Hossein Najaf-Zadeh

High-accuracy lung region segmentation and injury classification using deep networks

This study developed and evaluated a hybrid deep learning framework for automated lung segmentation and multi-class severity classification in chest CT scans, addressing key methodological gaps including heterogeneous dataset labeling, pseudo-label bias in segmentation, limited i...

Multi-Backbone U-Net segmentation and interpretable hybrid deep learning classification for lung cancer detection in chest CT images

Lung cancer remains the leading cause of cancer-related mortality worldwide, and its early and accurate diagnosis from chest CT imaging is complicated by overlapping radiological features between benign and malignant lesions, as well as by the limited cross-institution validation...