학술논문

Applications of images processing algorithms for bacterial meningitis diagnosis: Bacterial image processing in Mathlab
Document Type
Conference
Source
2017 9th International Conference on Electronics, Computers and Artificial Intelligence (ECAI) Electronics, Computers and Artificial Intelligence (ECAI), 2017 9th International Conference on. :1-4 Jun, 2017
Subject
Components, Circuits, Devices and Systems
Power, Energy and Industry Applications
Robotics and Control Systems
Fluorescence
Microorganisms
Image processing
Mobile handsets
Logistics
Biomedical optical imaging
Optical imaging
medical imaging
image proccessing
algorithms
fluorescence
Language
Abstract
Paper presents firstly the principle of fluorescent detection to be implemented for rapid diagnosis of bacterial and non-bacterial meningitis. The acquired image by the mobile phone equipped with adapted lens is prepared by special techniques including denoising, emphasizing the useful signals, highlight and setting thresholds. Secondly, the prepared image is cropped in individual matrix's and converted in black and white tones submitted for original processing algorithm implemented in MathLab. The implemented processing algorithm extract the model parameters to identify the meningitis type. Application was implemented on the android mobile phone and can be used in emergencies cases for rapid decisions. The acquired images can also be sent by mobile phone to emergency point management data base stored and sent for more precise investigations in specialised laboratories.