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Learning Algorithms for Medical Big Data Analysis

The big data analytics group is concerned with combining multi-modal imaging and clinical data for improved clinical decision making. Current topics of interest include identification of malignant tumour sub-types in breast cancer, establishing correlations between image-based features, gene expression and disease progression in patients, and developing innovative therapeutic approaches such as immune cell guidance and response activation.  

Colloquium Time Table

DateResponsible PersonTitle
10.7.2017 Tobias PertlwieserIntro Talk: Generative Adversarial Models for Outlier Detection
17.7.2017Dalia Rodrigues SalasMapping decision trees to 
24.7.2017-No Colloquium due to PRS
31.7.2017Stefan Freitag
Final Talk: Improving the Absolute Accuracy of a Robotic C-Arm System  with Machine Learning Techniques
Overview: Co-registration of breast lesions in CT and MRI

Jonas Denck

Katrin Mentl

Final Talk: Automatic Billing Code Retrieval from MR-Log Data

Overview: Stroke Detection on NCCT


Markus Schmidt

Rimon Saffoury

Final Talk:Deep Learning Based, tissue specific, gene expression labeling using merely Nucleotide Sequences

Intro Talk: Automatic Malignancy Estimation for Pulmonary Nodules from CT Images

21.8.2017Sebastian GundelTBD


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Running Projects

Breast Tumor Lesions Segmentation

Segmenting and classifying the tumor lesions in breast through Dynamic Contrast-Enhanced MR Images

Medical Image Understanding

Advancing the State-of-the-Art through Integration of Medical Knowledge