Abnormalities and Disease Detection in Gastro-Intestinal Tract Images
Gastrointestinal (GI) tract image analysis plays a crucial role in medical diagnosis. This research addresses the challenge of accurately classifying and segmenting GI images for real-time applications, where traditional methods often struggle due to the diversity and complexity of abnormalities. The high computational demands of this domain require efficient and adaptable solutions. This PhD thesis presents a multifaceted approach to GI image analysis. Initially, texture-based feature extraction and classification methods were explored, achieving high processing speed (over 4000 FPS) and strong performance (F1-score: 0.76, Accuracy: 0.98) on the Kvasir V2 dataset. The study then transiti...
| Authors | Zeshan Khan, Muhammad Atif Tahir |
|---|---|
| Primary category | eess.IV |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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