONH) will be harmed, resulting in vision loss. Nevertheless, there are currently not enough eye experts accessible, and eye screening is personal, time-consuming and labor-intensive. Therefore, this is a real issue that can be addressed by automatically diagnosing glaucoma using deep …
Deep Learning Based Classification Of Focal Liver Lesions With 3 And 4 Phase Contrast-Enhanced Ct Protocols, Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf
Deep Learning Based Classification Of Focal Liver Lesions With 3 And 4 Phase Contrast-Enhanced Ct Protocols, Ahmed El-Emam, Hossam El-Din Moustafa, Mohamed Moawad, Mohamed Aouf
Mansoura Engineering Journal
It had been noticed that 3-phase and 4-phase computed tomography protocols with contrast serve as standard examinations for diagnosing liver tumors. Additionally, many patients require periodic follow-up, which entails significant radiation exposure for them. Advancements in image processing facilitate automated liver lesion segmentation. However, the challenge remains in classifying these small lesions by doctors, especially when the liver has different types of lesions with very little intensity difference. Therefore, deep learning can be utilized for the classification of liver lesions. The present work introduces a CNN-based module for the classification of liver lesions. The module consists of four stages: data …
Classification Of Kidney Masses Using Convolution Neural Network, Nada M. Yakout, Eman Abdelhalim, Abdalla Abdelhalim, Hossam El-Din Moustafa
Classification Of Kidney Masses Using Convolution Neural Network, Nada M. Yakout, Eman Abdelhalim, Abdalla Abdelhalim, Hossam El-Din Moustafa
Mansoura Engineering Journal
Classification of tumors among kidney masses (KM) through deep neural networks is one of the most important applications for detecting the disease at an early stage. It can increase patient survival rates, prevent mass growth, and prevent complications. Preoperative multi-phase abdominal Contrast Enhancement Computed Tomography (CE-CT) is widely used to detect lesions of kidney masses in order to avoid unneeded biopsy or surgery. However, decisions about treatment are difficult because of inter-observer variability caused by minute variations in the imaging characteristics of mass sub-types. In this study, we offer a comprehensive deep learning model using a Convolutional Neural Networks(CNN) for …
Integrative Software Design For Hospital Information Systems, Esraa M. Hashem, Mahmoud F. Y. Shalaby, Mai S. Mabrouk, Samir.Y. Marzouk
Integrative Software Design For Hospital Information Systems, Esraa M. Hashem, Mahmoud F. Y. Shalaby, Mai S. Mabrouk, Samir.Y. Marzouk
Mansoura Engineering Journal
The Hospital Information System is a huge, integrated system that meets these needs. The primary objective of any hospital information system is to produce high-quality and timely reporting for evidence-based decisions and interventions. The electronic health record is essential in creating uniform data formats and terminology for both corporate and public sector reporting needs. In this study, we design a hospital information system that focuses on the tools, and techniques necessary to improve the gathering, archiving, retrieval, and application of information in biomedicine and the healthcare industry. With the intention of bringing about progress, the idea of a paperless hospital …