Oncology/Hematology

Brain Cancer

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

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Automatic Bevacizumab Response Prediction in Ovarian Cancer from Digital Pathology Images via Novel AI-based Computational Pipeline

Ovarian cancer is one of the gynecological cancer types, which, if metastasized and not detected ear...

Predicting one-year postoperative functional status in contrast-enhancing glioma

Background and Objectives Preoperative prediction of functional outcomes in contrast-enhancing gliom...

A Data-Centric Framework for Intraoperative Fluorescence Lifetime Imaging for Glioma Surgical Guidance

Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resectio...

Radiomics- and Clinical Feature-Driven Prediction of Volumetric Response in Skull-Base Meningioma after CyberKnife Radiosurgery

Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomica...

GlioVision: A Multi-Modal MRI Framework for Non-Invasive Glioma Molecular Biomarkers Prediction

Gliomas are aggressive primary brain tumors that necessitate critical molecular biomarker prediction...

Glio-SERS: Label-Free Molecular Profiling of Plasma Extracellular Vesicles in Brain Tumors Using SERS and Artificial Intelligence

Extracellular vesicles are increasingly recognized as important carriers of disease-associated molec...

an interpretable vision transformer framework for automated brain tumor classification

Brain tumors represent one of the most critical neurological conditions, where early and accurate di...

AI Approach for MRI-only Full-Spine Vertebral Segmentation and 3D Reconstruction in Paediatric Scoliosis

MRI is preferred over CT in paediatric imaging because it avoids ionising radiation, but its use in ...

Topology-Driven Fusion of nnU-Net and MedNeXt for Accurate Brain Tumor Segmentation on Sub-Saharan Africa Dataset

Accurate automatic brain tumor segmentation in Low and Middle-Income (LMIC) countries is challenging...

Auxiliary Clinical Prompt Integration into Vision-Language Prompt SAM for Brain Tumor Segmentation

Background. Adult diffuse glioma is a representative class of primary brain tumors for which accurat...

Multi-Stain Fusion of Histopathology Images Using Deep Learning for Pediatric Brain Tumor Classification

The classification of pediatric brain tumors is investigated using deep learning on hematoxylin and ...

A Scalable High-Density Microwell Assay for Single-Cell Clonal Expansion Profiling

Traditional clonogenic assays remain central to evaluating the self-renewal capacity of tumor cells....

Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge

Clinical deployment of automated brain MRI analysis faces a fundamental challenge: clinical data is ...

Adaptive Dual Residual U-Net with Attention Gate and Multiscale Spatial Attention Mechanisms (ADRUwAMS)

Glioma is a harmful brain tumor that requires early detection to ensure better health results. Early...

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis

We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-spe...

Improving Glioblastoma Classification Using Quantitative Transport Mapping with a Synthetic Data Trained Deep Neural Network

Purpose: To develop a deep neural network-based, AIF-free, perfusion estimation method (QTMnet) for ...

Evaluating the Large Language Model-Based Quality Assurance Tool for Auto-Contouring

Purpose: Manual verification of AI-based auto-contouring is labor-intensive and prone to fatigue-rel...

Knowledge-Guided Adversarial Training for Infrared Object Detection via Thermal Radiation Modeling

In complex environments, infrared object detection exhibits broad applicability and stability across...

RVLM: Recursive Vision-Language Models with Adaptive Depth

Medical AI systems face two fundamental limitations. First, conventional vision-language models (VLM...

An Explainable AI-Driven Framework for Automated Brain Tumor Segmentation Using an Attention-Enhanced U-Net

Computer-aided segmentation of brain tumors from MRI data is of crucial significance to clinical dec...

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