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Found 19 papers, 4 papers with code
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data
Gliomas, a kind of brain tumor characterized by high mortality, present substantial diagnostic challenges in low- and middle-income countries, particularly in Sub-Saharan Africa.
Ranked #1 on
Brain Tumor Segmentation
on BraTS-Africa
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation
Additionally, an open-source web-application is accessible at https://segmenter. hope4kids. io/ which uses the docker container aparida12/brats-peds-2024:v20240913 .
Ranked #1 on
Brain Tumor Segmentation
on BraTs Peds 2024
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance Imaging
In 2023, the well-established Brain Tumor Segmentation (BraTS) challenge presented a substantial expansion with eight tasks and 4, 500 brain tumor cases.
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency
To further bridge the theory and algorithm, we devise the model called Sufficiency and Necessity Inspired Graph Learning (SNIGL), which ensembles an invariant subgraph classifier on top of latent sufficient and necessary invariant subgraphs, and a domain variant subgraph classifier specific to the test domain for generalization enhancement.
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-specific fine-tuning.
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children.
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions
LLaVA-Med, a pioneering large language and vision assistant for biomedicine, can perform multi-modal biomedical image and data analysis to provide a natural language interface for radiologists.
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0. 976, 0. 976, and 0. 964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0. 899, 0. 904, and 0. 871, respectively.
The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children.
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency
Under mild conditions, we show that the invariant subgraph can be extracted by minimizing an upper bound, which is built on the theoretical advance of probability of necessity and sufficiency.
Quantitative Metrics for Benchmarking Medical Image Harmonization
However, benchmarking the effectiveness of harmonization techniques has been a challenge due to the lack of widely available standardized datasets with ground truths.
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI
To prevent hallucination in medical imaging, such as magnetic resonance images (MRI) of the brain, we propose a one-shot learning method where we utilize neural style transfer for harmonization.
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing.
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)
Thus, the BraTS-Africa Challenge provides a unique opportunity to include brain MRI glioma cases from SSA in global efforts through the BraTS Challenge to develop and evaluate computer-aided-diagnostic (CAD) methods for the detection and characterization of glioma in resource-limited settings, where the potential for CAD tools to transform healthcare are more likely.
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children.
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)
In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023.
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
The challenge is organized as part of the ASNR-BraTS MICCAI challenge.
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality.
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
