Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
[HTML][HTML] A novel deep learning method for recognition and classification of brain tumors from MRI images
A brain tumor is an abnormal growth in brain cells that causes damage to various blood
vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor …
vessels and nerves in the human body. An earlier and accurate diagnosis of the brain tumor …
Detection of brain tumor based on features fusion and machine learning
Automated detection of brain tumor is a more challenging work due to the variability and
complexity of shape, size, texture and location of lesions. The non-invasive MRI methods …
complexity of shape, size, texture and location of lesions. The non-invasive MRI methods …
Automatic brain lesion segmentation on standard magnetic resonance images: a sco** review
Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …
addressed with algorithm-based segmentation tools. In this study, we map the field of …
A stacked multi-connection simple reducing net for brain tumor segmentation
It is well known that the Unet has been widely used in the area of medical image
segmentation because of the cascade connection in the up-sampling process. However, it …
segmentation because of the cascade connection in the up-sampling process. However, it …
A multi-path adaptive fusion network for multimodal brain tumor segmentation
The deep learning method has shown its outstanding performance in object recognition and
becomes the first choice for medical image analysis. However, how to effectively propagate …
becomes the first choice for medical image analysis. However, how to effectively propagate …
Machine learning in neurooncology imaging: from study request to diagnosis and treatment
JE Villanueva-Meyer, P Chang, JM Lupo… - American Journal of …, 2019 - ajronline.org
OBJECTIVE. Machine learning has potential to play a key role across a variety of medical
imaging applications. This review seeks to elucidate the ways in which machine learning …
imaging applications. This review seeks to elucidate the ways in which machine learning …
How to improve the deep residual network to segment multi-modal brain tumor images
Brain tumor segmentation plays an important role in diagnosing brain tumor. Nowadays,
intense interest has been received in applying convolution neural networks in medical …
intense interest has been received in applying convolution neural networks in medical …
Segmentation of ultrasound brachial plexus based on U-Net
Y Wang, J Geng, C Zhou… - … international conference on …, 2021 - ieeexplore.ieee.org
Brachial plexus block anesthesia (PNB) is one of the anesthesia methods commonly used
by anesthesiologists in surgical operations. Anesthesiologists use ultrasonic equipment to …
by anesthesiologists in surgical operations. Anesthesiologists use ultrasonic equipment to …
3D EMSU‐Net: A framework for automatic segmentation of brain tumors
Glioma is the most common tumor in the brain's central nerve cells, which is extremely
dangerous clinically. Glioma's accurate surgical localization and diagnosis both rely on the …
dangerous clinically. Glioma's accurate surgical localization and diagnosis both rely on the …
Research on recommendation of big data for higher education based on deep learning
A Zhao, Y Ma - Scientific Programming, 2022 - Wiley Online Library
To improve the recommendation accuracy of educational resources, an intelligent
recommendation method based on autoencoder has been proposed by combining …
recommendation method based on autoencoder has been proposed by combining …