A deep learning method using SPECT images to diagnose remaining thyroid tissue post-thyroidectomy

After total thyroidectomy, Single-photon emission computed tomography (SPECT) is used to diagnose whether thyroid tissue remains in patients' bodies. Physicians visually diagnose the residual thyroid tissue in patient base on their expertise, so it is difficult for making a quick and accurate diagnostic. In present, Computer-aided Diagnosis systems (CAD) are becoming more widely in medical treatment, thyroid cancer is a potential field where CAD can improve diagnostic accuracy. This paper proposes a novel approach for diagnosing whether residual thyroid tissues remain in patient using thyroid SPECT scintigraphy by fine-tuning pre-trained Deep neural networks. Our proposed method achieved sensitivity of 84.85% and specificity is 89.11%, these results demonstrate that CAD is promising in diagnosing remaining thyroid tissue after total thyroidectomy.