VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data

Overview

VISNOTATE: An Opensource tool for Gaze-based Annotation of WSI Data

Introduction

This repo contains the source code for 'Visnotate' which is a tool that can be used to track gaze patterns on Whole Slide Images (WSI) in the svs format. Visnotate was used to evaluate the efficacy of gaze-based labeling of histopathology data. The details of our research on gaze-based annotation can be found in the following paper:

  • Komal Mariam, Osama Mohammed Afzal, Wajahat Hussain, Muhammad Umar Javed, Amber Kiyani, Nasir Rajpoot, Syed Ali Khurram and Hassan Aqeel Khan, "On Smart Gaze based Annotation of Histopathology Images for Training of Deep Convolutional Neural Networks", submitted to IEEE Journal of Biomedical and Health Informatics.

blockDiagram

Requirements

  • Openslide
  • Python 3.7

Installation and Setup

  1. Install openslide. This process is different depending on the operating system.

    Windows

    1. Download 64-bit Windows Binaries from the openslide download page. Direct link to download the latest version at the time of writing.
    2. Extract the zip archive.
    3. Copy all .dll files from bin to C:/Windows/System32.

    Debian/Ubuntu

    # apt-get install openslide-tools

    Arch Linux

    $ git clone https://aur.archlinux.org/openslide.git
    $ cd openslide
    $ makepkg -si

    macOS

    $ brew install openslide
  2. For some operating systems, tkinter needs to be installed as well.

    Debian/Ubuntu

    # apt-get install python3-tk

    Arch Linux

    # pacman -S tk
  3. (Optional) If recording gaze points using a tracker, install the necessary software from its website.

  4. Clone this repository.

    git clone https://github.com/UmarJ/lsiv-python3.git visnotate
    cd visnotate
    
  5. Create and activate a new python virtual environment if needed. Then install required python modules.

    python -m pip install -r requirements.txt
    
  6. (Optional) Start gaze tracking software in the background if tracking gaze points.

  7. Run interface_recorder.py.

    python interface_recorder.py
    

Supported Hardware and Software

At this time visinotate supports the GazePoint GP3, tracking hardware. WSI's are read using openslide software and we support only the .svs file format. We do have plans to add support for other gaze tracking hardware and image formats later.

Screenshots

The Visnotate Interface

Interface Screenshot

Collected Gazepoints

Gazepoints Screenshot

Generated Heatmap

Heatmap Screenshot

Reference

This repo was used to generate the results for the following paper on Gaze-based labelling of Pathology data.

  • Komal Mariam, Osama Mohammed Afzal, Wajahat Hussain, Muhammad Umar Javed, Amber Kiyani, Nasir Rajpoot, Syed Ali Khurram and Hassan Aqeel Khan, "On Smart Gaze based Annotation of Histopathology Images for Training of Deep Convolutional Neural Networks", submitted to IEEE Journal of Biomedical and Health Informatics.

BibTex Reference: Available after acceptance.

Owner
SigmaLab
This github account belongs to the Sigma Lab. Which is Dr. Hassan Aqeel Khan's research group.
SigmaLab
Experiments on continual learning from a stream of pretrained models.

Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them

Antonio Carta 6 Dec 04, 2022
Perturb-and-max-product: Sampling and learning in discrete energy-based models

Perturb-and-max-product: Sampling and learning in discrete energy-based models This repo contains code for reproducing the results in the paper Pertur

Vicarious 2 Mar 14, 2022
Large scale PTM - PPI relation extraction

Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT The silver standard

1 Feb 25, 2022
Cognate Detection Repository

Cognate Detection Repository Details This repository contains the data for two publications: Challenge Dataset of Cognates and False Friend Pairs from

Diptesh Kanojia 1 Apr 26, 2022
This code is the implementation of the paper "Coherence-Based Distributed Document Representation Learning for Scientific Documents".

Introduction This code is the implementation of the paper "Coherence-Based Distributed Document Representation Learning for Scientific Documents". If

tsc 0 Jan 11, 2022
Learning Synthetic Environments and Reward Networks for Reinforcement Learning

Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (

AutoML-Freiburg-Hannover 16 Sep 02, 2022
Object tracking and object detection is applied to track golf puts in real time and display stats/games.

Putting_Game Object tracking and object detection is applied to track golf puts in real time and display stats/games. Works best with the Perfect Prac

Max 1 Dec 29, 2021
Converts geometry node attributes to built-in attributes

Attribute Converter Simplifies converting attributes created by geometry nodes to built-in attributes like UVs or vertex colors, as a single click ope

Ivan Notaros 12 Dec 22, 2022
The project is an official implementation of our paper "3D Human Pose Estimation with Spatial and Temporal Transformers".

3D Human Pose Estimation with Spatial and Temporal Transformers This repo is the official implementation for 3D Human Pose Estimation with Spatial and

Ce Zheng 363 Dec 28, 2022
GEP (GDB Enhanced Prompt) - a GDB plug-in for GDB command prompt with fzf history search, fish-like autosuggestions, auto-completion with floating window, partial string matching in history, and more!

GEP (GDB Enhanced Prompt) GEP (GDB Enhanced Prompt) is a GDB plug-in which make your GDB command prompt more convenient and flexibility. Why I need th

Alan Li 23 Dec 21, 2022
Repository for training material for the 2022 SDSC HPC/CI User Training Course

hpc-training-2022 Repository for training material for the 2022 SDSC HPC/CI Training Series HPC/CI Training Series home https://www.sdsc.edu/event_ite

sdsc-hpc-training-org 21 Jul 27, 2022
Official implementation of "Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets" (CVPR2021)

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets This is the official implementation of "Towards Good Pract

Sanja Fidler's Lab 52 Nov 22, 2022
👨‍đŸ’ģ run nanosaur in simulation with Gazebo/Ingnition

đŸĻ• 👨‍đŸ’ģ nanosaur_gazebo nanosaur The smallest NVIDIA Jetson dinosaur robot, open-source, fully 3D printable, based on ROS2 & Isaac ROS. Designed & ma

nanosaur 9 Jul 19, 2022
Semantic Edge Detection with Diverse Deep Supervision

Semantic Edge Detection with Diverse Deep Supervision This repository contains the code for our IJCV paper: "Semantic Edge Detection with Diverse Deep

Yun Liu 12 Dec 31, 2022
Bulk2Space is a spatial deconvolution method based on deep learning frameworks

Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on

Dr. FAN, Xiaohui 60 Dec 27, 2022
An efficient and easy-to-use deep learning model compression framework

TinyNeuralNetwork įŽ€äŊ“中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura

Alibaba 441 Dec 25, 2022
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

D-X-Y 137 Dec 20, 2022
Freecodecamp Scientific Computing with Python Certification; Solution for Challenge 2: Time Calculator

Assignment Write a function named add_time that takes in two required parameters and one optional parameter: a start time in the 12-hour clock format

Hellen Namulinda 0 Feb 26, 2022
A Kernel fuzzer focusing on race bugs

Razzer: Finding kernel race bugs through fuzzing Environment setup $ source scripts/envsetup.sh scripts/envsetup.sh sets up necessary environment var

Systems and Software Security Lab at Seoul National University (SNU) 328 Dec 26, 2022
Leaf: Multiple-Choice Question Generation

Leaf: Multiple-Choice Question Generation Easy to use and understand multiple-choice question generation algorithm using T5 Transformers. The applicat

Kristiyan Vachev 62 Dec 20, 2022