Your mugshot

Ludovic Sibille

ludovic

  •  United States of America
  •  Subtle Medical
  •  R&D
Statistics
  • Member for 2 years
  • 7 challenge submissions
  • 11 algorithms run

Activity Overview

ultra-low-dose-PET Logo
Ultra-low Dose PET Imaging Challenge
Challenge User

This challenge aims to develop deep learning algorithms capable of recovering high-quality imaging from low-dose scans on this ultra-low-dose PET scanner.

instance Logo
INSTANCE2022
Challenge User

The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT)

SynthRAD2023 Logo
SynthRAD2023
Challenge User

SynthRAD is the first challenge on automatic generation of synthetic computed tomography (sCT) for radiotherapy

autoPET Logo
autoPET
Challenge User

Automatic lesion segmentation in whole-body FDG-PET/CT

LNQ2023 Logo
LNQ2023
Challenge User

Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and in longitudinal scans, assessing response to therapy. Current standard practice for quantifying lymph node size is based on a variety of criteria that use unidirectional or bidirectional measurements on just one or a few nodes, typically on just one axial slice. But humans have hundreds of lymph nodes, any number of which may be enlarged to various degrees due to disease or immune response. While a normal lymph node may be approximately 5mm in diameter, a diseased lymph node may be several cm in diameter. The mediastinum, the anatomical area between the lungs and around the heart, may contain ten or more lymph nodes, often with three or more enlarged greater than 1cm. Accurate segmentation in 3D would provide more information to evaluate lymph node disease.

ULS23 Logo
Universal Lesion Segmentation Challenge '23
Challenge User