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Scientific Background

Here we provide a list of the most useful papers to read before starting the WebValley 2018 School.

# Year Authors Title Link
1 1995 David A Lisle Introduction to Medical Imaging Download
2 2017 Mohme M and Maire C and Riecken K et al. Optical Barcoding for Single-Clone Tracking to Study Tumor Heterogeneity Download
3 2017 H.K. van der Burgh et al. Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis Download
4 2017 Mohan et al. MRI based medical image analysis: Survey on brain tumor grade classification Download
5 2017 Vallières et al. Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer Download
6 2017 Miotto, R and Wang, F et al. Deep learning for healthcare: review, opportunities and challenges Download
7 2017 Litjens et al. A Survey on Deep Learning in Medical Image Analysis Download
8 2017 Mobadersany et al. Predicting cancer outcomes from histology and genomics using convolutional networks Download
9 2017 Ciompi F. et al. Towards automatic pulmonary nodule management in lung cancer screening with deep learning Download
10 2017 Garcia et al. A Review on Deep Learning Techniques Applied to Semantic Segmentation Download
11 2017 Liao et al. Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network Download
12 2018 Zhou et al. Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches Download