# Semantic Segmentation of Pathological Lung Tissue With Dilated Fully Convolutional Networks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/semantic-segmentation-of-pathological-lung-tissue-with-dilated-fully/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Marios Anthimopoulos,Stergios Christodoulidis,Lukas Ebner,Thomas Geiser,Andreas Christe,Stavroula Mougiakakou |
| Citations | 152 |
| DOI | 10.1109/jbhi.2018.2818620 |
| Fields | Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/1803.06167 |
| OpenAlex ID | https://openalex.org/W2793444752 |
| PMID | 29993791 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Stavroula Mougiakakou](https://scholariq.org/researchers/stavroula-mougiakakou/)

## Paper journal

- [IEEE Journal of Biomedical and Health Informatics](https://scholariq.org/journals/ieee-journal-of-biomedical-and-health-informatics/)

## Paper primary topic

- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)

## Paper topics

- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)
- [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/)

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