# UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/unet-deep-learning-architecture-for-segmentation-of-vascular-and-non-vascular/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jasjit S. Suri,Mrinalini Bhagawati,Sushant Agarwal,Sudip Paul,Amit Kumar Pandey,Suneet Gupta,Luca Saba,Kosmas I. Paraskevas,Narendra N. Khanna,John R. Laird,Amer M. Johri,Manudeep Kalra,Mostafa M. Fouda,Mostafa Fatemi,Subbaram Naidu |
| Citations | 86 |
| DOI | 10.1109/access.2022.3232561 |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/10005208/09999432.pdf |
| OpenAlex ID | https://openalex.org/W4312726348 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Suneet Gupta](https://scholariq.org/researchers/suneet-gupta/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Cerebrovascular and Carotid Artery Diseases](https://scholariq.org/topics/cerebrovascular-and-carotid-artery-diseases/)
- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)

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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.