• Project Title: Lung Cancer Detection with Deep Learning Convolutional Neural Networks

  • BASIS Advisor: Ms. Bhattacharya

  • Internship Location: Duke University

  • Onsite Mentor: Dr. Yiran Chen

Lung cancer is currently the deadliest disease in the world, killing 1.3 million people annually. Due to the large amount of work required to determine whether a patient has lung cancer, it would be extremely beneficial if doctors could use rapid-developing computer technology to help optimize the screening process of lung cancer. At Duke University, I will build an AlexNet and a VGG derived lung cancer detector with aggressive data augmentation, altering the last branch by transferring the original ability of classifying typical images to nodule images. I believe that my AlexNet and VGG models will classify a cancerous nodule correctly around 93% and 95% of the time respectively. In comparison, human doctors only correctly detect cancerous nodules 23% of the time. I will further improve my model through the AIFT algorithm, which continuously fine-tunes the CNN by incrementally enlarging the training dataset with newly annotated samples. Thus, I can reduce the number of labels without a significant sacrifice in accuracy. I hope that my research will be a convenient assistive tool in lung cancer diagnosis and change the world by saving millions of lives.