# Explainable Deep Learning Framework for Ground Glass Opacity (GGO) Segmentation from Chest CT Scans

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/explainable-deep-learning-framework-for-ground-glass-opacity-ggo-segmentation/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Paula Atim,Shereen Fouad,Sinling Tiffany Yu,A. Fratini,Arvind Rajasekaran,Pankaj Nagori,John Morlese,Bahadar Bhatia |
| Citations | 2 |
| DOI | 10.1007/978-981-96-3863-5_18 |
| Fields | Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://publications.aston.ac.uk/id/eprint/46770/1/MICAD_2024.pdf |
| OpenAlex ID | https://openalex.org/W4409180288 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Bahadar Bhatia](https://scholariq.org/researchers/bahadar-bhatia/)

## Paper journal

- [Lecture notes in electrical engineering](https://scholariq.org/journals/lecture-notes-in-electrical-engineering/)

## 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.