Your mugshot

Paul Onium

paul.blancdurand

  •  France
  •  APHP
  •  NucMed
Statistics
  • Member for 6 years, 1 month
  • 2 challenge submissions
  • 10 algorithms run

Activity Overview

EMPIRE10 Logo
EMPIRE10
Challenge User

Challenge for intra-subject registration of chest CT images.

CHAOS Logo
CHAOS
Challenge User

In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.

curious2019 Logo
curious2019
Challenge User

MICCAI Challenge 2019 for Correction of Brainshift with Intra-Operative Ultrasound. Taks 1: Register pre-operative MRI to iUS before tumor resection;Taks 2: Register iUS after tumor resection to iUS before tumor resection

fastPET-LD Logo
fastPET-LD
Challenge User

The purpose of this challenge is the detection of “hot spots” in fast PET scan, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by a nuclear medicine expert. It consists of a 3-D segmentation map of the hot spots as well as a text file containing the position and size of 3D cuboid bounding box for each hot spot.

autoPET Logo
autoPET
Challenge User

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

autoPET-II Logo
autoPET-II
Challenge User

Automated Lesion Segmentation in PET/CT - Domain Generalization

ULS23 Logo
Universal Lesion Segmentation Challenge '23
Challenge User

AutoPET-III Logo
AutoPET III
Challenge User