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Michael Green

pihash

  •  Israel
  •  Sheba Medical Center
  •  Computation Imaging Lab
Statistics
  • Member for 3 years, 1 month
  • 7 challenge submissions

Activity Overview

LUNA16 Logo
LUNA16
Challenge User

The LUNA16 challenge: automatic nodule detection on chest CT

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SLIVER07
Challenge User

The goal of this competition is to compare different algorithms to segment the liver from clinical 3D computed tomography (CT) scans.

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CHAOS
Challenge User

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

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BrainPTM 2021
Challenge User

Brain Pre-surgical Tractography Mapping (BrainPTM) in real clinical scans.

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fastPET-LD
Challenge Editor

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.