Κωδικός Authors Τίτλος εργασίας
P.6.1 Christoulakis et al Identification of low-grade gliomas on brain MRI based on deep neural networks
P.6.2 Nalentzi et al Image analysis of brain MRI for Alzheimer’s disease based on radiomics: preliminary results
P.6.3 Koumatzidis et al Cyclic recurrence, quarantine and vaccination policies in epidemiology mathematical models
P.6.4 Chatzisavvas et al Investigation of X-Ray tube target material, anode angle and filter at 120keV and 30keV using Monte Carlo.
P.6.5 Koussis et al Atrophy evaluation using hippocampus and cerebrum volumes, as measured by volBrain software, in correlation of Scheletens’ scale
P.6.6 Koussis et al P-Atrophy, a computer program fed with age and hippocampus volume, as measured by volBrain software, calculates Scheltens’ scale grade and evaluates atrophy
P.6.7 Broumpoulis et al Artificial Intelligence-based models for predicting cardiovascular disease risk
P.6.8 Raptis et al Artificial Intelligence in Lung Radiotherapy
P.6.9 Michas et al Efficient Machine Learning Algorithms for Breast Cancer Prediction
P.6.10 Kalaitzakis et al Introduction of a software tool for MR thermometry utilizing fast T2 relaxometry techniques in mild hyperthermia temperature ranges for three hydatic solution samples
P.6.11 Tzika et al Segmentation and Analysis of Clinical Dermatological Images
P.6.12 Dimitriou et al PET radiomics for differentiation between adenocarcinoma and squamous cell carcinoma in Non-Small-Cell Lung Cancer (NSCLC): A pilot study
P.6.13 Bara et al Assessing the contribution of machine learning texture analysis of muscle ultrasound imaging in distinguishing neurogenic from myopathic disease: a pilot study
P.6.14 Livanos et al Deep learning approach of skin lesion classification from dermoscopy and clinical images along with patient clinical data
P.6.15 Sharma et al Deep learning in upscaling low quality MR images: A comparison study of three UNet architectures with and without priors employment
P.6.16 Velazco-Garcia et al A multiuser teleradiology paradigm that merges on-the-fly remote control of the MRI scanner and immersive data visualization with multi-platform holographic augmented reality interfaces