Author

J. Sivakumar

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Open access Sep 2026

An end-to-end deep learning approach for lung nodule segmentation and classification using LN-DETR and deep sequential convolutional harmonic networks.

A Deep Sequential Convolutional Neural Harmonic Network (DSeqCH-Net) is devised for lung nodule classification from Computed Tomography (CT) scans, which achieved the highest True Negative Rate (TNR), accuracy, and True Positive Rate (TPR) of 95.813%, 96.745%, and 97.643%.

S. Ramani, S. Rajeshkannan, J. Sivakumar · Computers in Biology and Med... · 0 citations