Oncology/Hematology

Brain Cancer

Latest AI and machine learning research in brain cancer for healthcare professionals.

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Showing 1681-1701 of 6,123 articles
Inference of cancer driver mutations from tumor microenvironmentcomposition: a pan-cancer study with cross-platform external validation

Cancer driver mutations shape the tumor microenvironment (TME), yet whether TME composition alone ca...

HD-TTA: Hypothesis-Driven Test-Time Adaptation for Safer Brain Tumor Segmentation

Standard Test-Time Adaptation (TTA) methods typically treat inference as a blind optimization task, ...

Spatial multi-omics identify an immunosuppressive lipid-laden macrophage niche in primary CNS lymphoma

Primary central nervous system lymphoma (PCNSL) is a subtype of diffuse large B-cell lymphoma (DLBCL...

A NOVEL DEEP LEARNING MODEL, RDBCYCYLEGAN-CBAM FOR LOW-DOSE CT IMAGE DENOISING

Computed Tomography (CT) is one of the largest contributors to radiation exposure from medical imagi...

VariViT: A Vision Transformer for Variable Image Sizes

Vision Transformers (ViTs) have emerged as the state-of-the-art architecture in representation learn...

A radiation-free screening system for adolescent idiopathic scoliosis using deep learning on 3D back surface point clouds

Widespread screening for Adolescent Idiopathic Scoliosis (AIS) is critical for timely intervention b...

Learning Glioblastoma Tumor Heterogeneity Using Brain Inspired Topological Neural Networks

Accurate prognosis for Glioblastoma (GBM) using deep learning (DL) is hindered by extreme spatial an...

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting...

Multiparameter Uncertainty Mapping in Quantitative Molecular MRI using a Physics-Structured Variational Autoencoder (PS-VAE)

Quantitative imaging methods, such as magnetic resonance fingerprinting (MRF), aim to extract interp...

Training Beyond Convergence: Grokking nnU-Net for Glioma Segmentation in Sub-Saharan MRI

Gliomas are placing an increasingly clinical burden on Sub-Saharan Africa (SSA). In the region, the ...

Feature Integration of FDG PET Brain Imaging Using Deep Learning for Sensitive Cognitive Decline Detection

Background Distinguishing individuals with cognitive decline (CD), including early Alzheimers diseas...

A Tumor Aware DenseNet Swin Hybrid Learning with Boosted and Hierarchical Feature Spaces for Large-Scale Brain MRI Classification

This study proposes an efficient Densely Swin Hybrid (EDSH) framework for brain tumor MRI analysis, ...

Fusion-Restoration Image Processing Algorithm to Improve the High-Temperature Deformation Measurement

In the deformation measurement of high-temperature structures, image degradation caused by thermal r...

Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype

Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. Histomorphology is ...

Karhunen-Loève Expansion-Based Residual Anomaly Map for Resource-Efficient Glioma MRI Segmentation

Accurate segmentation of brain tumors is essential for clinical diagnosis and treatment planning. De...

GARD: Genomic Data based Drug Repurposing in Head and Neck Cancer with Large Language Model Validation

Background/ObjectivesHead and neck cancer (HNC) represents the seventh most common cancer diagnosis ...

Onco-Seg: Adapting Promptable Concept Segmentation for Multi-Modal Medical Imaging

Medical image segmentation remains a critical bottleneck in clinical workflows, from diagnostic radi...

Real-Time Dose-Guided Radiation Therapy.

Dramatic strides have been made in real-time adaptive radiation therapy, where treating single tumor...

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F3-Net: Foundation Model for Full Abnormality Segmentation of Medical Images with Flexible Input Modality Requirement

F3-Net is a foundation model designed to overcome persistent challenges in clinical medical image ...

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