The architecture of the SVNC-Net.

<div><p>Accurate measurement of spleen volume is essential for the diagnosis of splenomegaly. While Computed Tomography (CT) is among the most reliable imaging modalities for this task, manual segmentation of the spleen is labor-intensive and impractical for routine clinical workflows. A...

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Detaylı Bibliyografya
Yazar:	Mehmet Zahid Genc (22683526) (author)
Diğer Yazarlar:	Yaser Dalveren (22683529) (author), Ali Kara (690960) (author), Mohammad Derawi (22683532) (author), Jan Kubicek (170285) (author), Marek Penhaker (13014797) (author)
Baskı/Yayın Bilgisi:	2025
Konular:	Medicine Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified training compression techniques targeted architectural optimizations reliable imaging modalities promising results achieved neighborhood convolutional network model &# 8217 limited processing capabilities depthwise separable convolution high segmentation accuracy 3d organ segmentation routine clinical workflows memory demands make net builds upon entirely new architecture comparative analysis verified comparative analysis manual segmentation memory usage clinical deployment viable alternative time applications recent years purpose due ongoing efforts net variant net framework less suitable inference speed including upernet highly suitable first time findings contribute explore post edge devices constrained environments computed tomography 2d convolutions
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The architecture of the SVNC-Net.

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