DIAGNijmegen/StreamingCNN

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DIAGNijmegen/StreamingCNN

DIAGNijmegen

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To train deep convolutional neural networks, the input data and the activations need to be kept in memory. Given the limited memory available in current GPUs, this limits the maximum dimensions of the input data. Here we demonstrate a method to train convolutional neural networks while holding only parts of the image in memory.

neural-odes-segmentation

Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands

pathology-whole-slide-data

A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

pathology-streaming-pipeline

Use streaming to train whole-slides images with single image-level labels, by reducing GPU memory requirements with 99%.

pathology-he-auto-augment

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

pathology-hooknet

Jupyter Notebook

picai_labels

Annotations for the PI-CAI Challenge: Public Training and Development Dataset

picai_baseline

Baseline AI models for 3D csPCa detection/diagnosis in bpMRI

prostateMR_3D-CAD-csPCa

Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.

HoVer-UNet

pathology-artifact-detection

Quality control of whole-slide images through multi-class semantic segmentation of artifacts

ULS23

Repository for the Universal Lesion Segmentation Challenge '23

picai_prep

Preprocessing 3D medical images and image archives —geared towards prostate cancer detection in MRI.

picai_eval

Evaluation of 3D detection and diagnosis performance —geared towards prostate cancer detection in MRI.

Report-Guided-Annotation

Report Guided Annotation

spgnn

Structure and position aware graph neural network for airway labeling

opencxr

A collection of open-source algorithms for chest X-ray analysis

rse-panimg

Conversion of medical images to MHA and TIFF.

AbdomenMRUS-prostate-segmentation

Grand Challenge wrapper for whole-gland prostate segmentation with nnUNet

SPIDER-Baseline-IIS

panda-challenge

Code related to the PANDA challenge on artificial intelligence for Gleason grading

Jupyter Notebook

pathology-hooknet-tls

Jupyter Notebook

pathology-tiger-algorithm-example

Example algorithm and docker for the TIGER challenge

pathology-tiger-baseline

panorama_labels

drive-vessels-unet

pathology-whole-slide-packer

extracts tissue sections from one or multiple whole slide images and combines them into a single new slide removing excess white space

website-content

This repository stores all the content for the diag websites.

covid19-imaging-ai

An organized collection of data, software, initiatives and papers for COVID-19 imaging AI

pathology-he-autoaugmetation

Comparative analysis of 4 state-of-the-art automatic augmentation algorithms in H&E stained histopathology.

MedicalTransferLearning3D-UNet

This repository contains the model used for the paper ''Transfer learning from a sparsely annotated dataset of 3D medical images'' by G. Humpire, C. Jacobs, M. Prokop, B. van Ginneken, N. Lessmann.

Jupyter Notebook

prostateMR-USSL

Uncertainty Aware Self-Supervised Prostate Zonal Segmentation in 3D MRI scans using Probabilistic Attention U-Net..

picai_nnunet_gc_algorithm

nnUNet model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

picai_nndetection_semi_supervised_gc_algorithm

Semi-supervised nnDetection model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

AbdomenMRUS-csPCa-CAD-nnUNet

Clinically Significant Prostate Cancer Detection in bpMRI using models trained with Report Guided Annotations

pathology-streamingclam

Lightstream implementation of the StreamingCLAM model

PANORAMA_baseline

picai_unet_semi_supervised_gc_algorithm

Semi-supervised UNet model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

bodyct-dsb2017-grt123

Repository which contains the code of the grt123 solution from the Kaggle DSB 2017 challenge on lung cancer detection

picai_unet_gc_algorithm

U-Net model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

picai_nnunet_semi_supervised_gc_algorithm

Semi-supervised nnUNet model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

adhesion_detection

Adhesion detection on cine MRI

Jupyter Notebook

rse-gcapi

Python client for the grand-challenge.org API

flare22-brananas

Codebase of team brananas for the FLARE22 challenge

picai_nndetection_gc_algorithm

nnDetection model for 3D csPCa detection/diagnosis in bpMRI, deployable on grand-challenge.org

ACOUSLIC-AI-baseline

ACOUSLIC-AI-evaluation-method

SPIDER-Evaluation

Evaluation code used for the SPIDER Challenge.

bodyct-luna22-ismi-training-baseline

Baseline repo for LUNA22-ismi challenge

stoic2021-finalphase-submission-hal9000

stoic2021-finalphase-submission-code1055

Jupyter Notebook

bodyct-dram

node21-noduledetection

Template for nodule detection algorithm for node21 challenge

Jupyter Notebook

frodo

library for FRODO

node21

m-heads

rse-pyswot

Python implementation of JetBrains/swot

LEOPARD-challenge-baseline

rse-sagemaker-shim

Adapts algorithms that implement the Grand Challenge inference API for running in SageMaker

CE-CT_PDAC_AutomaticDetection_nnUnet

Fully automtic pipeline for pancreatic ductal adenocarcinoma (PDAC) detection on contrast enhanced computed tomography (CE-CT) scans

auc23-t2-algorithm-container-rib-ct-fracture