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Chapter and Conference Paper
Manifold Learning of COPD
Analysis of CT scans for studying Chronic Obstructive Pulmonary Disease (COPD) is generally limited to mean scores of disease extent. However, the evolution of local pulmonary damage may vary between patients ...
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Chapter and Conference Paper
Modelling Airway Geometry as Stock Market Data Using Bayesian Changepoint Detection
Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exhibit dilation of the airways. Accurate measurement of dilatation enables assessment of the progression of disease. Unfortunately the comb...
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Chapter and Conference Paper
Learning to Address Intra-segment Misclassification in Retinal Imaging
Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one ...
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Chapter and Conference Paper
Prevention of Fault Attacks in ASCON Authenticated Cipher Using Cellular Automata
ASCON is a sponge function based authenticated encryption (AE) scheme chosen in CAESAR competition for lightweight applications. Its suitability for high performance applications make it desirable in environme...
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Chapter and Conference Paper
Strengthening ACORN Authenticated Cipher with Cellular Automata
The authenticated encryption (AE) scheme ACORN v3, a CAESAR competition finalist, has been shown to be particularly vulnerable against Differential Fault Attack (DFA), even more so than its previous version AC...
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Chapter
IIIB: Characterization of Penile Cancers with Comprehensive Genomic Profiling
Penile squamous cell carcinoma (PSCC) can be a devastating disease when major local recurrences and distant spread take place. In the modern era of targeted and immunotherapy approaches to cancer treatments, r...
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Chapter and Conference Paper
Airway Measurement by Refinement of Synthetic Images Improves Mortality Prediction in Idiopathic Pulmonary Fibrosis
Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) are characterised by abnormal dilatation of the airways. Quantification of airway features on computed tomography (CT) can help character...
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Chapter and Conference Paper
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-supervised Segmentation
This paper concerns pseudo labelling in segmentation. Our contribution is fourfold. Firstly, we present a new formulation of pseudo-labelling as an Expectation-Maximization (EM) algorithm for clear statistica...
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Chapter and Conference Paper
Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis
Imaging biomarkers derived from medical images play an important role in diagnosis, prognosis, and therapy response assessment. Develo** prognostic imaging biomarkers which can achieve reliable survival pred...
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Chapter and Conference Paper
Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors
During the COVID-19 pandemic, the sheer volume of imaging performed in an emergency setting for COVID-19 diagnosis has resulted in a wide variability of clinical CXR acquisitions. This variation is seen in the...
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Chapter
Imaging Approach to Interstitial Lung Disease
Imaging with computed tomography is a central and essential component of the diagnostic pathway when evaluating patients with interstitial lung diseases. The salient imaging features required to identify a usu...