Accurate Segmentation of Brain Tumors in Magnetic Resonance Images with Pyramid Stage Decomposition Network Approach
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study explores the utilization of the Pyramid Scene Parsing Network (PSPNet) architecture to achieve accurate segmentation of brain tumors in magnetic resonance (MR) images. Experimental evaluations were conducted on different pre-trained backbone network models, including Vgg16, Inceptionv3, Mobilenetv2, Efficientnetb0, Resnet18, Resnet34, Resnet50, Resnet101, Resnext50, and Resnext101, assessing the performance of each model in brain tumor segmentation. The results highlight the VGG16-PSPNet model as the most successful, showcasing high F1-score, mIoU, precision, recall, and accuracy values.
Açıklama
32nd IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2024 -- Tarsus Univ Campus, Mersin, TURKEY
Anahtar Kelimeler
Brain tumors, Magnetic Resonance Imaging (MRI), Segmentation, Pyramid Scene Parsing Network (PSPNet), Medical Image Analysis
Kaynak
32nd IEEE Signal Processing and Communications Applications Conference, Siu 2024
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
