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Philipp Marquardt

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  •  Germany
  •  Karlsruhe Institute of Technology
  •  Student
Statistics
  • Member for 2 years, 9 months
  • 18 challenge submissions

Activity Overview

ANHIR Logo
ANHIR
Challenge User

The challenge focuses on comparing the accuracy (using manually annotated landmarks) and the approximate speed of automatic non-linear registration methods for aligning microscopy images of multi-stained histology tissue samples.

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TIGER
Challenge User

Grand challenge on automate assessment of tumor infiltrating lymphocytes in digital pathology slides of triple negative and Her2-positive breast cancers

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CoNIC 2022
Challenge User

Colon Nuclei Identification and Counting Challenge 2022

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BCNB
Challenge User

Early Breast Cancer Core-Needle Biopsy WSI Dataset

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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.

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

NeurIPS22-CellSeg Logo
Cell Segmentation in Multi-modality Microscopy Images
Challenge User

Weakly Supervised Cell Segmentation in Multi-modality High-resolution Microscopy Images

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PAIP 2023: TC prediction in pancreatic and colon cancer
Challenge User

Tumor cellularity prediction in pancreatic cancer (supervised learning) and colon cancer (transfer learning)

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Foundation Model Prompting for Medical Image Classification
Challenge User

The primary objective of this challenge is to promote the development and evaluation of model adaptation techniques for medical image classification to leverage the existing foundation models.

lightmycells Logo
Light My Cells : Bright Field to Fluorescence Imaging Challenge
Challenge User

Join the Light My Cells France-Bioimaging challenge! Enhance biology and microscopy by contributing to the development of new image-to-image deep labelling methods. The task: predict the best-focused output images of several fluorescently labelled organelles from label-free transmitted light input images. Dive into the future of imaging with us! 🌐🔬 #LightMyCellsChallenge

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AutoPET III
Challenge User