专题:Brain Tumor Detection and Classification

This cluster of papers focuses on the classification of brain tumor type and grade using various techniques such as MRI, deep learning, convolutional neural networks, feature extraction, and machine learning. The research aims to improve the accuracy and efficiency of brain tumor classification for better diagnosis and treatment.
最新文献
近5年高被引文献
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images

conference-paper Full Text OpenAlex 2256 FWCI259.8412

The Liver Tumor Segmentation Benchmark (LiTS)

article Full Text OpenAlex 1395 FWCI75.9112

Glioblastoma and Other Primary Brain Malignancies in Adults

article Full Text OpenAlex 1292 FWCI183.3116

SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining

article Full Text OpenAlex 648 FWCI57.8299

Epidemiology of Glioblastoma Multiforme–Literature Review

article Full Text OpenAlex 633 FWCI64.1542

MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques

article Full Text OpenAlex 623 FWCI51.2139

Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI

article Full Text OpenAlex 593 FWCI35.7531

UNETR++: Delving Into Efficient and Accurate 3D Medical Image Segmentation

article Full Text OpenAlex 505 FWCI68.2571

SynthStrip: skull stripping for any brain image

article Full Text OpenAlex 500 FWCI26.5638

Brain Tumor Detection Based on Deep Learning Approaches and Magnetic Resonance Imaging

article Full Text OpenAlex 497 FWCI40.9916