Semantic Segmentation of Gastrointestinal Tract in MRI Scans Using PSPNet Model With ResNet34 Feature Encoding Network

Author:

Sharma Neha1,Gupta Sheifali1ORCID,Rajab Adel2ORCID,Elmagzoub Mohamed A.3ORCID,Rajab Khairan2,Shaikh Asadullah4ORCID

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University, Chandigarh, Punjab, India

2. Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

3. Department of Network and Communication Engineering, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

4. Department of Information Systems, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

Funder

Deanship of Scientific Research at Najran University under the Research Groups Funding Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference35 articles.

1. Polyp-Alert: Near real-time feedback during colonoscopy

2. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

3. Polyp detection and radius measurement in small intestine using video capsule endoscopy

4. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;arXiv 1905 11946,2019

5. Colorectal Segmentation Using Multiple Encoder-Decoder Network in Colonoscopy Images

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