Nodule Classification

Nodule classification, primarily focusing on lung and thyroid nodules, aims to automatically distinguish benign from malignant nodules in medical images using computer-aided diagnosis (CAD) systems. Current research emphasizes improving model accuracy and interpretability through techniques like self-supervised learning, encoder-decoder networks, transformer architectures, and the integration of multimodal data (imaging and electronic health records). These advancements hold significant potential for improving the speed and accuracy of cancer diagnosis, leading to earlier interventions and better patient outcomes.