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∙ 08/09/2023

Geometric Learning-Based Transformer Network for Estimation of Segmentation Errors

Many segmentation networks have been proposed for 3D volumetric segmenta...

0 Sneha Sree C, et al. ∙

∙ 08/09/2023

HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI Reconstruction

Parallel imaging, a fast MRI technique, involves dynamic adjustments bas...

0 Sriprabha Ramanarayanan, et al. ∙

∙ 08/08/2023

SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction

Transformers have emerged as viable alternatives to convolutional neural...

0 Rahul G. S., et al. ∙

∙ 07/15/2023

Automated Knowledge Modeling for Cancer Clinical Practice Guidelines

Clinical Practice Guidelines (CPGs) for cancer diseases evolve rapidly d...

0 Pralaypati Ta, et al. ∙

∙ 07/13/2023

Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning Hypernetworks

Meta-learning has recently been an emerging data-efficient learning tech...

0 Sriprabha Ramanarayanan, et al. ∙

∙ 04/13/2023

Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning

Magnetic Resonance (MR) images suffer from various types of artifacts du...

0 Arun Palla, et al. ∙

∙ 11/28/2022

A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRI

Anomaly detection in MRI is of high clinical value in imaging and diagno...

0 Ayantika Das, et al. ∙

∙ 02/21/2022

MIST GAN: Modality Imputation Using Style Transfer for MRI

MRI entails a great amount of cost, time and effort for the generation o...

0 Jaya Chandra Raju, et al. ∙

∙ 02/10/2021

Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance images

Magnetic Resonance Imaging (MRI) is a valuable clinical diagnostic modal...

0 Madhu Mithra K K, et al. ∙

∙ 07/15/2020

Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks

One of the important parameters for the assessment of glaucoma is optic ...

0 Sharath M Shankaranarayana, et al. ∙

∙ 03/20/2020

Detection and skeletonization of single neurons and tracer injections using topological methods

Neuroscientific data analysis has traditionally relied on linear algebra...

0 Dingkang Wang, et al. ∙

∙ 01/08/2020

DC-WCNN: A deep cascade of wavelet based convolutional neural networks for MR Image Reconstruction

Several variants of Convolutional Neural Networks (CNN) have been develo...

0 Sriprabha Ramanarayanan, et al. ∙

∙ 01/08/2020

A context based deep learning approach for unbalanced medical image segmentation

Automated medical image segmentation is an important step in many medica...

0 Balamurali Murugesan, et al. ∙

∙ 08/25/2019

Recon-GLGAN: A Global-Local context based Generative Adversarial Network for MRI Reconstruction

Magnetic resonance imaging (MRI) is one of the best medical imaging moda...

24 Balamurali Murugesan, et al. ∙

∙ 08/14/2019

Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation

For the task of medical image segmentation, fully convolutional network ...

4 Balamurali Murugesan, et al. ∙

∙ 03/29/2019

Deep Network for Capacitive ECG Denoising

Continuous monitoring of cardiac health under free living condition is c...

0 Vignesh Ravichandran, et al. ∙

∙ 02/12/2019

RespNet: A deep learning model for extraction of respiration from photoplethysmogram

Respiratory ailments afflict a wide range of people and manifests itself...

0 Vignesh Ravichandran, et al. ∙

∙ 02/11/2019

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation

Medical image segmentation is a primary task in many applications, and t...

0 Balamurali Murugesan, et al. ∙

∙ 02/04/2019

Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation

Glaucoma is a serious ocular disorder for which the screening and diagno...

0 Sharath M Shankaranarayana, et al. ∙

∙ 01/25/2019

Joint shape learning and segmentation for medical images using a minimalistic deep network

Recently, state-of-the-art results have been achieved in semantic segmen...

0 Kaushik Sarveswaran, et al. ∙

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