Lung Cancer Detection using CT Scan Images
The Lung Cancer Detection project utilizes neural networks to analyze medical imaging data for the early identification of lung cancer. By processing CT scans or X-rays, the system assists healthcare professionals in detecting abnormalities and potential cancerous nodules. The neural networks enhance diagnostic accuracy, enabling timely intervention and improving patient outcomes. This application stands at the forefront of medical advancements, providing a valuable tool for early cancer detection.
Project Working of Lung Cancer Detection using Chest X-Ray Images:-
Chest Cancer Detection is machine learning based project designed using tkinter module of python and developed using python programming language. InceptionV3 is the algorithm that is used to train the model.
This machine learning project is trained on large dataset of image that contain four classes.
-
- Large cell carcinoma
- Normal
- Squamous cell carcinoma
- Adenocarcinoma
We have to run the python script then User Interface will open in that there will be home page, about section and exit button. User have to upload image from dataset and model will predict the type of cancer with accuracy.
Aim of the tool is to determine disease in the CT scan image. If disease is found, it classifies the class of diseases.
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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