Lung cancer classification using neural networks for CT images

By Jinsa Kuruvilla, Kandasamy Gunavathi. Comput. Methods Programs Biomed., 2014

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Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images (2017, methodology): “In [6], Kuruvilla and Gunavathi proposed a methodology based on texture features using the artificial neural network (ANN), with an accuracy rate of 93.”
A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework (2021, methodology): “In 2014, Kuruvilla and Gunavathi proposed a CAD method for lung cancer classification based on the analysis of CT scan images [16].”
Lung Nodule Classification Using Deep Features in CT Images (2015, methodology): “Kuruvilla et al. [13] have used six distinct parameters including skewness and fifth & sixth central moments extracted from segmented single slices containing 2 lungs along with the features mentioned in [12] and have trained a feed forward back propagation neural network with them to evaluate…”