Processed MRI Image and Mask Used in "Clustering-based Low-Rank Matrix Approximation: An Adapt" (Subset from BraTS 2020 Dataset)
- Citation Author(s):
-
Sisipho Hamlomo
- Submitted by:
- Sisipho Hamlomo
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- DOI:
- 10.21227/ewrp-2m68
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Abstract
1. MRI (Brain Tumor Segmentation - BraTS 2020) Kaggle Link: https://www.kaggle.com/datasets/awsaf49/brats20-dataset-training-validation BRATS 2020 Dataset Contains multi-modal MRI scans (T1, T1ce, T2, FLAIR) with tumor segmentation masks. 2. Ultrasound (Breast Ultrasound Images) Kaggle Link: https://www.kaggle.com/datasets/aryashah2k/breast-ultrasound-images-dataset Breast Ultrasound Dataset Includes breast ultrasound images (normal, benign, malignant) with lesion annotations. 3. CT (COVID-19 CT Scan Lesion Segmentation) Kaggle Link: https://www.kaggle.com/datasets/maedemaftouni/covid19-ct-scan-lesion-segmentation-dataset COVID-19 CT Lesion Segmentation Dataset Contains lung CT scans with pixel-wise COVID-19 lesion masks. 4. X-ray (COVID-QU-Ex Dataset) Kaggle Link: https://www.kaggle.com/datasets/anasmohammedtahir/covidqu COVID-QU-Ex Dataset Curated chest X-rays (COVID-19, normal, pneumonia) with labels.
Instructions:
This dataset contains the specific MRI slice and associated mask used in the experiments presented in "Clustering-based Low-Rank Matrix Approximation:
An Adaptive Theoretical Analysis with Application to Data Compression". The data is a subset extracted from the publicly available BraTS 2020 dataset [1].
Users interested in the full dataset should refer to the original source.
[1] Menze et al., The Multimodal Brain Tumor Image Segmentation Benchmark (BraTS), DOI: 10.1109/TMI.2014.2377694.
