Breast Cancer is deadly and the most common type of cancer in the world. Based on machine learning algorithm such as random forest, XGBoost, logistic regression and K-nearest neighbor, this paper establishes different models to predict and classify breast cancer. Machine Learning has potential to predict breast cancer based on features hidden in data. Breast Cancer is a Multifactorial disease and the most common cancer in women around worldwide with approx 30% of female cancers. Over past 30 years the death rate has decreased while disease is increased.
1. In whole coding part the first set of code is to convert digicom dataset files into PNG Images.
2. The second set of command is for detection on images, user have to provide input single image and model will predict that it is malignant or benign.
3. There are two type of models
i). first model is for only image based prediction
ii). Image + Heatmap Prediction
To run all the commands first you have to setup all the models and files that can be done with two shell script to setup you need to run those two python shell script.
Breast Arterial Classification 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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