- Abstract: Deep Learning for medical imaging has been on the forefront of its numerous applications, thanks to its versatility and robustness in deployment. In this paper we explore various classification methodologies that are employed for datasets of relatively small in size to actually train a deep learning algorithm from scratch. Thyroid ultrasound images are classified using a small CNN from scratch, trans-fer learning and fine-tuning of Inception-v3, VGG-16. We present a comparison of the aforementioned methods through accuracy, sensitivity and specificity.
- Keywords: Transfer Learning, Finetuning, Image Classification
- Author Affiliation: Sri Sathya Sai Institute of Higher Learning