The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Clinical monitoring of metastatic disease to the brain can be a laborious and time-consuming process, especially in cases involving multiple metastases when the assessment is performed manually. The Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) guideline, which utilizes the unidim...
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Veröffentlicht in: | ArXiv.org 2023-06 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Clinical monitoring of metastatic disease to the brain can be a laborious and
time-consuming process, especially in cases involving multiple metastases when
the assessment is performed manually. The Response Assessment in Neuro-Oncology
Brain Metastases (RANO-BM) guideline, which utilizes the unidimensional longest
diameter, is commonly used in clinical and research settings to evaluate
response to therapy in patients with brain metastases. However, accurate
volumetric assessment of the lesion and surrounding peri-lesional edema holds
significant importance in clinical decision-making and can greatly enhance
outcome prediction. The unique challenge in performing segmentations of brain
metastases lies in their common occurrence as small lesions. Detection and
segmentation of lesions that are smaller than 10 mm in size has not
demonstrated high accuracy in prior publications. The brain metastases
challenge sets itself apart from previously conducted MICCAI challenges on
glioma segmentation due to the significant variability in lesion size. Unlike
gliomas, which tend to be larger on presentation scans, brain metastases
exhibit a wide range of sizes and tend to include small lesions. We hope that
the BraTS-METS dataset and challenge will advance the field of automated brain
metastasis detection and segmentation. |
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ISSN: | 2331-8422 |