A Novel Pancreatic Tumor Detection and Diagnosis Using Adaptive TransResUnet Aided Segmentation and ASPP with Multi-Scale EfficientNet-Based Classification
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Tarih
2025
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor and Francis Ltd.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
A 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.
Açıklama
CODEN : CYSYD
Anahtar Kelimeler
adaptive TransResUnet, atrous spatial pyramid pooling-based multi-scale EfficientNet with attention mechanism improved African vultures optimization algorithm, Pancreatic tumor detection, ROI cropping
Kaynak
Cybernetics and Systems
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
Sayı
Künye
Athab, 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. 10.1080/01969722.2025.2488820
