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Research Paper | Computer Science and Information Technology | India | Volume 12 Issue 11, November 2023 | Popularity: 5.3 / 10
Enhancing Wireless Capsule Endoscopic Image Classification using Mayfly Algorithm with Deep Learning Approach
M. Amirthalingam, R. Ponnusamy
Abstract: Wireless capsule endoscopy (WCE) image classification is a pivotal application of medical image analysis that mainly focuses on the automatic classification of images obtained by small ingestible capsules as they traverse the gastrointestinal tract. These images play a major role in the diagnosis and monitoring of different gastrointestinal disorders, namely small bowel tumors, inflammatory bowel disease, and gastrointestinal bleeding. Innovative machine learning (ML) and deep learning (DL) modelsare employed to categorize these images into applicable clinical categories, aiding healthcare professionals in making timely and accurate diagnoses. The development of robust classification approaches for WCE images has the potential to considerably improve the accuracy and efficiency of gastrointestinal disease detection, ultimately enhancing patient care and outcomes. This research introduces an Enhanced Wireless Capsule Endoscopic Image Classification employing Mayfly Algorithm with Deep Learning (WCEIC-MFADL) Approach. The major intention of WCEIC-MFADL technique focuses on classification and recognition of WCE images. To obtain this, WCEIC-MFADL technique follows a Gaussian filtering (GF) based noise removal procedure. Additionally, WCEIC-MFADL model usesSqueezeNet model for deriving feature vectors. For WCE image classification, the WCEIC-MFADL technique uses gated recurrent unit (GRU) model. At last, the MFA can be applied for the optimal hyperparameter tuning of the GRU model which aidsin enhanced classifier results. To highlight improved performance of WCEIC-MFADL method, a huge range of simulations was involved. An experimental result stated that WCEIC-MFADL technique achieves better performance than other methods.
Keywords: Wireless Capsule Endoscopy, Gastrointestinal Tract, Machine Learning, Gated Recurrent Unit, Image Classification
Edition: Volume 12 Issue 11, November 2023
Pages: 1113 - 1124
DOI: https://www.doi.org/10.21275/SR231115113636
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