February 2020

4 total

15FEB 2020
Datasets
Large-scale pathology dataset for mitotic figure detection
We released a large-scale data set for mitotic figure detection as open data. Unlike previous data sets, it is the only data set that provides a complete annotation map for the histology whole slide image. It includes 44880 mitotic figures, verified in blind review by two expert pathologists. We were able to show that the […]
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06FEB 2020
News
BMBF to fund joint project on MR Imaging and Deep Learning in Cooperation with University of Würzburg
We are proud to announce the funding of “Intelligent MR Diagnosis of the Liver by Linking Model and Data-driven Processes (iDELIVER)“ by BMBF. The project examines the use and further development of machine learning methods for MR image reconstruction and for the classification of liver lesions. Based on a comparison model and data-driven image reconstruction […]
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06FEB 2020
News
Pattern Recognition for Material Characterisation 2.0
We just received news that we are able to continue our project on material characterisation using machine learning for another two years. DFG will fund the use of deep learning procedures to determine the forming limits of metal sheets with approximately 150,000 EUR. The project is conducted in cooperation with FAU’s Lab for Manufacturing Technologies […]
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03FEB 2020
Ph.D. Gallery
Yixing Huang
Consistency Conditions, Compressed Sensing and Machine Learning for Limited Angle Tomography Cone-beam computed tomography (CBCT) is a widely used imaging technology for medical diagnosis and interventions nowadays. Compared with conventional 2-D X-ray images, 3-D volumes reconstructed by CBCT provide cross sectional images and offer much better visualization of patients’ anatomical structures and disease information. In […]Consistency Conditions, Compressed Sensing and Machine Learning for Limited Angle Tomography Cone-beam computed tomography (CBCT) is a widely used imaging technology for medical diagnosis and interventions nowadays. Compared with conventional 2-D X-ray images, 3-D volumes reconstructed by CBCT provide cross sectional images and offer much better visualization of patients’ anatomical structures and disease information. In […]
Read more about Yixing Huang