Publicacións en colaboración con investigadores/as de Masaryk University (15)

2023

  1. The Cell Tracking Challenge: 10 years of objective benchmarking

    Nature Methods, Vol. 20, Núm. 7, pp. 1010-1020

2019

  1. 3-D quantification of filopodia in motile cancer cells

    IEEE Transactions on Medical Imaging, Vol. 38, Núm. 3, pp. 862-872

2018

  1. Segmentation of actin-stained 3D fluorescent cells with filopodial protrusions using convolutional neural networks

    Proceedings - International Symposium on Biomedical Imaging

2017

  1. An objective comparison of cell-tracking algorithms

    Nature Methods, Vol. 14, Núm. 12, pp. 1141-1152

  2. Characterization of three-dimensional cancer cell migration in mixed collagen-Matrigel scaffolds using microfluidics and image analysis

    PLoS ONE, Vol. 12, Núm. 2

2015

  1. Cell tracking accuracy measurement based on comparison of acyclic oriented graphs

    PLoS ONE, Vol. 10, Núm. 12

  2. Characterization of the role of collagen network structure and composition in cancer cell migration

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

  3. Quantification of the 3D collagen network geometry in confocal reflection microscopy

    Proceedings - International Conference on Image Processing, ICIP

  4. Toward a morphodynamic model of the cell: Signal processing for cell modeling

    IEEE Signal Processing Magazine, Vol. 32, Núm. 1, pp. 20-29

2014

  1. A benchmark for comparison of cell tracking algorithms

    Bioinformatics, Vol. 30, Núm. 11, pp. 1609-1617

  2. Objective comparison of particle tracking methods

    Nature Methods, Vol. 11, Núm. 3, pp. 281-289

2013

  1. Automatic quantification of filopodia-based cell migration

    Proceedings - International Symposium on Biomedical Imaging

  2. Segmentation and shape tracking of whole fluorescent cells based on the Chan-Vese model

    IEEE Transactions on Medical Imaging, Vol. 32, Núm. 6, pp. 995-1006

2009

  1. A two-phase segmentation of cell nuclei using fast level set-like algorithms

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Segmentation of touching cell nuclei using a two-stage graph cut model

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)