Research output per year
Research output per year
Campus de Campolide
1070-312 Lisboa
Portugal
Research activity per year
Working with tumor classification and segmentation
-Developed framework that is used for multifile classification with a lot of parameters (data balancing ratio, data balancer, feature seletor, heatmap parameters, classification methods selection)
**Framework is tested and was used to write article (accepted) for CIBB conference in 2019. Then used to write extended version of the paper.
**It was also used to write another paper for breast cancer (for medical journal, waiting for journal response)
-Working on computer vision tasks
--3D volume segmentation in medicine
---Developing new models based on existing ones as well as creating new models, because 3D volume segmentation is not that popular as 2D
---Segmentation of volumes based on 2D models with further processing by 3D model for better segmentation results
-Image classification (prostate, breast, biopsy) to reduce burden of doctors
--Applying straight transfer learning to existing data
--Developing new models based on TL. E.g. developed new fused model where we have two parallel path that merge later. This increased convergence speed as well as final accuracy scores.
Research output: Contribution to journal › Article › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review