14 citations · 62 across the 29 of their papers we have counts for
12 papers · 1 filter
SAMRI: Segment Any MRI
Zhao Wang, Wei Dai, Thuy Thanh Dao +4
Summary: SAMRI is an MRI-specialized adaptation of the Segment Anything Model achieving superior whole-body MRI segmentation, particularly for small and clinically critical structu…
Explainable Semantic Medical Image Segmentation with Style
Wei Dai, Siyu Liu, Craig B. Engstrom +1
Semantic medical image segmentation using deep learning has recently achieved high accuracy, making it appealing to clinical problems such as radiation therapy. However, the lack o…
AliasNet: Alias Artefact Suppression Network for Accelerated Phase-Encode MRI
Marlon E. Bran Lorenzana, Shekhar S. Chandra, Feng Liu
Sparse reconstruction is an important aspect of MRI, helping to reduce acquisition time and improve spatial-temporal resolution. Popular methods are based mostly on compressed sens…
Automated anomaly-aware 3D segmentation of bones and cartilages in knee MR images from the Osteoarthritis Initiative
Boyeong Woo, Craig Engstrom, William Baresic +3
In medical image analysis, automated segmentation of multi-component anatomical structures, which often have a spectrum of potential anomalies and pathologies, is a challenging tas…
Cascaded Multi-Modal Mixing Transformers for Alzheimer's Disease Classification with Incomplete Data
Linfeng Liu, Siyu Liu, Lu Zhang +3
Accurate medical classification requires a large number of multi-modal data, and in many cases, different feature types. Previous studies have shown promising results when using mu…
Structure Guided Manifolds for Discovery of Disease Characteristics
Siyu Liu, Linfeng Liu, Xuan Vinh +4
In medical image analysis, the subtle visual characteristics of many diseases are challenging to discern, particularly due to the lack of paired data. For example, in mild Alzheime…
Undersampled MRI Reconstruction with Side Information-Guided Normalisation
Xinwen Liu, Jing Wang, Cheng Peng +3
Magnetic resonance (MR) images exhibit various contrasts and appearances based on factors such as different acquisition protocols, views, manufacturers, scanning parameters, etc. T…
Automated volumetric and statistical shape assessment of cam-type morphology of the femoral head-neck region from 3D magnetic resonance images
Jessica M. Bugeja, Ying Xia, Shekhar S. Chandra +7
Femoroacetabular impingement (FAI) cam morphology is routinely assessed using two-dimensional alpha angles which do not provide specific data on cam size characteristics. The purpo…
CAN3D: Fast 3D Medical Image Segmentation via Compact Context Aggregation
Wei Dai, Boyeong Woo, Siyu Liu +6
Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of in…
Bespoke Fractal Sampling Patterns for Discrete Fourier Space via the Kaleidoscope Transform
Jacob M. White, Stuart Crozier, Shekhar S. Chandra
Sampling strategies are important for sparse imaging methodologies, especially those employing the discrete Fourier transform (DFT). Chaotic sensing is one such methodology that em…
Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI
Hang Min, Darryl McClymont, Shekhar S. Chandra +2
Previous studies on computer aided detection/diagnosis (CAD) in 4D breast magnetic resonance imaging (MRI) regard lesion detection, segmentation and characterization as separate ta…
Generalisable 3D Fabric Architecture for Streamlined Universal Multi-Dataset Medical Image Segmentation
Siyu Liu, Wei Dai, Craig Engstrom +4
Data scarcity is common in deep learning models for medical image segmentation. Previous works proposed multi-dataset learning, either simultaneously or via transfer learning to ex…