Attention Enhanced InceptionNeXt-Based Hybrid Deep Learning Model for Lung Cancer Detection

Lung cancer is the most common cause of cancer-related mortality globally. Early diagnosis of this highly fatal and prevalent disease can significantly improve survival rates and prevent its progression. Computed tomography (CT) is the gold standard imaging modality for lung cancer diagnosis, offering critical insights into the assessment of lung nodules. We present a hybrid deep learning model that integrates Convolutional Neural Networks (CNNs) with Vision Transformers (ViTs). By optimizing and integrating grid and block attention mechanisms with InceptionNeXt blocks, the proposed model effectively captures both fine-grained and large-scale features in CT images. This comprehensive approach enables the model…

• AU
  Alfaisal University