Shekhar S. Chandra | DeepAI

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∙ 03/24/2023

Evidence-aware multi-modal data fusion and its application to total knee replacement prediction

Deep neural networks have been widely studied for predicting a medical c...

0 Xinwen Liu, et al. ∙

∙ 03/10/2023

Explainable Semantic Medical Image Segmentation with Style

Semantic medical image segmentation using deep learning has recently ach...

0 Wei Dai, et al. ∙

∙ 03/02/2023

Towards Trustable Skin Cancer Diagnosis via Rewriting Model's Decision

Deep neural networks have demonstrated promising performance on image re...

0 Siyuan Yan, et al. ∙

∙ 02/17/2023

PhaseNet: Phase-Encode Denoising Network for Compressed Sensing MRI

Sparse reconstruction is an important aspect of modern medical imaging, ...

0 Marlon E. Bran Lorenzana, et al. ∙

∙ 12/15/2022

NBC-Softmax : Darkweb Author fingerprinting and migration tracking

Metric learning aims to learn distances from the data, which enhances th...

0 Gayan K. Kulatilleke, et al. ∙

∙ 11/30/2022

Automated anomaly-aware 3D segmentation of bones and cartilages in knee MR images from the Osteoarthritis Initiative

In medical image analysis, automated segmentation of multi-component ana...

0 Boyeong Woo, et al. ∙

∙ 10/01/2022

Cascaded Multi-Modal Mixing Transformers for Alzheimer's Disease Classification with Incomplete Data

Accurate medical classification requires a large number of multi-modal d...

0 Linfeng Liu, et al. ∙

∙ 09/28/2022

Efficient block contrastive learning via parameter-free meta-node approximation

Contrastive learning has recently achieved remarkable success in many do...

0 Gayan K. Kulatilleke, et al. ∙

∙ 04/27/2022

SCGC : Self-Supervised Contrastive Graph Clustering

Graph clustering discovers groups or communities within networks. Deep l...

0 Gayan K. Kulatilleke, et al. ∙

∙ 03/24/2022

Transformer Compressed Sensing via Global Image Tokens

Convolutional neural networks (CNN) have demonstrated outstanding Compre...

0 Marlon Bran Lorenzana, et al. ∙

∙ 03/07/2022

Undersampled MRI Reconstruction with Side Information-Guided Normalisation

Magnetic resonance (MR) images exhibit various contrasts and appearances...

0 Xinwen Liu, et al. ∙

∙ 10/21/2021

FDGATII : Fast Dynamic Graph Attention with Initial Residual and Identity Mapping

While Graph Neural Networks have gained popularity in multiple domains, ...

0 Gayan K. Kulatilleke, et al. ∙

∙ 08/02/2021

Bespoke Fractal Sampling Patterns for Discrete Fourier Space via the Kaleidoscope Transform

Sampling strategies are important for sparse imaging methodologies, espe...

6 Jacob M. White, et al. ∙

∙ 03/31/2021

Deep Simultaneous Optimisation of Sampling and Reconstruction for Multi-contrast MRI

MRI images of the same subject in different contrasts contain shared inf...

0 Xinwen Liu, et al. ∙

∙ 11/27/2020

Manipulating Medical Image Translation with Manifold Disentanglement

Medical image translation (e.g. CT to MR) is a challenging task as it re...

23 Siyu Liu, et al. ∙

∙ 07/07/2020

Automatic lesion detection, segmentation and characterization via 3D multiscale morphological sifting in breast MRI

Previous studies on computer aided detection/diagnosis (CAD) in 4D breas...

0 Hang Min, et al. ∙

∙ 06/28/2020

Fabric Image Representation Encoding Networks for Large-scale 3D Medical Image Analysis

Deep neural networks are parameterised by weights that encode feature re...

0 Siyu Liu, et al. ∙

∙ 06/28/2019

Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNN

Purpose: To propose pseudo-color mammograms that enhance mammographic ma...

6 Hang Min, et al. ∙