pr4deepr Goto Github PK

followers: 47.0 following: 172.0 repos: 66.0 gists: 0.0

Name: Pradeep Rajasekhar

Type: User

Company: Walter and Eliza Hall Institute of Medical Research

Bio: Bioimage Analyst with a background in neuroscience and engineering. Particularly interested in Python, machine learning, data visualisation and analysis.

Twitter: pr4deepr

Location: Melbourne, Australia

Blog: https://www.linkedin.com/in/rajapradeep/

Hi 👋

I am a Research Scientist passionate about image and data analysis in biomedical research.

🔭 Spend a lot of time analysing microscopy images in Python and ImageJ.
🔧 Enjoy developing user-friendly open source tools.
👯 I’m looking to collaborate on bioimage analysis tools and workflows.
🤔 Would love help with identifying tools and methods to analyze multivariate data.
💬 Ask me about image and data analysis in biomedical research.

Publications:

Talks:

DASK Life Sciences Summit 2021: Experiences using Dask for large microscopy datasets

Pradeep Rajasekhar's Projects

2019-advanced-python

Advanced python class material for the 2019 summer school in Canberra.

2019-data-tidying-and-visualisation

Data vizualisation class materials for the 2019 summer school in Canberra.

articles

Links to images/video/code used in articles

aspp-visualisation

Exercises and data for the ASPP Visualisation and Tidy Data workshop

assistant

A user interface for GPU-accelerated image processing using CLIJ2

australia_victorian_crime_statistics

Crime statistics Victoria, Australia

biapy

Open source Python library for building bioimage analysis pipelines

cellpose

a generalist algorithm for cellular segmentation

clic_prototype

GPU-accelerated Image Processing library

This repository provides a collection of tools to simplify reading CZI (Carl Zeiss Image) pixel and metadata in Python. In addition it also contains other useful utilities to visualize CZI images inside Napari.

data-visualizar

Visualize data or 3D models (.obj) in augmented reality through the web with Google Poly, AR.js, flask.py (Mobile compatible)

deeplabv3plus-pytorch

A DeepLab V3+ Model with ResNet 50 Encoder to perform Binary Segmentation Tasks. Implemented with PyTorch.

docker-example-omero

OMERO Docker compose example

drlachie.github.io

folder-structure-conventions

Folder / directory structure options and naming conventions for software projects

gutanalysistoolbox

Analysis and characterisation of cells within the gut wall using deep learning models. The current focus is on studying enteric neurons and enteric glia.