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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: December 2025
Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19459
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 145
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Published Paper Details
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| Paper Title: | Improving Gastric Ulcer Diagnosis With Convolution Neural Network Using Endoscopy Images |
| Authors Name: | Mr.Murugan S , Mr Murugesan D , Mr.Barath A , Mr Jayasurya N |
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IJRTI_202984
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| Published Paper Id: | IJRTI2504248 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | Stomach ulcers, a common gastrointestinal disorder, can lead to severe complications if left undiagnosed or untreated. Early and accurate detection is critical to improving patient outcomes and reducing healthcare costs. This project aims to develop an artificial intelligence (AI)-based system to detect and classify stomach ulcers using medical imaging techniques such as endoscopy. Leveraging deep learning algorithms, particularly convolutional neural networks (CNNs), the system analyzes endoscopic images to identify ulcerative lesions with high accuracy and efficiency. The proposed model integrates advanced image preprocessing techniques, such as segmentation and contrast enhancement, to isolate regions of interest and improve diagnostic precision. A comprehensive dataset of annotated images, collected in collaboration with medical professionals, is used for training and validation. The system is designed to provide real-time diagnostic support, assisting clinicians in identifying ulcers, assessing their severity, and distinguishing them from other gastric conditions. This AI-based approach has the potential to reduce diagnostic errors, speed up clinical workflows, and make expert-level diagnostic capabilities accessible in resource-limited settings. By combining technological innovation with medical expertise, this project aims to advance healthcare delivery and improve the quality of life for patients suffering from gastric disorders. |
| Keywords: | Stomach Ulcer, CNN, Endoscopy Images, AI ,Image detection |
| Cite Article: | "Improving Gastric Ulcer Diagnosis With Convolution Neural Network Using Endoscopy Images ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c199-c212, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504248.pdf |
| Downloads: | 000337 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2504248
Registration ID:202984
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: c199-c212 Country: Namakkal , Tamil Nadu , India Research Area: Bio Medical Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504248 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504248 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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