Lung Cancer Detection from CT Images: Modified Adaptive Threshold Segmentation with Support Vector Machines and Artificial Neural Network Classifier.
Sneha S NairV N Meena DeviSaju BhasiPublished in: Current medical imaging (2023)
This innovation may have a major impact on the worldwide rate of lung cancer rate due to its ability to detect lung tumors in their earliest stages when they are most amenable to being avoided and treated. This method is useful because it provides more information and facilitates quick, precise decision-making for doctors diagnosing lung cancer in their patients.
Keyphrases
- neural network
- deep learning
- end stage renal disease
- decision making
- newly diagnosed
- convolutional neural network
- ejection fraction
- chronic kidney disease
- prognostic factors
- magnetic resonance imaging
- healthcare
- magnetic resonance
- image quality
- patient reported outcomes
- positron emission tomography
- quantum dots
- sensitive detection