no code implementations • 4 Mar 2019 • Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Mark Anastasio, Hua Li
Accurately counting cells in microscopic images is important for medical diagnoses and biological studies, but manual cell counting is very tedious, time-consuming, and prone to subjective errors, and automatic counting can be less accurate than desired.
no code implementations • 1 Mar 2019 • Shenghua He, Kyaw Thu Minn, Lilianna Solnica-Krezel, Hua Li, Mark Anastasio
A domain adaptation model (DAM) is built to map experimental images (the target domain) to the feature space of the source domain.
no code implementations • 10 Jul 2018 • Shenghua He, Jie Zheng, Akiko Maehara, Gary Mintz, Dalin Tang, Mark Anastasio, Hua Li
Traditional machine learning based methods, such as the least squares support vector machine and random forest methods, have been recently employed to automatically characterize plaque regions in OCT images.