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David Ellis

UNeImage

  •  United States of America
  •  University of Nebraska Medical Center
  •  Neurosurgery
Statistics
  • Member for 6 years, 8 months
  • 27 challenge submissions
  • 16 algorithms run

Activity Overview

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CuRIOUS 2018
Challenge User

MICCAI Challenge 2018 for Correction of Brainshift with Intra-Operative Ultrasound

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The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

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TDSC-ABUS2023
Challenge User

Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound

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SynthRAD2023
Challenge User

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

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Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022
Challenge User

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The Head and Neck Organ-at-Risk CT & MR Segmentation Challenge
Challenge User

A semantic multimodal segmentation challenge comprising 30 organs at risk

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ToothFairy: Cone-Beam Computed Tomography Segmentation Challenge
Challenge User

This is the first edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Raudboud University. This challenge aims at pushing the development of deep learning frameworks to segment the Inferior Alveolar Canal (IAC) by incrementally extending the amount of publicly available 3D-annotated Cone Beam Computed Tomography (CBCT) scans. CBCT modality is becoming increasingly important for treatment planning and diagnosis in implant dentistry and maxillofacial surgery. The three-dimensional information acquired with CBCT can be crucial to plan a vast number of surgical interventions with the aim of preserving noble anatomical structures such as the Inferior Alveolar Canal (IAC), which contains the homonymous nerve (Inferior Alveolar Nerve, IAN). Deep learning models can support medical personnel in surgical planning procedures by providing a voxel-level segmentation of the IAN automatically extracted from CBCT scans.

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Ultrasound Image Enhancement challenge 2023
Challenge User

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SEG.A. - Segmentation of the Aorta
Challenge User

Segmentation, modeling and visualization of the arterial tree are still a challenge in medical image analysis. The main track of this challenge deals with the fully automatic segmentation of the aortic vessel tree in computed tomography images. Optionally, teams can submit tailored solutions for meshing and visualization of the vessel tree.

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Surgical Planning in Pediatric Neuroblastoma
Challenge User

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Topology-Aware Anatomical Segmentation of the Circle of Willis
Challenge User

Segment the Circle of Willis (CoW) vessel components for both CTA and MRA

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SegRap 2023
Challenge User

A segmentation challenge with 200 patients (two modalities of CT images, 45 OARs and 2 GTVs).

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Hypoxic Ischemic Encephalopathy Lesion Segmentation Challenge
Challenge User

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Ischemic Stroke Lesion Segmentation Challenge 2024
Challenge User

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Automated Identification of Mod-Sev TBI Lesions
Challenge User

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TopCoW 2024 Challenge
Challenge User

Segment, classify, and detect the Circle of Willis (CoW) for both CTA and MRA