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Frailty and postoperative outcomes in brain tumor patients: a systematic review subdivided by tumor etiology
PurposeFrailty has gained prominence in neurosurgical oncology, with more studies exploring its relationship to postoperative outcomes in brain tumor...
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Harnessing immunotherapy for brain metastases: insights into tumor–brain microenvironment interactions and emerging treatment modalities
Brain metastases signify a deleterious milestone in the progression of several advanced cancers, predominantly originating from lung, breast and...
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Brain tumor image segmentation based on improved FPN
PurposeAutomatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation....
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Mechanical characteristics of glioblastoma and peritumoral tumor-free human brain tissue
BackgroundThe diagnosis of brain tumor is a serious event for the affected patient. Surgical resection is a crucial part in the treatment of brain...
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NeuroIGN: Explainable Multimodal Image-Guided System for Precise Brain Tumor Surgery
Precise neurosurgical guidance is critical for successful brain surgeries and plays a vital role in all phases of image-guided neurosurgery (IGN)....
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Coordination of anti-CTLA-4 with whole-brain radiation therapy decreases tumor burden during treatment in a novel syngeneic model of lung cancer brain metastasis
Lung cancer is the most common primary tumor to metastasize to the brain. Although advances in lung cancer therapy have increased rates of survival...
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Hippocampus segmentation after brain tumor resection via postoperative region synthesis
PurposeAccurately segmenting the hippocampus is an essential step in brain tumor radiotherapy planning. Some patients undergo brain tumor resection...
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Short and long-term prognostic value of intraoperative motor evoked potentials in brain tumor patients: a case series of 121 brain tumor patients
PurposeIatrogenic neurologic deficits adversely affect patient outcomes following brain tumor resection. Motor evoked potential (MEP) monitoring...
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A bis-boron boramino acid PET tracer for brain tumor diagnosis
PurposeBoramino acids are a class of amino acid biomimics that replace the carboxylate group with trifluoroborate and can achieve the 18 F-labeled...
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Refining neural network algorithms for accurate brain tumor classification in MRI imagery
Brain tumor diagnosis using MRI scans poses significant challenges due to the complex nature of tumor appearances and variations. Traditional methods...
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Integrated approach of federated learning with transfer learning for classification and diagnosis of brain tumor
Brain tumor classification using MRI images is a crucial yet challenging task in medical imaging. Accurate diagnosis is vital for effective treatment...
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Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention
PurposeFully convolutional neural networks architectures have proven to be useful for brain tumor segmentation tasks. However, their performance in...
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Brain Tumor Segmentation for Multi-Modal MRI with Missing Information
Deep convolutional neural networks (DCNNs) have shown promise in brain tumor segmentation from multi-modal MRI sequences, accommodating heterogeneity...
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A hybrid deep CNN model for brain tumor image multi-classification
The current approach to diagnosing and classifying brain tumors relies on the histological evaluation of biopsy samples, which is invasive,...
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Robust brain tumor classification by fusion of deep learning and channel-wise attention mode approach
Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists’ expertise and interpretive skills. However, the...
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Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
This review delves into the most recent advancements in applying artificial intelligence (AI) within neuro-oncology, specifically emphasizing work on...
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Advanced AI-driven approach for enhanced brain tumor detection from MRI images utilizing EfficientNetB2 with equalization and homomorphic filtering
Brain tumors pose a significant medical challenge necessitating precise detection and diagnosis, especially in Magnetic resonance imaging(MRI)....
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Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction
Deep learning models have demonstrated great potential in medical imaging but are limited by the expensive, large volume of annotations required. To...
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Association between elevated preoperative red cell distribution width and mortality after brain tumor craniotomy
Background: Red cell distribution width (RDW) has been recognized as a potential inflammatory biomarker, with elevated levels associated with adverse...
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Effect of tumor genetics, pathology, and location on fMRI of language reorganization in brain tumor patients
ObjectivesLanguage reorganization may follow tumor invasion of the dominant hemisphere. Tumor location, grade, and genetics influence the...
