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Thilo Sentker

TS_UKE

  •  Germany
  •  University Medical Center Hamburg-Eppendorf
  •  Department of Computational Neuroscience
Statistics
  • Member for 4 years, 8 months
  • 26 challenge submissions
  • 17 algorithms run

Activity Overview

LOLA11 Logo
LOLA11
Challenge User

The goal of LOLA11 (LObe and Lung Analysis 2011) is to compare methods for (semi-)automatic segmentation of the lungs and lobes from chest computed tomography scans. Any team, whether from academia or industry, can join.

StructSeg2019 Logo
StructSeg2019
Challenge User

Welcome to Automatic Structure Segmentation for Radiotherapy Planning Challenge 2019. This competition is part of the MICCAI 2019 Challenge.

Learn2Reg Logo
Learn2Reg
Challenge User

Challenge on medical image registration addressing: learning from small datasets; estimating large deformations; dealing with multi-modal scans; and learning from noisy annotations

VALDO Logo
Where is VALDO?
Challenge User

Vascular Lesion Detection Challenge at MICCAI 2021

feta Logo
FeTA - Fetal Tissue Annotation Challenge
Challenge User

Fetal Tissue Annotation Challenge

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.

MELA Logo
MELA2022
Challenge User

MICCAI 2022 MELA Challenge: A Large-Scale Detection Benchmark of 1,100 CT Scans for Mediastinal Lesion Analysis

DFUC2022 Logo
DFUC 2022
Challenge User

Diabetes is a global epidemic affecting around 425 million people and expected to rise to 629 million by 2045. Diabetic Foot Ulcer (DFU) is a severe condition that can result from the disease. The rise of the condition over the last decades is a challenge for healthcare systems. Cases of DFU usually lead to severe conditions that greatly prolongs treatment and result in limb amputation or death. Recent research focuses on creating detection algorithms to monitor their condition to improve patient care and reduce strain on healthcare systems. Work between Manchester Metropolitan University, Lancashire Teaching Hospitals and Manchester University NHS Foundation Trust has created an international repository of up to 11,000 DFU images. Analysis of ulcer regions is a key for DFU management. Delineation of ulcers is time-consuming. With effort from the lead scientists of the UK, US, India and New Zealand, this challenge promotes novel work in DFU segmentation and promote interdisciplinary researcher collaboration.

3DTeethSeg Logo
3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022
Challenge User

Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.

FLARE22 Logo
MICCAI FLARE 2022
Challenge User

MICCAI 2022 Fast and Low-resource semi-supervised Abdominal oRgan sEgmentation (FLARE) Challenge

ACROBAT Logo
ACROBAT 2023
Challenge User

The ACROBAT challenge aims to advance the development of WSI registration algorithms that can align WSIs of IHC-stained breast cancer tissue sections to corresponding tissue regions that were stained with H&E. All WSIs originate from routine diagnostic workflows.

AMOS22 Logo
Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022
Challenge User

SurgToolLoc Logo
Surgical Tool Localization in endoscopic videos
Challenge User

vessel-wall-segmentation-2022 Logo
Carotid Vessel Wall Segmentation and Atherosclerosis Diagnosis
Challenge User

crossmoda2022 Logo
Cross-Modality Domain Adaptation: Segmentation & Classification
Challenge User

The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

isles22 Logo
Ischemic Stroke Lesion Segmentation Challenge
Challenge User

Deep-Learning-Based CT Lung Registration Logo
Deep-Learning-Based CT Lung Registration
Algorithm User

Registration of inspiration and expiration lung CT scans using a neural network trained with multiple anatomical constraints.