Brain metastasis detection using machine learning: a systematic review and meta-analysis
Background Accurate detection of brain metastasis (BM) is important for cancer patients. We
aimed to systematically review the performance and quality of machine-learning-based BM …
aimed to systematically review the performance and quality of machine-learning-based BM …
Artificial intelligence in brain tumour surgery—an emerging paradigm
S Williams, H Layard Horsfall, JP Funnell… - Cancers, 2021 - mdpi.com
Simple Summary Artificial intelligence (AI) is the branch of computer science that enables
machines to learn, reason, and problem solve. In recent decades, AI has been developed …
machines to learn, reason, and problem solve. In recent decades, AI has been developed …
The brain tumor segmentation (brats-mets) challenge 2023: Brain metastasis segmentation on pre-treatment mri
The translation of AI-generated brain metastases (BM) segmentation into clinical practice
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data
Brain metastasis (BM) is one of the main complications of many cancers, and the most
frequent malignancy of the central nervous system. Imaging studies of BMs are routinely …
frequent malignancy of the central nervous system. Imaging studies of BMs are routinely …
Deep learning for brain metastasis detection and segmentation in longitudinal MRI data
Purpose Brain metastases (BM) occur frequently in patients with metastatic cancer. Early
and accurate detection of BM is essential for treatment planning and prognosis in radiation …
and accurate detection of BM is essential for treatment planning and prognosis in radiation …
[HTML][HTML] Automated tumor segmentation in radiotherapy
Autosegmentation of gross tumor volumes holds promise to decrease clinical demand and
to provide consistency across clinicians and institutions for radiation treatment planning …
to provide consistency across clinicians and institutions for radiation treatment planning …
Integrating AI into radiology workflow: levels of research, production, and feedback maturity
We present a roadmap for integrating artificial intelligence (AI)-based image analysis
algorithms into existing radiology workflows such that (1) radiologists can significantly …
algorithms into existing radiology workflows such that (1) radiologists can significantly …
Deep learning for detecting brain metastases on MRI: a systematic review and meta-analysis
Simple Summary Manual detection and delineation of brain metastases are time consuming
and variable. Studies have therefore been conducted to automate this process using …
and variable. Studies have therefore been conducted to automate this process using …
Fully automated MR detection and segmentation of brain metastases in non‐small cell lung cancer using deep learning
ST Jünger, UCI Hoyer, D Schaufler… - Journal of Magnetic …, 2021 - Wiley Online Library
Background Non‐small cell lung cancer (NSCLC) is the most common tumor entity
spreading to the brain and up to 50% of patients develop brain metastases (BMs). Detection …
spreading to the brain and up to 50% of patients develop brain metastases (BMs). Detection …
Automatic segmentation of brain metastases using T1 magnetic resonance and computed tomography images
An increasing number of patients with multiple brain metastases are being treated with
stereotactic radiosurgery (SRS). Manually identifying and contouring all metastatic lesions is …
stereotactic radiosurgery (SRS). Manually identifying and contouring all metastatic lesions is …