In recent years there has been an increased thrust to understand and quantify the complex information conveyed by medical images. Developing modern computational techniques that offer the potential for extracting diverse and complex information from imaging data and applying these to a plethora of clinical studies is crucial. These techniques not only support precise quantification but also overcome the limitations of subjective visual interpretation. Furthermore, these methods can facilitate finding specific markers that relate to pathologies as well as aid in treatment planning.View Our Campus
"HR-CAM: Precise Localization of pathology using multi-level learning in CNNs"
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019
"Atrophy of cerebellar peduncles in essential tremor: a machine learning–based volumetric analysis"
European radiology, 2019
"Clinical correlates of abnormal subcortical volumes in Essential Tremor”
Journal of Neural Transmission, 2019.