23 citations · 26 across the 8 of their papers we have counts for
8 papers
A Quantitative Analysis of Multimodal Biomarkers in Alzheimer's Disease
Antonio Scardace, Daniele Ravì
Despite increasing adoption of multimodal approaches in Alzheimer's Disease (AD) research -- aimed at integrating molecular, structural, clinical, and genetic biomarkers to enhance…
Brain Latent Progression: Individual-based Spatiotemporal Disease Progression on 3D Brain MRIs via Latent Diffusion
Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì
The growing availability of longitudinal Magnetic Resonance Imaging (MRI) datasets has facilitated Artificial Intelligence (AI)-driven modeling of disease progression, making it po…
Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì
In this work, we introduce Brain Latent Progression (BrLP), a novel spatiotemporal disease progression model based on latent diffusion. BrLP is designed to predict the evolution of…
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…
Deformably-Scaled Transposed Convolution
Stefano B. Blumberg, Daniele Raví, Mou-Cheng Xu +3
Transposed convolution is crucial for generating high-resolution outputs, yet has received little attention compared to convolution layers. In this work we revisit transposed convo…
An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training
Daniele Ravi, Frederik Barkhof, Daniel C. Alexander +3
Large medical imaging data sets are becoming increasingly available, but ensuring sample quality without significant artefacts is challenging. Existing methods for identifying impe…
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia
Daniele Ravi, Stefano B. Blumberg, Silvia Ingala +3
Accurate and realistic simulation of high-dimensional medical images has become an important research area relevant to many AI-enabled healthcare applications. However, current sta…
Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
Daniele Ravi, Daniel C. Alexander, Neil P. Oxtoby
Simulating images representative of neurodegenerative diseases is important for predicting patient outcomes and for validation of computational models of disease progression. This…