1.Functional requirements and Usability requirements
Objective is to present software (deep learning models) tailored for detecting pneumonia infection cases such as viral cases towards screening and diagnosing COVID-19 on chest x-ray images.

-In many cases, COVID-19 disease causes pneumonia. Pulmonary infections can be observed through radiography images.
-The facilities necessary to perform chest x rays are a X ray machine.
-Chest x-ray uses a very small dose of ionizing radiation to produce pictures of the inside of the chest.
-Installed software on Windows desktop/ browser access.
-Patient chest x ray images posteroanterior and anteroposterior each view specified in each image.
-Radiographer, Clinicians, Technicians can then upload jpeg/png images to the software for analysis and diagnosis.
-Results returned on each images indicating whether or not the patient is infected, as well as those with the highest infection rates, flagged of further medical attention and treatment.
-Over time the software's ability to calculate infection rate and output, true positive cases and true negatives will improve in precision and accuracy, as the convolutional neural network improves with every use, using machine learning.


METHOD

• Automatically analyzing query chest x-ray images towards screening & diagnosing COVID-19
• Use software (deep learning) models over sets of chest x-ray images towards screening viral pneumonia. Chest x-ray test images of COVID-19 infected patients are successfully diagnosed
• Based on statistical tools (logistic regression and statistical tests) and realistic data, studies on COVID-19-related death risk factor namely, age, comorbidity,and infection rate indicator which will be determined by the software as well
• Sample an open source dataset of x-ray images for patients who have tested positive for COVID-19
• Sample “normal” , “bacterial pneumonia”, “viral pneumonia” x-ray images
• Train a CNN to automatically detect COVID-19 in X-ray images via the dataset we created
• Derive infection rate formular and Evaluate the results

A typical workflow of the chest x-ray analysis supported by the CNN in the detection of COVID-19




3.Safety requirement

1.Operators ,holders and other people should be protected from ionizing radiation by: operator must stand behind the protective barrier at the controls during exposure, all individuals must be protected from the primary beam atleast 0.5 mm lead equivalency and from scatter radiation by atleast 0.22 mm and X- ray room must be secured during exposure.
2.Safety Personal Protective Equipment ( gloves, a mask, goggles and a gown ) should be worn at all times.
3.The equipment should be washed and sterilized after each use to practice infection control.
4.X-ray equipment produces radiation when energized therefore staff should be trained on operating it.
5.only individuals required for radiography must be in the room during exposure
6.Aluminum filtration shall be placed in the primary beam to reduce the quantity of soft X-rays to the patient

4.Interaction requirements (Describe how the product should work with other systems)

1. To get the best quality x-ray films, x-ray technicians are required to manipulate the equipment and the patient for perfect alignment.
2. Patient can lie down or sit on a chair, depending on the environment conditions at the time.