KhrystynaFaryna

pathology-he-auto-augment

H&E tailored Randaugment: automatic data augmentation policy selection for H&E-stained histopathology.

data-centric-ai

Resources for Data Centric AI

awesome-gan-for-medical-imaging

Awesome GAN for Medical Imaging

BrainAgeing

This is the project about simulating the ageing brain.

gcapi-examples

GC-API: tutorials and example scripts to help you interact with grand-challenge.org via python.

Harris_3D_corner_detector

Implementation of Harris corner detector in 3D with Qt and GSL

multi-label-annotation-text-reports-body-CT

There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) Computed Tomography (CT). Currently, the major bottleneck for developing multi-disease classifiers is a lack of manually annotated data. The purpose of this work was to develop high throughput multi-label annotators for body CT reports that can be applied across a variety of abnormalities, organs, and disease states thereby mitigating the need for human annotation.

Skin-lesion-classification-web-application-SKINAI

Client side web app for skin lesion classification with deep learning.

ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

KhrystynaFaryna/gcapi-examples

GC-API: tutorials and example scripts to help you interact with grand-challenge.org via python.

KhrystynaFaryna/multi-label-annotation-text-reports-body-CT

There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) Computed Tomography (CT). Currently, the major bottleneck for developing multi-disease classifiers is a lack of manually annotated data. The purpose of this work was to develop high throughput multi-label annotators for body CT reports that can be applied across a variety of abnormalities, organs, and disease states thereby mitigating the need for human annotation.

KhrystynaFaryna/awesome-gan-for-medical-imaging

Awesome GAN for Medical Imaging

KhrystynaFaryna/BrainAgeing

This is the project about simulating the ageing brain.

KhrystynaFaryna/Harris_3D_corner_detector

Implementation of Harris corner detector in 3D with Qt and GSL

KhrystynaFaryna/Skin-lesion-classification-web-application-SKINAI

Client side web app for skin lesion classification with deep learning.

KhrystynaFaryna/BraTs-Segmentation-Challenge

KhrystynaFaryna/data-augmentation-review

List of useful data augmentation resources. You will find here some not common techniques, libraries, links to github repos, papers and others.

KhrystynaFaryna/gc-api-examples

KhrystynaFaryna/IHClymphocytesdetection

KhrystynaFaryna/intensity-normalization

normalize the intensity of several MR image contrasts with various routines

KhrystynaFaryna/khrystynafaryna.github.io

KhrystynaFaryna/medSynthesisV1

This is a copy of package for medical image synthesis work with LRes-ResUnet and GAN (wgan-gp) in pytorch framework

KhrystynaFaryna/neuron

Neural networks toolbox focused on medical image analysis

KhrystynaFaryna/nnUNet

KhrystynaFaryna/nnunet-for-pathology

Tailoring the awesome nnUNet framework into a computational pathology oriented framework.

KhrystynaFaryna/pathology-embedding-stain-invariance

This repository includes code for SPIE 2024 abstract

KhrystynaFaryna/PyTorch-GAN

PyTorch implementations of Generative Adversarial Networks.

KhrystynaFaryna/slide2patch-utils

Utility scripts for converting WSI to latches

KhrystynaFaryna/SocialCoding

KhrystynaFaryna/topojson_world_map

world map for topojson with Crimeea, Hong Kong and Singapore

KhrystynaFaryna/w4U

KhrystynaFaryna/workshops4Ukraine

KhrystynaFaryna/world-atlas-crimea