36 citations · 42 across the 5 of their papers we have counts for
5 papers
Multiple Instance Learning for Brain Tumor Detection from Magnetic Resonance Spectroscopy Data
Diyuan Lu, Gerhard Kurz, Nenad Polomac +3
We apply deep learning (DL) on Magnetic resonance spectroscopy (MRS) data for the task of brain tumor detection. Medical applications often suffer from data scarcity and corruption…
Human-Expert-Level Brain Tumor Detection Using Deep Learning with Data Distillation and Augmentation
Diyuan Lu, Nenad Polomac, Iskra Gacheva +2
The application of Deep Learning (DL) for medical diagnosis is often hampered by two problems. First, the amount of training data may be scarce, as it is limited by the number of p…
Staging Epileptogenesis with Deep Neural Networks
Diyuan Lu, Sebastian Bauer, Valentin Neubert +3
Epilepsy is a common neurological disorder characterized by recurrent seizures accompanied by excessive synchronous brain activity. The process of structural and functional brain a…
Towards Early Diagnosis of Epilepsy from EEG Data
Diyuan Lu, Sebastian Bauer, Valentin Neubert +3
Epilepsy is one of the most common neurological disorders, affecting about 1% of the population at all ages. Detecting the development of epilepsy, i.e., epileptogenesis (EPG), bef…
Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy
Diyuan Lu, Jochen Triesch
Epilepsy is the fourth most common neurological disorder, affecting about 1% of the population at all ages. As many as 60% of people with epilepsy experience focal seizures which o…