research
∙
09/04/2023
SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations
Despite significant progress in semi-supervised learning for image objec...
share
research
∙
05/14/2023
Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection
We propose an embarrassingly simple method – instance-aware repeat facto...
research
∙
08/17/2022
Object Detection for Autonomous Dozers
We introduce a new type of autonomous vehicle - an autonomous dozer that...
research
∙
04/17/2022
Accelerated MRI With Deep Linear Convolutional Transform Learning
Recent studies show that deep learning (DL) based MRI reconstruction out...
research
∙
03/23/2022
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging
Physics-driven deep learning methods have emerged as a powerful tool for...
research
∙
09/23/2021
End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction
Deep learning techniques have emerged as a promising approach to highly ...
research
∙
09/08/2021
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data
Improving speed and image quality of Magnetic Resonance Imaging (MRI) vi...
research
∙
05/17/2021
Unsupervised Deep Learning Methods for Biological Image Reconstruction
Recently, deep learning approaches have become the main research frontie...
research
∙
05/12/2021
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction
High spatial and temporal resolution across the whole brain is essential...
research
∙
05/10/2021
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning
Functional MRI (fMRI) is commonly used for interpreting neural activitie...
research
∙
02/25/2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations
Although deep learning (DL) has received much attention in accelerated M...
research
∙
02/15/2021
Scan-Specific MRI Reconstruction using Zero-Shot Physics-Guided Deep Learning
Physics-guided deep learning (PG-DL) has emerged as a powerful tool for ...
research
∙
11/18/2020
Self-Supervised Physics-Guided Deep Learning Reconstruction For High-Resolution 3D LGE CMR
Late gadolinium enhancement (LGE) cardiac MRI (CMR) is the clinical stan...
research
∙
10/26/2020
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking
Physics-guided deep learning (PG-DL) via algorithm unrolling has receive...
research
∙
08/13/2020
Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI
Purpose: To develop an improved self-supervised learning strategy that e...
research
∙
06/16/2020
Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling
Deep learning based image denoising methods have been recently popular d...
research
∙
05/12/2020
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks
Long scan duration remains a challenge for high-resolution MRI. Deep lea...
research
∙
12/16/2019
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data
Purpose: To develop a strategy for training a physics-driven MRI reconst...
research
∙
12/16/2019
Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms
Inverse problems in medical imaging applications incorporate domain-spec...
research
∙
10/21/2019