arXiv:2404.11725
공식 코드 · Papers with Code
Postoperative glioblastoma segmentation: Development of a fully automated pipeline using deep convolutional neural networks and comparison with currently available models
원문 초록
Accurately assessing tumor removal is paramount in the management of glioblastoma. We developed a pipeline using MRI scans and neural networks to segment tumor subregions and the surgical cavity in postoperative images. Our model excels in accurately classifying the extent of resection, offering a valuable tool for clinicians in assessing treatment effectiveness.
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skfolio: Portfolio Optimization in Python
100-Day Analysis of USD/IDR Exchange Rate Dynamics Around the 2025 U.S. Presidential Inauguration
Automated Risk Management Mechanisms in DeFi Lending Protocols: A Crosschain Comparative Analysis of Aave and Compound
Semantic Scheduling for LLM Inference
SDialog: A Python Toolkit for Synthetic Dialogue Generation and Analysis
From Axioms to Algorithms: Mechanized Proofs of the vNM Utility Theorem
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