no code implementations • 21 Dec 2022 • Jorge F. Lazo, Benoit Rosa, Michele Catellani, Matteo Fontana, Francesco A. Mistretta, Gennaro Musi, Ottavio De Cobelli, Michel de Mathelin, Elena De Momi
We address the challenge of tissue classification when annotations are available only in one domain, in our case WLI, and the endoscopic images correspond to an unpaired dataset, i. e. there is no exact equivalent for every image in both NBI and WLI domains.
no code implementations • 1 Jul 2022 • Jorge F. Lazo, Chun-Feng Lai, Sara Moccia, Benoit Rosa, Michele Catellani, Michel de Mathelin, Giancarlo Ferrigno, Paul Breedveld, Jenny Dankelman, Elena De Momi
Navigation inside luminal organs is an arduous task that requires non-intuitive coordination between the movement of the operator's hand and the information obtained from the endoscopic video.
no code implementations • 8 Apr 2021 • Jorge F. Lazo, Sara Moccia, Aldo Marzullo, Michele Catellani, Ottavio De Cobelli, Benoit Rosa, Michel de Mathelin, Elena De Momi
In this work we study the implementation of 3 different Convolutional Neural Networks (CNNs), using a 2-steps training strategy, to classify images from the urinary tract with and without lesions.
no code implementations • 5 Apr 2021 • Jorge F. Lazo, Aldo Marzullo, Sara Moccia, Michele Catellani, Benoit Rosa, Michel de Mathelin, Elena De Momi
Of these, two architectures are taken as core-models, namely U-Net based in residual blocks($m_1$) and Mask-RCNN($m_2$), which are fed with single still-frames $I(t)$.
no code implementations • 13 Jan 2021 • Jorge F. Lazo, Aldo Marzullo, Sara Moccia, Michele Catellani, Benoit Rosa, Michel de Mathelin, Elena De Momi
For the training of these networks, we analyze the use of two different color spaces: gray-scale and RGB data images.