DEEPMIR: a deep neural network for differential detection of cerebral microbleeds and iron deposits in MRI
@article{Rashid2021DEEPMIRAD, title={DEEPMIR: a deep neural network for differential detection of cerebral microbleeds and iron deposits in MRI}, author={Tanweer Rashid and Ahmed Abdulkadir and Ilya M. Nasrallah and Jeffrey B. Ware and Hangfan Liu and Pascal Spincemaille and Jos{\'e} Rafael Romero and Robert Nick Bryan and Susan R. Heckbert and Mohamad Habes}, journal={Scientific Reports}, year={2021}, volume={11} }
Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and neurodegenerative disorders. Particularly, CMBs are small lesions and require multiple neuroimaging modalities for accurate detection. Quantitative susceptibility mapping (QSM) derived from in vivo magnetic resonance imaging (MRI) is necessary to differentiate between iron content and mineralization. We set out to develop a deep learning…
6 Citations
Computer-Aided Extraction of Select MRI Markers of Cerebral Small Vessel Disease: A Systematic Review
- Psychology, MedicineArXiv
- 2022
This work aimed to summarise published computer-aided methods to examine three imaging biomarkers of CSVD, namely cerebral microbleeds (CMB), dilated perivascular spaces (PVS), and lacunes of presumed vascular origin.
Automated Detection of Cerebral Microbleeds on MR images using Knowledge Distillation Framework
- Computer SciencemedRxiv
- 2021
This work proposes a fully automated, deep learning-based, 2-step algorithm, using structural and anatomical properties of CMBs from any single input image modality for their accurate detection, which is flexible in terms of the input modality and provides comparable clusters-wise TPR and a better cluster-wise precision compared to existing state-of-the-art methods.
A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
- Computer ScienceElectronics
- 2021
The paper presents the main challenges connected with automatic cerebral microbleeds detection, its deep analysis and developed system, and carefully analysed the network predictions and proposed an algorithm for its post-processing.
Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
- Computer ScienceMICCAI
- 2021
MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds
- Computer ScienceArXiv
- 2021
This work proposes a multi-stage approach to both microbleed detection and segmentation, where possible microbleeds locations are detected with a Mask R-CNN technique and a simple U-Net performs the final segmentation.
MixMicrobleedNet: segmentation of cerebral microbleeds using nnU-Net
- Computer ScienceArXiv
- 2021
Cerebral microbleeds are hypointense, small, and round or ovoid lesions [1, 2]; visible on magnetic resonance imaging (MRI) with gradient echo, T2*, or susceptibility weighted (SWI) imaging[3, 4, 5].…
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