- Grand Challenge

Philippe Weitz

phiewe

Sweden
Karolinska Institutet
Department of Medical Epidemiology and Biostatistics

Statistics

Member for 6 years, 6 months
3 challenge submissions

Activity Overview

LUNA16

Challenge User

The LUNA16 challenge: automatic nodule detection on chest CT

ICIAR 2018

Challenge User

Can you develop a method for automatic detection of cancerous regions in breast cancer histology images?

BreastPathQ: Cancer Cellularity Challenge 2019

Challenge User

SPIE-AAPM-NCI BreastPathQ:Cancer Circularity Challenge 2019: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity for tumor burden assessment in each.

PatchCamelyon

Challenge User

PatchCamelyon is a new and challenging image classification dataset of 327.680 color images (96 x 96px) extracted from histopathology images of the CAMELYON16 challenge. The goal is to detect breast cancer metastasis in lymph nodes.

HEROHE

Challenge User

Unlike previous challenges, this proposes to find an image analysis algorithm to identify HER2-positive from HER2-negative breast cancer specimens evaluating only the morphological features present on the HE slide, without the staining patterns of IHC.

PAIP2021

Challenge User

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

TIGER

Challenge User

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

BCNB

Challenge User

Early Breast Cancer Core-Needle Biopsy WSI Dataset

ACROBAT 2023

Challenge Editor

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.

Breast Cancer Immunohistochemical Image Generation Challenge

Challenge User

The Breast Cancer Immunohistochemical Image Generation Challenge aims to directly generate IHC-stained breast cancer histopathology images from HE-stained images.