3D U-Net to Leverage Spatial and Intensity Information from Different MRI Sequences to Enhance Tumor Boundary Delineation

Shaikh Abdul Sami
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Shaikh Abdul Sami: College of Information and Communication Engineering, Harbin Engineering University, China

Biomedical Journal of Scientific & Technical Research, 2025, vol. 60, issue 1, 52219-52239

Abstract: Accurate tumor boundary delineation is critical in medical imaging for diagnosis, treatment planning, and out- come monitoring. This study presents a 3D U-Net architecture designed to leverage spatial and intensity infor- mation from multiple MRI sequences to improve tumor segmentation. By integrating data from different mo- dalities, such as T1-weighted, T2-weighted, and FLAIR images, the network captures complementary features, enhancing its ability to differentiate between tumor tissue and surrounding structures.

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Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:60:y:2025:i:1:p:52219-52239

DOI: 10.26717/BJSTR.2025.60.009401

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