NEWS

Our collaborative paper "FFPE++: Improving the quality of formalin-fixed paraffin-embedded tissue imaging via contrastive unpaired image-to-image translation." is published at Elsevier Medical Image Analysis!
Our collaborative paper 'A deep-learning model for transforming the style of tissue images from cryosectioned to formalin-fixed and paraffin-embedded' is published on Nature Biomedical Engineering
Congratulations to DeepMIA lab! Our collaborative paper ''Deep learning based robust positioning for all weather autonomous driving'' is published on Nature Machine Intelligence!
Our Digital Pathology Application and Research Center – DPAUAM Project has been found eligible to be supported within the scope of Istanbul Development Agency Innovative Istanbul Financial Support Program.
"Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies" paper is Online!!
"SelfVIO: Self-supervised deep monocular Visual–Inertial Odometry and depth estimation" Paper is Online!!
Dec'01: Congratulations to DeepMIA ! Our collaborative paper with Harvard Medical school entitled ''International Evaluation of an AI System for Endomyocardial Biopsy Assessment'' is accepted to be published at Nature Medicine (Impact Factor: 53.44) !
Aug'21: Our collaborative TUBITAK-1501 project with ViraSoft on artificial intelligence based assessment of gastric histology images is accepted !
Jul'21: New pre-print: Deep Learning-based Frozen Section to FFPE Translation
Jun’21: EndoSLAM Dataset is now published at Mendeley!

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