A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture

Glioma is the most aggressive and dangerous primary brain tumor with a survival time of less than 14 months. Segmentation of tumors is a necessary task in the image processing of the gliomas and is important for its timely diagnosis and starting a treatment. Using 3D U-net architecture to perform se...

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Vydané v:	BMC bioinformatics Ročník 23; číslo 1; s. 251 - 21
Hlavní autori:	Shaukat, Zeeshan, Farooq, Qurat ul Ain, Tu, Shanshan, Xiao, Chuangbai, Ali, Saqib
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London BioMed Central 24.06.2022 Springer Nature B.V BMC
Predmet:	3D U-Net Accuracy Algorithms Bioinformatics Biomedical and Life Sciences Brain Brain cancer Brain Neoplasms - diagnostic imaging Brain Neoplasms - pathology Brain tumor Brain tumors Cloud Computing Computational Biology/Bioinformatics Computer Appl. in Life Sciences Datasets Deep Learning Experiments Glioma Humans Image processing Image Processing, Computer-Assisted - methods Image segmentation Life Sciences Literature reviews Magnetic resonance imaging Magnetic Resonance Imaging - methods Mathematical analysis Medical diagnosis Methods Microarrays Neural networks Optimization Semantic segmentation Semantics Tomography Traumatic brain injury Tumors Deep learning Brain tumor Cloud computing Semantic segmentation 3D U-Net
ISSN:	1471-2105, 1471-2105
On-line prístup:	Získať plný text
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