19 citations · 42 across the 18 of their papers we have counts for
6 papers · 1 filter
A 3D deep learning classifier and its explainability when assessing coronary artery disease
Wing Keung Cheung, Jeremy Kalindjian, Robert Bell +11
Early detection and diagnosis of coronary artery disease (CAD) could save lives and reduce healthcare costs. The current clinical practice is to perform CAD diagnosis through analy…
Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance
Wing Keung Cheung, Ashkan Pakzad, Nesrin Mogulkoc +14
The morphology and distribution of airway tree abnormalities enables diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airw…
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images
Olga Fourkioti, Matt De Vries, Chen Jin +2
The visual examination of tissue biopsy sections is fundamental for cancer diagnosis, with pathologists analyzing sections at multiple magnifications to discern tumor cells and the…
Expectation Maximization Pseudo Labels
Moucheng Xu, Yukun Zhou, Chen Jin +5
In this paper, we study pseudo-labelling. Pseudo-labelling employs raw inferences on unlabelled data as pseudo-labels for self-training. We elucidate the empirical successes of pse…
A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study
Yaozhi Lu, Shahab Aslani, An Zhao +5
In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respirat…
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification
Lemuel Puglisi, Frederik Barkhof, Daniel C. Alexander +3
Recent advances in MRI have led to the creation of large datasets. With the increase in data volume, it has become difficult to locate previous scans of the same patient within the…