Pinned Repositories
AimSeg
This project aims to accomplish the segmentation of three axonal components (axoplasm, inner cytoplasmic tongue and myelin) on TEM images using Fiji and ilastik
AimSeg_DLTraining
Jupyter Notebooks to train a DL pixel classifier
assess_segmentation
ImageJ macros to assess both semantic and instance segmentation.
cell_adhesion_assay
Bioimage analysis workflow for the analysis of high throughput microscpy experiments to assess cell adhesion (specifically, to quantify the binding of fluorescence-labeled cells to a cell monolayer) using Fiji
Cell_Detection_Approaches
Bioimage analysis pipelines to detect cells (nucleus + cytoplasm) and generate label images with the aim of establishing an object hierarchy
cell_proliferation_assay
Bioimage analysis workflow for the analysis of high throughput microscopy experiments to assess cell proliferation in pulse-chase experiments (BrdU or EdU) using Fiji
dhb-venus
ImageJ macro for the detection of DHB-Venus positive cells and the quantification of its nucleus-to-cytoplasm ratio
embl-dl-course-2022
Materials for the EMBL Deep Learning course
imagej.github.io
The ImageJ wiki
TrackMate-StarDist_Headless
Groovy scripts to run TrackMate-StarDist headless
paucabar's Repositories
paucabar/AimSeg
This project aims to accomplish the segmentation of three axonal components (axoplasm, inner cytoplasmic tongue and myelin) on TEM images using Fiji and ilastik
paucabar/Cell_Detection_Approaches
Bioimage analysis pipelines to detect cells (nucleus + cytoplasm) and generate label images with the aim of establishing an object hierarchy
paucabar/AimSeg_DLTraining
Jupyter Notebooks to train a DL pixel classifier
paucabar/assess_segmentation
ImageJ macros to assess both semantic and instance segmentation.
paucabar/cell_adhesion_assay
Bioimage analysis workflow for the analysis of high throughput microscpy experiments to assess cell adhesion (specifically, to quantify the binding of fluorescence-labeled cells to a cell monolayer) using Fiji
paucabar/cell_proliferation_assay
Bioimage analysis workflow for the analysis of high throughput microscopy experiments to assess cell proliferation in pulse-chase experiments (BrdU or EdU) using Fiji
paucabar/dhb-venus
ImageJ macro for the detection of DHB-Venus positive cells and the quantification of its nucleus-to-cytoplasm ratio
paucabar/embl-dl-course-2022
Materials for the EMBL Deep Learning course
paucabar/imagej.github.io
The ImageJ wiki
paucabar/neurosphere_assay
Bioimage analysis workflow for the analysis of high throughput microscpy experiments to assess neurosphere assays (or other similar assays based on spheroid growing) using Fiji and ilastik
paucabar/Spheroid_DL
paucabar/TrackMate-StarDist_Headless
Groovy scripts to run TrackMate-StarDist headless
paucabar/label_mask_operations
paucabar/oligodendrocyte_differentiation
paucabar/other_macros
Diverse workflows to automate some simple tasks
paucabar/pytorch_semantic_unet
paucabar/qupath-gradle-scripting-project
paucabar/region_connection_calculus
Example macros for linking 'related' objects between different binary masks, e.g., nucleus with its corresponding cytoplasm. Objects are indexed to establish their relations by means of the output matrix of the Region Connection Calculus plugin
paucabar/stsm_i3s
This repository contains CellProfiler pipelines, ImageJ macros and other files generated during my NEUBIAS Short Term Scientific Mission at the scientific platforms for BioSciences Screening and Advanced Light Microscopy, Instituto de Investigação e Inovação da Universidade do Porto (Porto, Portugal)