Foto del docente

Filippo Piccinini

Senior assistant professor (fixed-term)

Department of Medical and Surgical Sciences

Academic discipline: FIS/07 Applied Physics


Keywords: Computer Vision Machine Learning Image Processing Microscopy & Imaging 3D Cell Cultures

All my research projects are based on Computer Vision applications at the service of Microscopy to solve open problems in Biology and Medicine.

In particular, together with collaborators and students, we have developed a series of software and tools.

See for instance:

  • Advanced Cell Classifier, for classifying cells in high-content screening images.
  • AnaSP, software suite to segment brightfield images of multicellular spheroids.
  • AND-Tool, Matlab tool for segmenting nuclei in 2D widefield images stained with DAB.
  • CellTracker, for tracking in 2D cells cultured in vitro.
  • CIDRE, for correcting the illumination field of microscopy images.
  • Colour Deconvolution 2, ImageJ/Fiji plugin for stain unmixing in RGB histological images. Prof. Gabriel Landini webpage
  • DS4H Image Alignment, ImageJ/Fiji plugin for aligning images based on markers manually defined.
  • F-Tracker3D, for tracking in 3D fluorescent particles imaged with a confocal/light-sheet microscope.
  • MicroMos, for building a panorama, starting from a set of overlapping images.
  • ReViMS, for cancer spheroids Reconstruction and Visualization using Multiple Sections.
  • ReViSP, for cancer spheroids Reconstruction and Visualization using a Single Projection.
  • 3D-Cell-Annotator, MITK plugin for segmenting single cells in 3D datasets.