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Gastric Tract Infections Detection and Classification from Wireless Capsule Endoscopy using Computer Vision
Amna Liaqat1, Muhammad Attique Khan2, Muhammad Sharif1
1Department of Computer Science, COMSATS University Islamabad, Wah Cantt, Pakistan.
Current Medical Imaging
|April 27, 2020
Summary
Early detection of gastric infections using automated Computer-Aided Diagnosis (CAD) with Wireless Capsule Endoscopy (WCE) is crucial. This review highlights WCE
Area of Science:
- Medical Imaging
- Gastroenterology
- Computer-Aided Diagnosis
Background:
- Gastric infections pose a significant health risk with high mortality rates.
- Manual diagnosis is time-consuming and costly, necessitating advanced solutions.
- Wireless Capsule Endoscopy (WCE) offers a less invasive diagnostic approach.
Purpose of the Study:
- To review the importance and scope of WCE in gastric infection detection.
- To outline the automated diagnostic process using WCE.
- To identify challenges and future directions in WCE-based gastric infection diagnosis.
Main Methods:
- Review of existing literature on WCE for gastric infections.
- Discussion of automated Computer-Aided Diagnosis (CAD) steps: preprocessing, feature extraction, segmentation, and classification.
- Analysis of challenges impacting accuracy and computation time.
Main Results:
- WCE is vital for medical imaging in detecting gastric issues.
- Automated CAD systems using WCE can aid endoscopy specialists.
- Challenges in WCE processing affect diagnostic efficiency.
Conclusions:
- Automated WCE systems are essential for timely and accurate gastric infection diagnosis.
- Addressing current challenges can improve detection rates and reduce diagnosis time.
- Further research is needed to optimize WCE-based diagnostic protocols.
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