Publications (12)
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network
Reza Akbari Movahed, Abuzar Rezaee, Arezoo Zakeri +3
Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often…
Supervised Saliency Map Driven Segmentation of the Lesions in Dermoscopic Images
Mostafa Jahanifar, Neda Zamani Tajeddin, Babak Mohammadzadeh Asl +1
Lesion segmentation is the first step in most automatic melanoma recognition systems. Deficiencies and difficulties in dermoscopic images such as color inconstancy, hair occlusion,…
High Throughput Computation of Reference Ranges of Biventricular Cardiac Function on the UK Biobank Population Cohort
Rahman Attar, Marco Pereanez, Ali Gooya +6
The exploitation of large-scale population data has the potential to improve healthcare by discovering and understanding patterns and trends within this data. To enable high throug…
Deep-Motion-Net: GNN-based volumetric organ shape reconstruction from single-view 2D projections
Isuru Wijesinghe, Michael Nix, Arezoo Zakeri +4
We propose Deep-Motion-Net: an end-to-end graph neural network (GNN) architecture that enables 3D (volumetric) organ shape reconstruction from a single in-treatment kV planar X-ray…
Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations
Mostafa Jahanifar, Neda Zamani Tajeddin, Navid Alemi Koohbanani +2
Computer-aided diagnosis systems for classification of different type of skin lesions have been an active field of research in recent decades. It has been shown that introducing le…
Weakly-supervised learning for image-based classification of primary melanomas into genomic immune subgroups
Lucy Godson, Navid Alemi, Jeremie Nsengimana +6
Determining early-stage prognostic markers and stratifying patients for effective treatment are two key challenges for improving outcomes for melanoma patients. Previous studies ha…
FractMorph: A Fractional Fourier-Based Multi-Domain Transformer for Deformable Image Registration
Shayan Kebriti, Shahabedin Nabavi, Ali Gooya
Deformable image registration (DIR) is a crucial and challenging technique for aligning anatomical structures in medical images and is widely applied in diverse clinical applicatio…
Nuclei Detection Using Mixture Density Networks
Navid Alemi Koohababni, Mostafa Jahanifar, Ali Gooya +1
Nuclei detection is an important task in the histology domain as it is a main step toward further analysis such as cell counting, cell segmentation, study of cell connections, etc.…
An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation
Soodeh Kalaie, Andy Bulpitt, Alejandro F. Frangi +1
Generative modelling for shapes is a prerequisite for In-Silico Clinical Trials (ISCTs), which aim to cost-effectively validate medical device interventions using synthetic anatomi…
Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework
Navid Alemi Koohbanani, Mostafa Jahanifar, Ali Gooya +1
Nuclear segmentation in histology images is a challenging task due to significant variations in the shape and appearance of nuclei. One of the main hurdles in nuclear instance segm…
UDF-GMA: Uncertainty Disentanglement and Fusion for General Movement Assessment
Zeqi Luo, Ali Gooya, Edmond S. L. Ho
General movement assessment (GMA) is a non-invasive tool for the early detection of brain dysfunction through the qualitative assessment of general movements, and the development o…
Automatic Assessment of Full Left Ventricular Coverage in Cardiac Cine Magnetic Resonance Imaging with Fisher-Discriminative 3D CNN
Le Zhang, Ali Gooya, Marco Pereanez +5
Cardiac magnetic resonance (CMR) images play a growing role in the diagnostic imaging of cardiovascular diseases. Full coverage of the left ventricle (LV), from base to apex, is a…