Demo Data from SIGIR 2026 / reviewers in the wild / expert
Paritosh J. Dhawale
dblp:29/3683
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 50% Audio and music processing · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › medical imaging
magnetic resonance imaging |
0.1 | 1 | 2005 | Single Image Phase-Based MRI Fat Suppression Expectation Maximization Algorithm · CVPR (2) 2005 |
Medical and health informatics
medical imaging |
0.1 | 1 | 2005 | Single Image Phase-Based MRI Fat Suppression Expectation Maximization Algorithm · CVPR (2) 2005 |
Image and video processing
image reconstruction |
0.0 | 1 | 2005 | Single Image Phase-Based MRI Fat Suppression Expectation Maximization Algorithm · CVPR (2) 2005 |
Audio and music processing › acoustic signal processing › audio signal reconstruction
phase reconstruction |
0.0 | 1 | 2005 | Single Image Phase-Based MRI Fat Suppression Expectation Maximization Algorithm · CVPR (2) 2005 |
Methods — techniques the papers use, named apart from their topics
phase-based estimation · 0.1expectation-maximization · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Single Image Phase-Based MRI Fat Suppression Expectation Maximization AlgorithmabstractMRI fat suppression techniques are primarily approached by variations of the phase based methods. Multipoint methods dominate the literature, specifically methods that require the acquisition of three images at different echo times. These methods estimate the contribution of fat and water signals by solving a set of equations using echos acquired with the relative phase of fat and water at -/spl pi/, 0, /spl pi/. We present a novel approach to fat suppression that requires only a single image. Using an expectation maximization algorithm on a gradient echo image with the relative phase of fat and water at approximately /spl pi//2, the pixel composition and inhomogeneity of the magnetic field are estimated. Fat suppressed images are generated from estimated inhomogeneity. Our method does not need custom pulse sequences. Results from mathematical phantoms and volunteer images are reported. Daniel J. Blezek, W. Thomas Dixon, Paritosh J. Dhawale |
CVPR (2) | 3 |