An Automated Framework for Multi-label Brain Tumor Segmentation based onKernel Sparse Representation-Reference-Cited by-同舟云学术

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An Automated Framework for Multi-label Brain Tumor Segmentation based onKernel Sparse Representation

Published:2017-04-06 Issue:1 Volume:14 Page:
ISSN:1785-8860
Container-title:Acta Polytechnica Hungarica
language:
Short-container-title:APH

Author:

Publisher

Obuda University

Subject

General Engineering

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An efficient computational framework for gastrointestinal disorder prediction using attention-based transfer learning;PeerJ Computer Science;2024-05-28

2. Advancements in health informatics: finite element insights into medial open-wedge high tibial osteotomy and lateral meniscal tears;Mathematical Biosciences and Engineering;2024

3. Optimal Superpixel Kernel-Based Kernel Low-Rank and Sparsity Representation for Brain Tumour Segmentation;Computational Intelligence and Neuroscience;2022-06-24

4. Brain Tumor MR Image Classification Using Convolutional Dictionary Learning With Local Constraint;Frontiers in Neuroscience;2021-05-28

5. A Transfer Model Based on Supervised Multi-Layer Dictionary Learning for Brain Tumor MRI Image Recognition;Frontiers in Neuroscience;2021-05-28

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