The AI.DReAM project, funded by BPI France, brings together a consortium of 9 partners (GE Healthcare, 4 SMEs and start-ups, 3 clinical partners, and LITO as the only academic laboratory). The project aims to accelerate the development and market access of Artificial Intelligence applications in medical imaging. The role of our laboratory is to carry out the necessary methodological developments to ensure the quality control, the robustness of the radiomic models (classical or deep) and their ability to produce reliable results on a wide variety of images. To evaluate our approaches, we will work with the clinical partners of the consortium, which are the AP-HP, Gustave Roussy, and the Hôpital Saint Joseph in Paris.

People involved in the lab : Nicolas Captier, Fanny Orlhac, Irène Buvat (PI for the lab).

The primary objective of the BIOMEDE-IA project (2020-2023) is to predict by machine learning methods the main genomic mutations of patients with diffuse intrinsic pontine gliomas from their clinical and imaging (multi-parametric MRI) features, to manage the cases for which biopsy is not available.

The TIPIT project (2020-2023), who involves U900 Inserm - Institut Curie - PSL (Head : Emmanuel Barillot), the Department of thoracic oncology of Institut Curie (Head : Nicolas Girard) and our lab is funded by the ARC fondation, as part of the SIGNIT call,  for 3 years.

The aim of the PANACEE project (2020-2023) is to develop methods and a tool that will make it possible, for a patient with non small cell lung cancer described by his or her clinical, biological, histological or medical images characteristics (radiomics), to identify a small group of patients with very similar characteristics, in a reference database consisting of patients already treated for the same pathology.

Positron Emission Tomography is well-established in the diagnosis and treatment monitoring of Hodgkin‘s lymphoma (HL).  HL is a type of tumour that can be characterized by its sugar consumption. Thus, PET enables early monitoring of treatment response, that is shows if the lymphoma shrinks or grows, reflecting whether the therapy is working or not working . So far, only very basic information of the acquired PET images is used. Since the biology of HL is linked to its metabolism, we aim to analyze PET images in more detail by using artificial intelligence algorithms.

The PRECISION PREDICT project (2020-2022) is led by Institut Curie (Thoracic Oncology Department, Data Department, and LITO) and funded as part of the Health Data Hub call related to the "Improvement of medical diagnosis through the use of Artificial Intelligence". 

VOCALE is a project (2018-2022) dedicated to motion analysis of vocal folds using dynamic translaryngeal ultrasound. It is driven by the laboratory in collaboration with surgical departments and the "Laboratoire d’Imagerie Biomédicale".

We are part of the H2020-MSCA-ITN-2017 HYBRID (Healthcare Yearns for Bright Researchers for Imaging Data, 2017-2021) project in collaboration with 10 partners from Germany, Austria, United Kingdom, the Netherlands, Danemark, and Belgium.

Photo Dynamic Therapy (PDT) is a localized treatment using a laser beam focused on the tumor. The PDT is based on the activation by specific wavelength light of a photosensitizer (PS) localized preferentially in tumor cells.

LIFEx is a user-friendly image processing software, making it possible for colleagues without any programming skills to perform radiomic studies using any type of medical images, including PET, MR, CT, SPECT or US images.