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

Znanstveni rad - Izvorni znanstveni rad

• Autor: Iva Šimunić
• Autor: Denis Jagečić
• Autor: Jasmina Isaković
• Autor: Marina Dobrivojević Radmilović
• Autor: Dinko Mitrečić
• Autorova ustanova: Sveučilište u Zagrebu; Medicinski fakultet; (HRVATSKI INSTITUT ZA ISTRAŽIVANJE MOZGA)
• Autorova ustanova: Sveučilište u Zagrebu; Medicinski fakultet; (KATEDRA ZA HISTOLOGIJU I EMBRIOLOGIJU)
• Znanstveno / umjetničko područje, polje i grana: BIOMEDICINA I ZDRAVSTVO; Temeljne medicinske znanosti; Citologija, histologija i embriologija

Sažetak (engleski)

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.

• Ključne riječi (engleski): Humans; Image Processing, Computer-Assisted / methods; Mitochondria; Neurons
• Jezik: engleski
• Vrsta publikacije: Znanstveni rad - Izvorni znanstveni rad
• Status objave: Objavljen
• Vrsta recenzije: Recenziran
• Verzija publikacije: Objavljena verzija rada (izdavačev PDF)
• Naslov časopisa: Scientific Reports
• Brojčani podaci: vol. 14, br. 1, 7383
• e-ISSN: 2045-2322
• DOI: https://doi.org/10.1038/s41598-024-57650-6
• URN:NBN: urn:nbn:hr:105:234312
• Datum objave publikacije: 2024-03-28
• Projekt: Šifra: UIP-2017-05-8082; Naziv (hrvatski): Uloga bradikinina u ishemiji mozga i mrežnice u mišjim modelima dijabetesa; Naziv (engleski): The role of bradykinin in brain and retinal ischemia in diabetic murine models; Kratica: BRADISCHEMIA; Voditelj: Marina Radmilović Dobrivojević; Pravna nadležnost: Hrvatska; Financijer: Hrvatska zaklada za znanost; Linija financiranja: Installation Research Projects
• Projekt: Šifra: IP-2022-10-4656; Naziv (hrvatski): Otkrivanje neurorazvojne osnove Downovog sindroma pomoću jedinstvenih organoida ljudskog mozga; Naziv (engleski): Revealing the Neurodevelopmental Basis of Down Syndrome on a Unique Human Brain Organoid Model; Kratica: DevDown; Voditelj: Dinko Mitrečić; Pravna nadležnost: Hrvatska; Financijer: Hrvatska zaklada za znanost; Linija financiranja: Research Projects
• URL dokumenta: https://www.nature.com/articles/s41598-024-57650-6
• Vrsta resursa: Tekst
• Prava pristupa: Otvoreni pristup
• Datum i vrijeme pohrane: 2024-09-26 11:03:22