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