Search Results for author:
Found 18 papers, 8 papers with code
In-vivo high-resolution χ-separation at 7T
The proposed method is compared with alternative pipelines, such as an end-to-end network and linearly-scaled $R_2'$, and is validated against $\chi$-separation maps at 3T, demonstrating its accuracy.
χ-sepnet: Deep neural network for magnetic susceptibility source separation
Magnetic susceptibility source separation ($\chi$-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of para- and diamagnetic susceptibility source distributions in the brain.
Adaptive Selection of Sampling-Reconstruction in Fourier Compressed Sensing
Our method outperforms joint optimization of sampling-reconstruction ($\mathcal{H}_1$) and adaptive sampling ($\mathcal{H}_2$) by achieving significant improvements on several Fourier CS problems.
MOST: MR reconstruction Optimization for multiple downStream Tasks via continual learning
To mitigate this issue, downstream task-oriented reconstruction optimization has been proposed for a single downstream task.
RTP-LX: Can LLMs Evaluate Toxicity in Multilingual Scenarios?
Large language models (LLMs) and small language models (SLMs) are being adopted at remarkable speed, although their safety still remains a serious concern.
A Note on LoRA
LoRA (Low-Rank Adaptation) has emerged as a preferred method for efficiently adapting Large Language Models (LLMs) with remarkable simplicity and efficacy.
QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference
We introduce QUICK, a group of novel optimized CUDA kernels for the efficient inference of quantized Large Language Models (LLMs).
Fast and accurate sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization
In the FACT method, we meta-trained a neural network and a hash-encoder using a few scans (= 15), and a new regularization technique is utilized to reconstruct the details of an anatomical structure.
A human brain atlas of chi-separation for normative iron and myelin distributions
Iron and myelin are primary susceptibility sources in the human brain.
BlindHarmony: "Blind" Harmonization for MR Images via Flow model
These differences in images create a domain gap that needs to be bridged by a step called image harmonization, to process the images successfully using conventional or deep learning-based image analysis (e. g., segmentation).
Coil2Coil: Self-supervised MR image denoising using phased-array coil images
Hence, methods such as Noise2Noise (N2N) that require only pairs of noise-corrupted images have been developed to reduce the burden of obtaining training datasets.
Blocks-World Cameras
For several vision and robotics applications, 3D geometry of man-made environments such as indoor scenes can be represented with a small number of dominant planes.
Deep reinforcement learning-designed radiofrequency waveform in MRI
This work may lay the foundation for an emerging field of AI-driven RF waveform design.
DIFFnet: Diffusion parameter mapping network generalized for input diffusion gradient schemes and bvalues
In this study, a new deep neural network, referred to as DIFFnet, is developed to function as a generalized reconstruction tool of the diffusion-weighted signals for various gradient schemes and b-values.
DeepResp: Deep learning solution for respiration-induced B0 fluctuation artifacts in multi-slice GRE
DeepResp is designed to extract the respiration-induced phase errors from a complex image using deep neural networks.
Image and Video Processing
Expression of Interest for the CODEX-b Detector
A design overview is presented for the CODEX-$\beta$ demonstrator detector, which will enable background calibration and detector design studies.
High Energy Physics - Experiment High Energy Physics - Phenomenology
Stochastic Exposure Coding for Handling Multi-ToF-Camera Interference
As continuous-wave time-of-flight (C-ToF) cameras become popular in 3D imaging applications, they need to contend with the problem of multi-camera interference (MCI).
Artificial neural network for myelin water imaging
Purpose: To demonstrate the application of artificial-neural-network (ANN) for real-time processing of myelin water imaging (MWI).
Image and Video Processing
