10 citations · 18 across the 6 of their papers we have counts for
4 papers · 1 filter
Pre-processing and quality control of large clinical CT head datasets for intracranial arterial calcification segmentation
Benjamin Jin, Maria del C. Valdés Hernández, Alessandro Fontanella +6
As a potential non-invasive biomarker for ischaemic stroke, intracranial arterial calcification (IAC) could be used for stroke risk assessment on CT head scans routinely acquired f…
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT
Alessandro Fontanella, Wenwen Li, Grant Mair +6
Computed Tomography (CT) is commonly used to image acute ischemic stroke (AIS) patients, but its interpretation by radiologists is time-consuming and subject to inter-observer vari…
Challenges of building medical image datasets for development of deep learning software in stroke
Alessandro Fontanella, Wenwen Li, Grant Mair +7
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited. Furthermore, the dat…
ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging
Alessandro Fontanella, Antreas Antoniou, Wenwen Li +4
In some medical imaging tasks and other settings where only small parts of the image are informative for the classification task, traditional CNNs can sometimes struggle to general…