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Dominik Müller

dmueller

  •  Germany
  •  University Augsburg
  •  IT-Infrastructure for Translational Medicial Research
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  • Member for 5 years
  • 54 challenge submissions

Activity Overview

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DRIVE
Challenge User

Develop a system to automatically segment vessels in human retina fundus images.

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KiTS19
Challenge User

2019 Kidney and Kidney Tumor Segmentation Challenge

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VerSe`19
Challenge User

Vertebrae labelling and segmentation on a spine dataset on an unprecedented 150 CT scans with voxel-level vertebral annotations.

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iChallenge-AMD
Challenge User

Age-related Macular Degeneration Challenge

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ODIR-2019
Challenge User

北京大学国际眼底图像智能识别竞赛 Peking University International Competition on Ocular Disease Intelligent Recognition

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PAIP2020
Challenge User

Built on the success of its predecessor, PAIP2020 is the second challenge organized by the Pathology AI Platform (PAIP) and the Seoul National University Hospital (SNUH). PAIP2020 will proceed to not only detect whole tumor areas in colorectal cancers but also to classify their molecular subtypes, which will lead to characterization of their heterogeneity with respect to prognoses and therapeutic responses. All participants should predict one of the molecular carcinogenesis pathways, i.e., microsatellite instability(MSI) in colorectal cancer, by performing digital image analysis without clinical tests. This task has a high clinical relevance as the currently used procedure requires an extensive microscopic assessment by pathologists. Therefore, those automated algorithms would reduce the workload of pathologists as a diagnostic assistance.

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RibFrac
Challenge User

Rib Fracture Detection and Classification Challenge: A large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80Gb)

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RIADD (ISBI-2021)
Challenge User

Retinal Image Analysis for multi-Disease Detection

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MitoEM
Challenge User

Large-scale 3D mitochondria instance segmentation benchmark

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COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020
Challenge User

This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.

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Cross-Modality Domain Adaptation Image Segmentation - 2021
Challenge User

The CrossMoDA challenge 2021 introduces the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.

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BrainPTM 2021
Challenge User

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

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PAIP2021
Challenge User

PAIP 2021 Challenge; Perineural invasion in multiple organ cancer (colon, prostate and pancreatobiliary tract)

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NuCLS
Challenge User

Classification, Localization and Segmentation of nuclei in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad et al. 2021. arXiv:2102.09099 [cs.CV].

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Breast Cancer Segmentation
Challenge User

Semantic segmentation of histologic regions in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083

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WSSS4LUAD
Challenge User

The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.

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STOIC2021 - COVID-19 AI Challenge
Challenge User

COVID-19 Artificial Intelligence Challenge: automated diagnosis, and prognostic evaluation based on computed tomography

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The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

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AGGC22
Challenge User

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

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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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Balaitous
Algorithm User

A deep learning model to estimate COVID disease and severity from a CT scan