A Novel Pancreatic Tumor Detection and Diagnosis Using Adaptive TransResUnet Aided Segmentation and ASPP with Multi-Scale EfficientNet-Based Classification

Athab, Naama MethabIbrahim, Abdullahi AbduNaseri, Raghda Awad ShabanFarhan, Hameed Mutlag2025-08-142025-08-142025Athab, N. M., Ibrahim, A. A., Naseri, R. A. S., & Farhan, H. M. (2025). A Novel Pancreatic Tumor Detection and Diagnosis Using Adaptive TransResUnet Aided Segmentation and ASPP with Multi-Scale EfficientNet-Based Classification. Cybernetics and Systems, 1-48. 10.1080/01969722.2025.24888200196-9722https://hdl.handle.net/20.500.12939/5915CODEN : CYSYDA deadly disease with poor prognosis procedure available at present is the pancreatic tumor. Efficient detection is done using a Computer-Aided Diagnosis (CAD) system. The early detection of pancreatic tumors can enhance the survival rate. However, no sufficient works are dedicated to detect pancreatic tumors at its beginning stages. Hence, an advanced deep learning-oriented segmentation process to assist in the detection of pancreatic tumor is developed in this work. The necessary CT and MRI images are gathered from the utilization of IoT-based devices. Once the input image is gathered, the segmentation is carried out. An Adaptive TransResUnet (ATResUNet) is utilized for the segmentation procedure. The variables in the ATResUNet are tuned with the help of Improved African Vultures Optimization Algorithm (IAVOA). The segmented image is further considered to crop the Region of Interest (ROI). The cropped ROI is finally given as input to the suggested Atrous Spatial Pyramid Pooling-based Multi-scale EfficientNet with Attention Mechanism (ASPP-MENetAM) model. The detection of the pancreatic tumor is carried out using the ASPP-MENetAM framework. The detection outcome from the implemented ASPP-MENetAM is then compared with the results from other conventional pancreatic tumor detection models to assess the efficacy of the implemented detection system.eninfo:eu-repo/semantics/closedAccessadaptive TransResUnetatrous spatial pyramid pooling-based multi-scale EfficientNet with attention mechanism improved African vultures optimization algorithmPancreatic tumor detectionROI croppingA Novel Pancreatic Tumor Detection and Diagnosis Using Adaptive TransResUnet Aided Segmentation and ASPP with Multi-Scale EfficientNet-Based ClassificationArticle10.1080/01969722.2025.24888202-s2.0-105007013732Q2WOS:001497319900001Q3