HE image analysis pipeline for quantifying morphological features

Valeria Ariotta; Oskari Lehtonen; Shams Salloum; Giulia Micoli; Kari Lavikka; Ville Rantanen; Johanna Hynninen; Anni Virtanen; Sampsa Hautaniemi

doi:10.1016/j.jpi.2023.100339

HE image analysis pipeline for quantifying morphological features

Valeria Ariotta
, Oskari Lehtonen
, Shams Salloum
, Giulia Micoli
, Kari Lavikka
, Ville Rantanen
, Johanna Hynninen
, Anni Virtanen
, Sampsa Hautaniemi

Research output: Contribution to journal › Article › Scientific › peer-review

Original language	English
Journal	Journal of pathology informatics
Volume	14
ISSN	2229-5089
DOIs	https://doi.org/10.1016/j.jpi.2023.100339
Publication status	Published - 2023
MoE publication type	A1 Journal article-refereed

Fields of Science

3122 Cancers

Access to Document

10.1016/j.jpi.2023.100339Licence: CC BY

featuresFinal published version, 4.05 MBLicence: CC BY

Cite this

@article{1a1cce69412a44859d4eaa3e7340ae91,

title = "HE image analysis pipeline for quantifying morphological features",

keywords = "3122 Cancers",

author = "Valeria Ariotta and Oskari Lehtonen and Shams Salloum and Giulia Micoli and Kari Lavikka and Ville Rantanen and Johanna Hynninen and Anni Virtanen and Sampsa Hautaniemi",

year = "2023",

doi = "10.1016/j.jpi.2023.100339",

language = "English",

volume = "14",

journal = "Journal of pathology informatics",

issn = "2229-5089",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - HE image analysis pipeline for quantifying morphological features

AU - Ariotta, Valeria

AU - Lehtonen, Oskari

AU - Salloum, Shams

AU - Micoli, Giulia

AU - Lavikka, Kari

AU - Rantanen, Ville

AU - Hynninen, Johanna

AU - Virtanen, Anni

AU - Hautaniemi, Sampsa

PY - 2023

Y1 - 2023

KW - 3122 Cancers

U2 - 10.1016/j.jpi.2023.100339

DO - 10.1016/j.jpi.2023.100339

M3 - Article

SN - 2229-5089

VL - 14

JO - Journal of pathology informatics

JF - Journal of pathology informatics

ER -