Lusca: FIJI (ImageJ) based tool for automated morphological analysis of cellular and subcellular structures

Scientific paper - Original scientific paper

• Author: Iva Šimunić
• Author: Denis Jagečić
• Author: Jasmina Isaković
• Author: Marina Dobrivojević Radmilović
• Author: Dinko Mitrečić
• Author's institution: University of Zagreb; School of Medicine; (Croatian Institiute for Brain Research)
• Author's institution: University of Zagreb; School of Medicine; (Department of Histology and Embryology)
• Scientific / art field, discipline and subdiscipline: BIOMEDICINE AND HEALTHCARE; Basic Medical Sciences; Cytology, Histology and Embryology

Abstract (english)

The human body consists of diverse subcellular, cellular and supracellular structures. Neurons possess varying-sized projections that interact with different cellular structures leading to the development of highly complex morphologies. Aiming to enhance image analysis of complex biological forms including neurons using available FIJI (ImageJ) plugins, Lusca, an advanced open-source tool, was developed. Lusca utilizes machine learning for image segmentation with intensity and size thresholds. It performs particle analysis to ascertain parameters such as area/volume, quantity, and intensity, in addition to skeletonization for determining length, branching, and width. Moreover, in conjunction with colocalization measurements, it provides an extensive set of 29 morphometric parameters for both 2D and 3D analysis. This is a significant enhancement compared to other scripts that offer only 5–15 parameters. Consequently, it ensures quicker and more precise quantification by effectively eliminating noise and discerning subtle details. With three times larger execution speed, fewer false positive and negative results, and the capacity to measure various parameters, Lusca surpasses other existing open-source solutions. Its implementation of machine learning-based segmentation facilitates versatile applications for different cell types and biological structures, including mitochondria, fibres, and vessels. Lusca’s automated and precise measurement capability makes it an ideal choice for diverse biological image analyses.

• Keywords (english): Humans; Image Processing, Computer-Assisted / methods; Mitochondria; Neurons
• Language: english
• Publication type: Scientific paper - Original scientific paper
• Publication status: Published
• Peer review: Peer review
• Publication version: Published version
• Journal title: Scientific Reports
• Numbering: vol. 14, no. 1, 7383
• e-ISSN: 2045-2322
• DOI: https://doi.org/10.1038/s41598-024-57650-6
• URN:NBN: urn:nbn:hr:105:234312
• Publication: 2024-03-28
• Project: Number: UIP-2017-05-8082; Title (croatian): Uloga bradikinina u ishemiji mozga i mrežnice u mišjim modelima dijabetesa; Title (english): The role of bradykinin in brain and retinal ischemia in diabetic murine models; Acronym: BRADISCHEMIA; Leader: Marina Radmilović Dobrivojević; Jurisdiction: Croatia; Funding stream: Installation Research Projects
• Project: Number: IP-2022-10-4656; Title (croatian): Otkrivanje neurorazvojne osnove Downovog sindroma pomoću jedinstvenih organoida ljudskog mozga; Title (english): Revealing the Neurodevelopmental Basis of Down Syndrome on a Unique Human Brain Organoid Model; Acronym: DevDown; Leader: Dinko Mitrečić; Jurisdiction: Croatia; Funding stream: Research Projects
• Document URL: https://www.nature.com/articles/s41598-024-57650-6
• Type of resource: Text
• Access conditions: Open access
• Created on: 2024-09-26 11:03:22