Abstract: Ulcerative Colitis (UC), a chronic inflammatory bowel disease, presents significant diagnostic challenges due to its overlapping symptoms with other gastrointestinal disorders and the complex visual patterns in endoscopic imagery. Accurate and early detection is essential to guide effective treatment and improve patient outcomes. This research introduces a robust hybrid framework that combines convolutional feature extraction with bidirectional temporal modelling for the precise identification of UC from medical imagery. The proposed approach integrates CNNs—including MobileNetV3Large, Inception v3, InceptionResNetV2, and Xception—with Bi-GRU and Bi-LSTM networks. The CNNs are responsible for capturing high-level spatial features, while the Bi-GRU and Bi-LSTM modules enhance temporal context understanding, enabling the model to effectively interpret subtle patterns and transitions characteristic of UC. Each hybrid model was designed, and thoroughly tested on an curated set of experimental data. Among the combinations, the highest accuracy was of 93.10%, obtained with the Xception+ Bi-GRU + Bi-LSTM model. Inception v3 + Bi-GRU + Bi-LSTM followed closely, attaining an accuracy of 92.62%. The different data augmentation techniques is deployed to handle the class imbalance that exists in the LIMUC dataset . Notably, the bidirectional temporal modelling component significantly improved the recognition of sequential dependencies in medical image frames, enhancing the model’s diagnostic robustness. The findings demonstrate that integrating CNNs with bidirectional temporal encoders offers a promising solution for UC detection, providing a valuable tool for clinicians in automated diagnostic systems. This study not only contributes to the advancement of intelligent medical imaging but also paves the way for deploying real-time UC detection models in clinical practice.

Dharmendra Gupta, Jayesh Gangrade, Yadvendra Pratap Singh and Shweta Gangrade. “Robust Ulcerative Colitis Detection via Integrated Convolutional Feature Encoding, Bidirectional Temporal Context, and Data Augmentation for Class Imbalance”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.8 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160885

@article{Gupta2025,
title = {Robust Ulcerative Colitis Detection via Integrated Convolutional Feature Encoding, Bidirectional Temporal Context, and Data Augmentation for Class Imbalance},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160885},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160885},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {8},
author = {Dharmendra Gupta and Jayesh Gangrade and Yadvendra Pratap Singh and Shweta Gangrade}
}