We are glad to announce that the partnership between Ivision and the Pathospotter project resulted in another published paper! The work is entitled “Computational pathology, new horizons and challenges for anatomical pathology” and was published in the Surgical and Experimental Pathology journal. The study reviews the advances in the Computational Pathology field, pointing to challenges and new prospects.

We are glad to announce that the partnership between Ivision and the Pathospotter project resulted in another published paper! The work is entitled “Computational pathology, new horizons and challenges for anatomical pathology” and was published in the Surgical and Experimental Pathology journal. The study reviews the advances in the Computational Pathology field, pointing to challenges and new prospects.

We are pleased to announce that our group not only had a paper accepted in the 22nd Brazilian Symposium on Computing Applied to Health, but was also invited to a special issue of the Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. The work is entitled “How feasible is it to segment human glomerulus with a model trained on mouse histology images?” and investigates knowledge transfer between mice and humans glomeruli images. The study is result of a fruitful partnership of Ivision along with the Pathospotter project.

We are pleased to announce that our group had a paper accept in the Computerized Medical Imaging and Graphics. The work is entitled “Boundary-aware glomerulus segmentation: Toward one-to-many stain generalization” and proposes a novel convolutional neural network for glomerulus segmentation: the DS-FNet. The work is part of Ivision’s research along with the Pathospotter project.

We want to congratulate now Doctor Jefferson Fontinele for finishing his Ph.D. Doctor Fontinele researched semantic segmentation deep learning methods on traffic and biomedical images. Two works from our lab (“Faster α-expansion via dynamic programming and image partitioning” and “Attention-based fusion of semantic boundary and non-boundary information to improve semantic segmentation”) are direct outcomes of his thesis entitled “Paying attention to the boundaries in semantic image segmentation,” confirming its success in the field of semantic segmentation. Well done, Doctor Jefferson Fontinele!