Blood Cancer Detection using Deep Learning
Blood Cancer Detection using Neural Networks introduces a diagnostic tool that aids in the early detection of blood cancer through medical imaging analysis. By training on diverse datasets, the neural network can identify abnormalities in blood cell morphology, providing timely and accurate insights for medical professionals. This application enhances the efficiency of cancer diagnosis, potentially leading to early intervention and improved patient outcomes.
Blood Cell Counting using Image Processing
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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