May 19, 2020 · We study the under-explored problem of fine-grained CT segmentation of multiple lesion types (core, blood, oedema) in traumatic brain injury (TBI).
This is the first work to report results for fine-grained multi-class segmentation of TBI in CT and concludes that resampling to isotropic resolution yields ...
We design an empirical study that extensively evaluates the impact of different data preprocessing and augmentation methods. We show that these choices can have ...
Automatic segmentation of lesions in head CT provides key information for patient management, prognosis and disease monitoring.
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation ... M. Monteiro, Kamnitsas K., E. Ferrante, et al. MICCAI Brain Lesion Workshop ...
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BACK. Oxford University · Research · Training · News · Impact ...
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
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... brain tumor image segmentation; ischemic stroke lesion image segmentation ... TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation.
We proposed a novel automatic method for segmenting the hemorrhage subtypes on a CT scan by integrated CT scan with bone window as input of a deep learning ...
... segmentation and quantification of traumatic brain injury lesions on head CT ... Impact of Preprocessing and Data Augmentation", booktitle = "MICCAI Brain ...
Nov 17, 2023 · In this study, we develop an artificial intelligence-based tool to segment brain lesions on admission CT-scan and predict TIL within the first week in the ICU.