ArticleBiomedical optics express2019
Dictionary learning sparse-sampling reconstruction method for
Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Image Quality Improvement Techniques and Assessment Adequacy in Clinical Optoacoustic Imaging: A Systematic Review.Biosensors · 2022Pooled it
- Integrating visual state space models with frequency selection for artifact reduction in photoacoustic tomography.Photoacoustics · 2026Article
- Residual-conditioned sparse transformer for photoacoustic image artifact reduction.Photoacoustics · 2025Article
- Quantitative photoacoustic imaging algorithm using sparse decomposition for photoacoustic and ultrasound dual-mode imaging.Biomedical optics express · 2025Article
- Convolutional sparse coding for compressed sensing photoacoustic CT reconstruction with partially known support.Biomedical optics express · 2024Article
- Deep Learning Enhanced Volumetric Photoacoustic Imaging of Vasculature in Human.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Photoacoustic imaging with limited sampling: a review of machine learning approaches.Biomedical optics express · 2023Review
- Application of photoacoustic computed tomography in biomedical imaging: A literature review.Bioengineering & translational medicine · 2023Review
- Image reconstruction for endoscopic photoacoustic tomography including effects of detector responses.Experimental biology and medicine (Maywood, N.J.) · 2022Article
- Dictionary learning technique enhances signal in LED-based photoacoustic imaging.Biomedical optics express · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The sparse transforms currently used in the model-based reconstruction method for photoacoustic computed tomography (PACT) are predefined and they typically cannot capture the underlying features of the specific data sets adequately, thus limiting the high-quality recovery of photoacoustic images. In this work, we present an advanced reconstruction model using the K-VSD dictionary learning technique and present the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.