Fattaneh Pourakpour, Ákos Szölgyén, Ramin Nateghi, David A Gutman, David Manthey, Lee Ad Cooper
{"title":"HistomicsTK: A Python toolkit for pathology image analysis algorithms.","authors":"Fattaneh Pourakpour, Ákos Szölgyén, Ramin Nateghi, David A Gutman, David Manthey, Lee Ad Cooper","doi":"10.1016/j.softx.2025.102318","DOIUrl":null,"url":null,"abstract":"<p><p>Growth in the digital imaging of glass tissue slides has produced petabytes of data, however, this data remains underutilized in biomedical research due in part to a lack of open-source software. HistomicsTK is an open-source Python package that provides preprocessing, segmentation, and feature extraction capabilities for building histology image processing pipelines. HistomicsTK can function as a standalone Python package or serve containerized pipelines through a web-based interface using the Digital Slide Archive platform. This paper provides an overview of HistomicsTK with illustrative use cases and describes how this project engages the community in software development and maintenance.</p>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494233/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.softx.2025.102318","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/22 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Growth in the digital imaging of glass tissue slides has produced petabytes of data, however, this data remains underutilized in biomedical research due in part to a lack of open-source software. HistomicsTK is an open-source Python package that provides preprocessing, segmentation, and feature extraction capabilities for building histology image processing pipelines. HistomicsTK can function as a standalone Python package or serve containerized pipelines through a web-based interface using the Digital Slide Archive platform. This paper provides an overview of HistomicsTK with illustrative use cases and describes how this project engages the community in software development and maintenance.
期刊介绍:
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.