Your mugshot

Khrystyna Faryna

KhrystynaFaryna

  •  Netherlands
  •  RadboudUMC
  •  Pathology/DIAG
Organizations
Statistics
  • Member for 3 years, 1 month
  • 3 challenge submissions
  • 733 algorithms run

Activity Overview

coronacases.org Logo
coronacases.org
Archive User

10 CT scans from the website https://coronacases.org/

LUNA16 Logo
LUNA16
Archive User

888 CT scans from the LUNA16 challenge

AI assisted Gleason grading "in the wild" Logo
AI assisted Gleason grading "in the wild"
Reader Study Editor

ICIAR2018-Challenge Logo
ICIAR 2018
Challenge User

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

drive Logo
DRIVE
Challenge User

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

HC18 Logo
HC18
Challenge User

Automated measurement of fetal head circumference using 2D ultrasound images

PAIP2019 Logo
PAIP 2019
Challenge User

PAIP2019: Liver Cancer Segmentation Task 1: Liver Cancer Segmentation Task 2: Viable Tumor Burden Estimation

Gleason2019 Logo
Gleason2019
Challenge User

MICCAI 2019 Automatic Prostate Gleason Grading Challenge: This challenge aims at the automatic Gleason grading of prostate cancer from H&E-stained histopathology images. This task is of critical importance because Gleason score is a strong prognostic predictor. On the other hand, it is very challenging because of the large degree of heterogeneity in the cellular and glandular patterns associated with each Gleason grade, leading to significant inter-observer variability, even among expert pathologists.

DigestPath2019 Logo
DigestPath2019
Challenge User

Welcome to Digestive-System Pathological Detection and Segmentation Challenge 2019. This competition is part of the MICCAI 2019 Challenge.

LYSTO Logo
Lymphocyte Assessment Hackathon
Challenge User

Lymphocyte Assessment Hackathon in conjunction with the MICCAI COMPAY 2019 Workshop on Computational Pathology

PAIP2020 Logo
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.

PAIP2021 Logo
PAIP2021
Challenge User

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

WSSS4LUAD Logo
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.

tiger Logo
TIGER
Challenge User

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

STOIC2021 Logo
STOIC2021 - COVID-19 AI Challenge
Challenge User

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

PI-CAI Logo
The PI-CAI Challenge
Challenge User

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

CoNIC-Challenge Logo
CoNIC 2022
Challenge User

Colon Nuclei Identification and Counting Challenge 2022

instance Logo
INSTANCE2022
Challenge User

The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT)

BCNB Logo
BCNB
Challenge User

Early Breast Cancer Core-Needle Biopsy WSI Dataset

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.

AGGC22 Logo
AGGC22
Challenge User

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

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.

MIDOG2022 Logo
MItosis DOmain Generalization 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

ARCADE Logo
ARCADE-MICCAI2023
Challenge User

TopCoW23 Logo
Topology-Aware Anatomical Segmentation of the Circle of Willis
Challenge User

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

LEOPARD Logo
The LEOPARD Challenge
Challenge Editor

ISLES-24 Logo
Ischemic Stroke Lesion Segmentation Challenge 2024
Challenge User

Gleason Grading of Prostate Biopsies Logo
Gleason Grading of Prostate Biopsies
Algorithm Editor

Automated Gleason grading of prostate biopsies following the Gleason Grade Group system.

Gleason Grading of Prostate Biopsies (non-normalized) Logo
Gleason Grading of Prostate Biopsies (non-normalized)
Algorithm Editor

Automated Gleason grading of prostate biopsies following the Gleason Grade Group system. This version of the algorithm runs without data normalization.

Pulmonary Lobe Segmentation Logo
Pulmonary Lobe Segmentation
Algorithm User

Automatic segmentation of pulmonary lobes on CT scans for patients with COPD or COVID-19.

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.

Nuclear Pleomorphism Scoring Logo
Nuclear Pleomorphism Scoring
Algorithm User

Scoring nuclear pleomorphism grade in whole-slide breast histopathology images

Lymphocytes detection in immunohistochemistry Logo
Lymphocytes detection in immunohistochemistry
Algorithm Editor