# An Open-Source COVID-19 CT Dataset with Automatic Lung Tissue Classification for Radiomics

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/an-open-source-covid-19-ct-dataset-with-automatic-lung-tissue-classification-for/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Paolo Zaffino,Aldo Marzullo,Sara Moccia,Francesco Calimeri,Elena De Momi,Bernardo Bertucci,Pier Paolo Arcuri,Maria Francesca Spadea |
| Citations | 42 |
| DOI | 10.3390/bioengineering8020026 |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2306-5354/8/2/26/pdf?version=1614064353 |
| OpenAlex ID | https://openalex.org/W3129415988 |
| PMID | 33669235 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Aldo Marzullo](https://scholariq.org/researchers/aldo-marzullo/)

## Paper journal

- [Bioengineering](https://scholariq.org/journals/bioengineering/)

## Paper primary topic

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

## Paper topics

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.